ExtendSim Adopter Program

ExtendSim Adopter These accredited institutions are giving their students a competitive edge by teaching simulation techniques and principles using the same product these students will use once they graduate... ExtendSim. Future engineers (civil, irrigation, cyber security, industrial, traffic systems, biochemical, construction, mining, etc.), business professionals (health care managers, policy & process managers, risk analysts, technology managers, economists, etc.), operations managers (service ops, supply chain, logistics planning, manufacturing systems, etc.), data & statistical analysts, and others are using ExtendSim to learn how simulation can help them advance in their careers.

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Arab Academy for Science, Technology, and Maritime Transport

College of Engineering and Technology
Department of Industrial and Management Engineering
AbuKir Campus, Alexandria, Eqypt

Courses ExtendSim has been used in

Adopter since 2011 Discrete Event System Simulation - IM528/IM729
Prof. Khaled El-Kilany, PhD

Student head count

10-31 Undergraduate and Postgraduate Students, depending on the semester

How ExtendSim typically is used in the course

Every aspect of simulation is taught through a set of case studies of varying complexities. The ACME Steel and the ITI ED case studies in the companion DESS e-book are among these set of case studies and are highly recommended, in addition to other set of comprehensive problems developed over the past years. Simulation parameters setting (run length, warm-up period, and number of replications); input modelling (using StatFit to fit distribution to datasets and selection of most suitable distribution); reporting simulation output (graphically using plotters and statistically using Mean and Variance and Stat blocks); and analyzing output (comparing scenarios and using Common Random Numbers). In addition to covering most of the blocks used in the item library that are useful in modelling various systems such as activities (setting capacity, random delays, delays based on attributes, and shutdown); queues (limited/unlimited, sorting items based on FIFO/priority/based on attribute, resource pool); routing (catch and throw, select item out/in based on attribute, random, and priority); resources (resource pools, resource release, and shifts); and information blocks for reporting cycle time and throughput. Also, a set of basic problems are taught in tutorials these problems introduces the development of basic reusable models that can be used by the students to model most real-life problems and would be useful when developing models for their term projects.

Student projects

During the first semester the students successfully fulfilled 6 projects. Some of the projects were based on a real-life case either in manufacturing or service. Specifically, modelling and simulation of an assembly line for car valves to determine the suitable number of operators needed to achieve an expected demand (data was collected by a student during a previous summer training in Germany), evaluating the impact of increasing resources in a dental clinic on the average length of stay of patients, and identifying the times of peak demand and waiting times in a pharmacy and scheduling pharmacists and employees accordingly. Two other groups, due to COVID-19 and country-wide lockdown, developed simulation models of the Intel Five-Machine Six Step Mini-Fab, which is a well-known problem in literature having a detailed description available online. As for the second semester, the Intel Five-Machine Six Step Mini-Fab problem was provided to 2 groups of students and both groups developed different models and scenarios for the same case.

Student projects over the years

AASTMT Medical Services Facility • Simulation of a queueing system
Bank • Queuing analysis
Bread Production Line • Capacity analysis of the production line
Cab Services Company • Optimization of the number of cars be used by the company
Car Filters Manufacturer • Capacity analysis
Car Spare Parts Manufacturer • Bottleneck analysis of a line within the manufacturing facility
Carrier Air-Conditioning Factory • Analysis of cycle time
Computer Service Center (on campus) • Modelling of different services offered and their combinations with the objective of maximizing the number of students served per day
Fast Food Restaurant • Order processing simulation
Gas Station • Analysis of service and performance of queues
ISP in Alexandria • Study of a multi-channel, multi-phase queuing system for an internet service provider
Marine Structure Fabrication Process • Optimization of resource usage
McDonald's • Simulation of queues buildup during rush hours to determine the number of cashiers to operate
Mobinil • Model this mobil carrier network in Egypt
On Campus Cafeteria • Simulation of available capacity and queues
QNB Bank (International Bank in City of Alexandria) • Simulation of different service offerings, employees schedules, and queues
Restaurant • Queuing analysis
Starbucks Cafe in Alexandria, Egypt • Analysis of queue buildup
Steel Manufacturer • Simulation of cold direct reduction iron briquette system with the objective of assessing the overall performance of the system and optimizing the production rates of the different equipment used
Structural Steel Fabrication Facility • Bottleneck analysis
Textile Coating Line • Modeling and simulating the line
Traffic Light Signal Analysis • Study of the duration of the different light signals on the number of cars waiting in queue
A variety of other companies in Eqypt • Credit Agricole Bank, Dental Arts Clinic, Metro, Mobil Gas Station
A variety of other real manufacturing systems in Eqypt • Evaluation of different maintenance plans in a sheet metal works company, analysis of traffic light signal timing, bottleneck analysis for bottled juice producer, capacity analysis of a beverage manufacturer, queuing system at a mobile service provider, and assessing the impact of adding additional filling machine in a yogurt production facility

Ease with which students learn to model with ExtendSim

Through the years of using ExtendSim in this course, students have always found it easy to develop simulation models, better understand the simulation concepts, and are always excited doing the models. I usually schedule the lecture and the tutorial back to back to give enough time to develop complete models for the case studies. A minimum of 5 case studies were covered in each semester; in addition, a set of simplified problems covering a single modelling approach or a simulation concept are done in the tutorial.

Thanks to the Adopter program, students develop their models during the lecture and tutorial with the professor and/or the TA. Once again, thanks to Imagine That, the students were able to download the free versions of the ExtendSim 10 student versions. If it wasn’t for Imagine That commitment and instant response to the COVID-19 pandemic, this course wouldn’t have been delivered in such a smooth and successful way.

Benefits attained through the use of ExtendSim

It is always much easier and more beneficial to use ExtendSim in teaching any simulation course compared to the conventional method of delivering a simulation course without any hands-on experience and/or developing the students’ practical and transferable skills. This semester I noticed several students continue using ExtendSim in their graduation projects and even apply for the ExtendSim Research Grant and successfully obtain it, which is all attributed to the knowledge and hands-on experience they gained in the IM528 course.

ExtendSim helps always in improving the students' abilities in model development, critical thinking, practical and transferable skills. They always consider this as an enjoyable learning experience and through the use of ExtendSim they grasp the basic concepts of simulation such as random number generation, setting the different simulation parameters, verification and validation... etc.

ExtendSim helped a lot in visualizing the systems under study. Various reports generated helped the students to further refine their analysis capabilities and enabled them in identifying and testing improvements to their models. It also helped Prof. El-Kilany in explaining several simulation concepts; such as, random number generation, setting simulation parameters, variance reduction techniques, and comparison of systems. Without ExtendSim, students would have never understood the importance of such concepts and their application when developing simulation models.

Rather than having a raw theoretical course about simulation with probably some spreadsheet applications of abstract problems, ExtendSim helped students in understanding the essence of simulation practice and theory and helped them in addressing more complex and realistic problems. In Prof. El-Kilany's opinion, the best aspect of using ExtendSim is the flexibility it provides in developing simulations for different situations and systems easily and its ability to model the same problem in various ways. This helps in building students' intuition and skills and helps the instructor in conveying model building knowledge in several approaches. ExtendSim is a suite that includes all the tools to successfully show the various concepts of simulation and complete a simulation study - animation, database, scenario manager, optimizer, distributing fitting, etc. Also, the libraries and blocks are very easy to deal with and develop various models.

Future plans for ExtendSim at AASTMT

Based on recommendations by ABET PE, the simulation course will be a compulsory course. So, they're expecting more students to enroll for the course at the undergraduate level. It continues to be used for illustrating several concepts in Factory Physics and Production Planning and Control courses. ExtendSim helps the students understand concepts of scheduling, production line flow control, and variability analyses; however, I use it for illustration purposes only and students are not asked to develop any models on their own in these courses.

Conference papers submitted based on models developed in this course

G. Y. Moustafa ; N. M. Galal, and K. S. El-Kilany, “Sustainable Dynamic Pricing for Perishable Food with Stochastic Demand” in Proceedings of the IEEE International Conference on Industrial Engineering and Engineering Management (IEEM2018), Bangkok, Thailand, 16-19 December 2018. Hagar H. Amer, Noha M. Galal, Khaled S. El-Kilany, “A Simulation Study of Sustainable Agri-Food Supply Chain”, Proceedings of the International Conference on Industrial Engineering and Operations Management, Paris, France, July 26-27, 2018.

Yassin M. Shaalan, Ingy A. El-Khouly, and Khaled S. El-Kilany, “Simulation Analysis of Segmented CONWIP: Application to Reentrant Flow Lines”, Proceedings of the International Conference on Industrial Engineering and Operations Management, Bandung, Indonesia, March 6-8, 2018.

N. Galal, and K. S. El-Kilany, “Sustainable Agri-Food Supply Chain with Uncertain Demand and Lead Time”, International Journal of Simulation Modelling, vol. 15, no. 3, pp. 485-496, 2016.

J. El-Zoghby, H. A. Farouk, and K. S. El-Kilany, “Discrete Event Simulation of Patients’ Flow in an Emergency Department”, in Proceedings of the 2016 Industrial and Systems Engineering Research Conference, Anaheim, California, 2016.

J. El-Zoghby, H. A. Farouk, and K. S. El-Kilany, “An Integrated Framework for Optimization of Resources in Emergency Departments”, in Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management, Kuala Lumpur, Malaysia, 2016.

Nayera E. El-Gharably, Khaled S. El-Kilany, and Aziz E. El-Sayed, "Optimization Using Simulation", World Academy of Science, Engineering and Technology, vol. 78, 2013.

Sherine Beshara, Khaled S. El-Kilany, Noha M. Galal, “Simulation of Agri-food supply chain”, presented May 13, 2012 at WASET 2012 Amsterdam International Conference.

El-Kilany, K.S., "Wafer lot release policies based on the continuous and periodic review of WIP levels", presented at Industrial Engineering and Engineering Management (IEEM), 2011 IEEE International Conference.

Arab Academy - Industry Service Complex

Arab Academy - Technical and Vocational Institute

Professional Engineering
Alexandria, Egypt

Courses ExtendSim is used in

Adopter since 2024
Professor Islam Ibrahim Mohamed ElBanna

Managing a Professional Engineering Project
Professional Engineering Management (Target)
Research Project

Type of course

100 students per year at Level 5 Higher National Diploma in Engineering

Course overview

Unit 35: Professional Engineering Managemen Engineers are professionals who can design, develop, manufacture, construct, operate and maintain the physical infrastructure and content of the world we live in. They do this by using their academic knowledge and practical experience, in a safe, effective and sustainable manner, even when faced with a high degree of technical complexity.

The aim of this unit is to continue building up on the knowledge gained in Unit 4: Managing a Professional Engineering Project to provide students with the professional standards for engineers and to guide them on how to develop the range of employability skills needed by professional engineers. Among the topics included in this unit are:

Engineering strategy and services delivery planning
The role of sustainability
Total Quality Management (TQM)
Engineering management tools
Managing people and becoming a professional engineer

On successful completion of this unit, students will be able to construct a coherent engineering services delivery plan to meet the requirements of a sector-specific organisation or business. They will display personal commitment to professional standards and obligations to society, the engineering profession and the environment.

Concepts to be taught in the course

Modeling and Simulation in Manufacturing
Perform experiments
Statistical Analysis
Controlling resources and activities
Improving performances
Optimizing flows or cycle times
Project Scheduling
Strategic Development
Research Six Sigma Process Improvement
Assigning Equipment
Testing the Effectiveness
Analyzing Costs
Launching New Prototypes
Providing support for scheduling
Evaluating the performance

Student projects

Students Graduation -Research Projects
Managing of engineering services delivery plan that meets the requirements of a sector-specific organisation
Review commercially available project management tools/software to select most suitable
Consideration of requirements of the chosen project, difference between systems (e.g. Prince 2) and software (e.g. PMIS, Microsoft Project, PROMIST)
Task and tracking tools and techniques (e.g. Trello, Smartsheet, Excel)
Scheduling and time planning (Gantt chart or similar)
Network diagrams
Types and applications
Critical-path methods (PERT)
Budget management tools Methodologies (e.g. waterfall, Agile, Scrum, Kanban, Scrumban, eXtreme programming (XP), Adaptive Project Framework (APF), Lean)
Project management techniques (e.g. SWOT, stakeholder matrices, risk mapping, radar chart and summary risk profiles).

Ateneo de Davao University

Benedictine University

College of Business
Department of Undergraduate Business
Lisle, IL USA

Course ExtendSim is used in

Adopter since 2014 Business Process Modelling - BALT350
Dr. Deborah Cernauskas

Type of course

Undergraduate, Junior/Senior level course that has grown from 15 to 32 students

How ExtendSim typically is used in the course

The class is a part of the Business Analytics major in the undergraduate program at Benedictine University in Lisle, IL. The focus of this class is on understanding how to build simulation models for business processes to determine how changes to the process will impact the process either positively or negatively. ExtendSim is the core of the course used as a basis for understanding how to model current state and modify to implement change. Students are reliant on the software to build simulation models and to get an understanding on how processes work. They learn how to evaluate, model, and restructure processes using ExtendSim. Business process analysis and improvements are modeled using the software. For example, in the Spring of 2018, students used the software to modeling business processes such as lines at an amusement park.

Student projects

Students are required to complete two projects: a team project which is presented at an in-house research symposium and an individual project that students complete and write up a report describing current and future state models. This fits with our objectives to teach students communication skills along with their technical knowledge. Many of the models created are highlighted under the ExtendSim Use in Higher Education tab on the Showcase page.

The team project is for the Benedictine Undergraduate, Research, Scholarship and Arts Symposium (URSA) which is held during the spring semester on campus. Undergraduate students present projects they have worked on in their classes. Projects have included improving the ordering process at a local restaurant.

Every student was also required to develop and write up a model that included a model of the current state process with an improved model. Students were required to include KPIs for the current and proposed state models.

Ease with which students learn to model with ExtendSim

Students like using the software and find ExtendSim easy to learn and use. Most students learned the basics quickly. The software makes learning simulation modeling very easy.

Benefits attained through the use of ExtendSim

Students learn queueing theory without having to learn all the horrendous equations typically involved. They gain an understanding of inefficiencies and bottlenecks in processes and how to find solutions. They have learned how to use a simulation modeling tool which will be very beneficial in their careers. Students do not have to write code. Most students in the College of Business do not want to write code, but enjoy building models with the drag and drop icons. Since they can learn to use the software quickly, they want to continue using it after graduation.

Additional comments

I like the software. I find it easy to use and the students have few hurdles in learning.

Campus ESPRIT

Delft University of Technology

Dublin City University

Faculty of Engineering & Computing
School of Mechancal & Manufacturing Engineering
Dublin, Ireland

Course ExtendSim is used in

Adopter since 2015 Manufacturing Systems Simulation - MM584
Prof. John Geraghty

Type of course

Masters course with 45 students

How ExtendSim typically is used in the course

ExtendSim is used in the labs to demonstrate and support student understanding of theory and gain practical experience in the art of simulation model development, validation, and experimental design and analysis. And, to support the deepening of their understanding of manufacturing systems' behaviour and performance.

Student projects

Weekly lab exercises linked directly to the lecture material delivered in the previous week. These as small simulation models and students submit written reports detailing the model development and the results of their study. A large individual project to develop a simulation model for an industrial problem over the course of semester is also set as challenge for the students. They can propose their own study of a system they are familiar with or select one from a list of projects provided by the lecturer.

Students typically complete 12 lab sessions on ExtendSim throughout the semester. The first five labs (based on guided tutorial exercises) are submitted for grading (20% of module grade). The remaining labs are designed to support knowledge acquisition required to complete a large individual modelling exercise (30% of module grade) based on integrating an assembly line and a job-shop environment with the goal of maximizing the throughput of the system while minimizing the work-in-process. Two reports are required, one detailing the development and validation of the model and the other documenting the experimental results and implications for the effective management of the system studied.

Ease with which students learn to model with ExtendSim

Students find the software is intuitive and relatively easy to learn basic simulation modelling constructs and concepts. They also like the flexibility within the software to leverage other developments through hierarchical modelling or to develop their own objects using ModL. Overall, feedback from the students is that ExtendSim allows them to develop models to test the limits and applicability of the the theoretical aspects of the module very easily.

Benefits attained through the use of ExtendSim

Learning the basics of how to interact with the software and develop simulation models is relatively straightforward and easily supported through the documentation provided with the software and the lab material developed by the lecturer for this module. This means that we can very quickly move from learning how to use the software to developing practical understanding of the theoretical principles of simulation that are explored in the lecture series. Students gain an understanding of the modelling environment so quickly that lab hours can be devoted to learning how to model and analyse problems in manufacturing systems rather than learning the software itself. Students engage with the module more enthusiastically. Since adopting ExtendSim many more students express interest in completing their dissertation on topics that require/could use discrete event simulation as the main modelling tool. I can easily map the theory onto very simple modelling examples that highlight the practical implications of the theory in a manufacturing environment. ExtendSim is now fully integrated into the module and all lectures have supporting labs and models that easily illustrate the theoretical concepts from the notes.

Emory University

Goizueta Business School
Department of Information Systems and Operations Management
Atlanta, GA USA

Course ExtendSim is used in

Adopter since 2014 Healthcare Operations and Technology Management - BUS652
Prof. KC Diwas

Type of course

MBA-level elective course with approx. 35 students

How ExtendSim typically is used in the course

ExtendSim was used in an MBA-level elective course titled “Healthcare Operations and Technology Management” (BUS652) at the Goizueta Business School at Emory University in the spring semester of 2014. In this course, students apply management tools to examine the health care value chain. Specifically, we learn to analyze health care organizations using qualitative as well as quantitative principles of operations management, and develop solutions to problems that are commonly encountered. The course is organized around four key modules:

Designing healthcare delivery options.
Capacity planning and decision making under uncertainty.
Process failure, learning, and improvement.
Innovations in healthcare.

Students learn from case discussions, lectures, problem solving, in-class exercises, and guest speakers from the healthcare industry. Case settings involve the key stakeholders in the healthcare industry, viz., hospitals and clinics, pharmaceutical companies, medical device manufacturers, IT providers, regulatory agencies, and doctors and patients. Students also learn to use ExtendSim, an award winning simulation tool, to supplement our understanding of process analysis and decision making under uncertainty.
Following the first and second modules on designing healthcare delivery system, and on capacity planning and decision-making under uncertainty, students map out patient process flows using ExtendSim. The goal is to:

develop a better understanding of the dynamics of process flows, and
examine “what-if” scenarios involving process level changes that could impact overall performance, including patient length of stay, throughput and waiting times.

Student projects

Students were assigned a homework problem set, consisting of various problems, which needed to be modeled in ExtendSim. The goal was to develop the ability to translate a verbal description of a business problem into a discrete event simulation model, which would help to generate useful managerial insights.

Benefits attained through the use of ExtendSim

Students greatly appreciated the utility of the ExtendSim tool, and its wide applicability to a range of business problems.

European Universities in Egypt

Fairfield University

George Mason University - School of Business

Costello College of Business
Area of Information Systems and Operations Management
Fairfax, VA USA

Courses ExtendSim is used in

Adopter since 2018 OM 435 • Business Process Analysis and Simulation
Professor Hang Ren
OM 303 • Operations Management

Type of course

OM 435 is an Undergraduate elective course with 17 to 38 students

OM303 is a required Undergraduate course with 120 students

How ExtendSim typically is used in the course

OM 435 • Every firm needs to manage a variety of processes that consist of activities with different functions owned by different departments. Each process needs to be effective and efficient on the whole, yet managers typically focus on their own departments and miss opportunities for process improvement. This course introduces concepts and tools used in designing, modeling, analyzing, and improving business processes. Analytical tools such as process analysis and queueing analysis are discussed, and process simulation methods using ExtendSim are introduced. Hands-on experiences (group assignments and in-class examples) are provided for students to apply analytical and simulation skills to solve real-world problems. Students learn basics, data input & output, attributes, resources, costs, and output data analysis.

OM 303 • Prof. Ren simulates projects in ExtendSim to demonstrate key concepts in process management and service operations. Students have hand-ons experiences with these concepts by playing with the software.

Student projects

A group project where students identify a real-world problem, model it using ExtendSim, propose an improving process, and use ExtendSim to evaluate the performance of the new process.

There are no student projects in OM 303 as students will simply be running pre-built models.

Ease with which students learn to model with ExtendSim

Easy. Students learned the basic building blocks quite easily, but struggled with more advanced features like the Equation block, batching/unbatching, and resource pools.

Benefits attained through the use of ExtendSim

Students reported that they learned a lot from simulation and liked that. Hands-on experience with key OM concepts.

George Mason University - Volgenau School of Engineering

George Washington University

School of Business
Department of Decision Sciences
Washington DC, USA

Course ExtendSim is used in

Adopter since 2020 DNSC6225: Business Process Simulation
Prof. Sanjay Jain

Student head count

30 graduate students

How ExtendSim typically is used in the course

The class teaches business process modeling using ExtendSim. We use the textbook "Business Process Modeling, Simulation and Design" by Manuel Laguna and Johan Marklund that is based on ExtendSim. Most of the sessions in the class are divided in two parts - one on business process modeling and the other on learning ExtendSim.

The course examines the key methods used to analyze, develop and improve processes in a given organization. The objective is to develop an understanding of the trade-offs and limitations involved in process design, as well as to develop an understanding of many of the basic tools used to analyze and improve processes. In addition, students learn how to test the performance of existing and proposed processes by building simulation models using a powerful discrete-event simulation tool used frequently in industry. The course is intended to be hands-on and application oriented, and helps students acquire the requisite skills for adopting a process-oriented approach when undertaking major projects.

Student project

Students work on 3 individual assignments that require successively more complicated ExtendSim models, and then do a group project that involves building an AS-IS and a TO-BE model using ExtendSim of a selected business process.

Ease with which students learn to model with ExtendSim

The class is only 7 weeks long so students do go through a steep learning curve but majority of students are able to develop ExtendSim models by the end of the class.

Benefits attained through the use of ExtendSim

Students learn the concept of simulation and its applicability to improving business processes.

Future plans for ExtendSim at GWU

I plan to continue using ExtendSim in the Business Process Simulation class that is taught every Spring.

German-Kazakh University

Faculty of Engineering and Information Technology
Department of Logistics
Almaty, Kazakhstan

Course ExtendSim is used in

Adopter since 2014 Simulation of Logistics Processes
Professor Zhandos Kegenbekov

Type of course

3rd year Bachelor's degree, 1st year Master's degree course with about 50 students

How ExtendSim typically is used in the course

Students and undergraduates imitated logistics processes with the help of ExtendSim, optimized the supply chain, and obtained optimal solutions for organizing transportation processes, warehousing, and production processes.

Student projects

Simulation of a supply chain between a producer and a market and evaluation of different order strategies.

Ease with which students learn to model with ExtendSim

Due to comprehensive documentation and the video tutorials good support for learning progress of students

Benefits attained through the use of ExtendSim

Combination of continuous, discrete rate and discrete event simulation. Different simulation paradigms within one tool for introducing logistics engineering students to simulation. Students learned how to support the planning and decision making processes in logistics with the help of discrete-event simulation models

Additionally, ExtendSim is being used in the following course

Logistics Networks and Supply Chain Management
Tobias Reggelin

Type of course

Undergraduate with 30-35 students, depending on the semester

How ExtendSim typically is used in this course

5 Student groups with 6 or 7 students in each group solve logistics planning problems with the help of a simulation study with ExtendSim.

Student projects

Simulation of a supply chain between a producer and a market and evaluation of different order strategies.

Ease with which students learn to model with ExtendSim

Due to comprehensive documentation and the video tutorials good support for learning progress of students.

Benefits attained through the use of ExtendSim

The combination of different simulation paradigms - continuous, discrete rate, and discrete event simulation - within one tool is ideal for introducing logistics engineering students to simulation. Students learned how to support the planning and decision making processes in logistics with the help of discrete-event simulation models.

Hereford Sixth Form College

Hofstra University

Frank G. Zarb School of Business
Department of Management, Entrepreneurship & General Business
Hempstead, NY USA

Course ExtendSim is used in

Adopter since 2011 Business Process Management
Dr. Kaushik Sengupta

Type of course

Course has grown from 15 to 35 MBA and MS students, depending on the semester

How ExtendSim typically is used in the course

ExtendSim is used to illustrate the application of simulation concepts in business process modeling and analysis. It is used during the part of the course where students model business scenarios, case based models and practical models to understand the nuances of simulation. Spend about 5 weeks in the 15-week semester using the software.

Student projects

Students initially use the software on small exercises and then work on more extended assignments which entails modeling of operating systems based on cases and experiential projects. Students will work on group projects on actual companies - previous examples have modeled car wash operations, banks, gyms and airlines. Examples on specific scenarios, group project that has to be modeled on ExtendSim, experiential learning opportunity.

Ease with which students learn to model with ExtendSim

Quite easy with some in-class discussions and the user manual. It does take some time for them to learn what each block does. The other part of the learning curve for them was to understand the overall structure of a simulation model.

Benefits attained through the use of ExtendSim

I cannot think of doing this class in any other way, other than using a software like ExtendSim. It is really fabulous to be able to use this in an academic setting with the way the licensing is set up. The practical use of a commercial software gives students invaluable experience to have an experiential class rather than a theoretical class. Practical knowledge of a commerical simulation software, nuances of simulation which would not be possible to teach otherwise.

Comments

Thanks for offering this licensing option - it is one of the best in the industry.

Jan Amos Komenski University of Applied Sciences in Leszno

Institute of Economy and Space Management
(Instytut Gospodarki I Zarządzania Przestrzenią)
Leszno, Poland

Course ExtendSim is used in

Adopter since 2020 Logistics Engineering, Logistics Technology, & for Bachelor theses
Prof. Piotr Sawicki

Student head count

37 undergrad students

How ExtendSim is used in the course

ExtendSim was used in the academic year 2020-21, as part of two optional courses (Logistics Engineering; Logistics Technologies) and for research as part of the BA thesis. As part of both completed courses, due to the COVID pandemia, the software was installed as a resource made available through a virtual laboratory, which allowed to remote classes use of ExtendSim, both during the lectures and tutorials. During the lectures, students were acquainted with the background of simulation modeling and the key features of the tool. During the online meetings, a common work was carried out on the design of simulation models of the analysed case studies - a simulation assessment of the benefits of the practical application of various logistic solutions and technologies.

Student projects

During tutorials all students of both courses (Logistics Engineering, Logistics Technologies) have individually use the ExtendSim. Their task was to solve simple decision problems, to demonstrate knowledge of the basics of simulation modeling and providing an ExtendSim based answer and recommendations. The crowning achievement was a design of the final 2-person team projects. Its result was the basis of the final assessment of their work and the level of acquired knowledge and skills.

Ease with which students learn to model with ExtendSim

Due to the limited time allocated to each individual course (15 hours / semester), the complexity of knowledge regarding simulation and the advancement of the simulation models were at an average level. Nevertheless, at this stage of getting knowledge and the practical usage of ExtendSim, the opinions of students about the ease learn simulation were consistent - the tool is user-friendly. In addition, all students have participated previously in the course entitled Process Design where they got an experience in modelling and simulation of business processes using ARIS Architect and Designer. This circumstance seems to have made the task easier.

Benefits attained through the use of ExtendSim

The key benefit of using ExtendSim was to proactively learn about a new and more advanced tool for solving engineering problems. The earlier use of ARIS was characterized by many limitations of its use in the field of engineering.

Future plans for ExtendSim

I’m planning to use this tool in following editions of the same subjects and, to a greater extent, in the implementation of bachelor's theses.

Johns Hopkins University

Carey Business School
Operations Management Department
Baltimore, MD USA

Course ExtendSim is used in

Adopter since 2012 Professor Chester Chambers

Fundamental of Healthcare Operations
Healthcare Operations and Quality Improvement
Managing Medical Services

Type of courses

Masters level courses with 20-30 students, depending on the semester

How ExtendSim typically is used in each course

In the Fundamental of Healthcare Operations course, ExtendSim is used for the course capstone project.

In the Healthcare Operations and Quality Improvement course, ExtendSim was used as part of case analysis and student projects.

In the Managing Medical Services course, ExtendSim was used as part of homework assignments on process re-engineering. In particular students used ExtendSim to create simulation models of a pharmacy prescription fulfillment process. This exercise supplemented case analysis and classroom discussion. Students were provided with instruction on model development via use of videos distributed via YouTube. ExtendSim was later used as part of a more complex case analysis exercise focused on management of cycle times and waiting times in a real specialty clinic with Johns Hopkins Outpatient Center. Instructor provided activity time data as part of case study for the students to start model development.

Student projects

In the Fundamental of Healthcare Operations course, ExtendSim was used for the course capstone project. The Case - Miller Pain Treatment Center was published in Informs Transactions on Education.

In the Healthcare Operations and Quality Improvement course, case analysis is tied to use of ExtendSim models of an outpatient clinic.

In the Managing Medical Services course, student teams created and altered models of appointment based outpatient clinics. This was done in conjunction with discussion of a case written by course instructor. Student models were used to analyze questions involving patient unpunctuality, resource levels, pre-processing, and schedule formulation. Students also compared performance in simulated clinics in private practice and an Academic Medical Center. Final projects were presented to clinic director for comment and evaluation.

Ease with which students learn to model with ExtendSim

Key elements in using ExtendSim in this course were providing students with a basic model that they could manipulate and alter to address more detailed questions. Also, use of videos on model development allowed the instructor to minimize classroom time covering technical details to less than 2 hours. Students worked in teams on all simulation related assignments so they could help each other over technical hurdles.

Benefits attained through the use of ExtendSim

ExtendSim helps prepare students for consulting in the healthcare field. Students can get involved with complex questions such as value of parallel processing, evaluation of alternative patient schedules, and hypothetical exercises involving changing resource levels and pre-processing of patients. These experiments could not be done in clinic without affecting care delivery. Use of simulation allows researchers to show clinic directors the potential impacts of changes to delivery system.

ExtendSim was used in published research involving the same medical clinic. It was key to be able to use the same tool and models in research as well as classroom exercises.

Conference papers submitted based on models developed in this course

Chester Chambers, Johns Hopkins Carey Business School; and Kayode Williams, Department of Anesthesiology and Critical Care Medicine, Johns Hopkins School of Medicine, "Case - Miller Pain Treatment Center", INFORMS Transactions on Higher Education, vol. 17, issue 3, June 2017.

Pending book release

Professor Chambers is using ExtendSim in a book he is writing for Springer publishing that will be printed in early 2022.

Kingston University London

Department of Management
London, UK

Course ExtendSim is used in

Adopter since 2023 BO6032 - Service Operations Management
Professor Michael Wang

Type of course

Second semester course with 25 students

Course overview

This module explores the concepts, tools, and techniques associated with Service Operations and focuses upon service evaluation, enhancement and improvement. The module is suitable for careers in retailing, financial services and consultancy.

Course goals

To introduce students to the nature and scope of Service Operations Management within both private and public sector operations.
To examine the growing literature associated with service operations and to introduce concepts, tools and techniques that will accommodate the assessment, analysis and improvement of service offerings.

Learning outcomes

On successful completion of the module, students will be able to:

Critically describe and evaluate factors that influence the strategic impact of service operations.
Recommend operational improvements that can make an effective contribution to overall business strategy at both national and international levels.
Conduct analysis of contemporary service operations issues and provide an insightful assessment of the appropriateness of service operations decision.
Apply the concepts and techniques of Service Operations Management to any service organisation.

Curriculum content

Defining and contextualising service operations management.
Evaluating service operations concepts, tools and techniques.
Comparing and contrasting alternative approaches to managing and improving service operations.
Evaluating and utilising service quality models.
Establishing the role of service networks and the creation of service value.
Appraise Service Operations within a global context.

Teaching and learning strategy

The knowledge-based materials for the module are provided by the module team in Canvas. These consist of notes and diagrams produced by the module team for each week of the module. These are supplemented by access to supplementary materials available online. Each week new material will be released into Canvas for students to read and study before attending a weekly “key-note” lecture that will be designed to explain the key concepts in the week’s reading. Key questions will then be provided to test understanding of the work; students will be divided into groups for this activity and will make informal presentations for which they will receive formative feedback.

Student projects

Managing waiting lines.

Ease with which students learn to model with ExtendSim

ExtendSim offers a graphical interface that simplifies the modeling process, making it accessible even for those who are not highly experienced in simulation.

Benefits attained through the use of ExtendSim

ExtendSim provides extensive libraries of pre-built blocks and components, which can accelerate the development of models and enhance their functionality. The software is well-suited for educational purposes, offering resources and support that help students understand complex simulation concepts and techniques.

Korea University

Maynooth University

Missouri State University

College of Business
Marketing Department
Springfield, MO USA

Course ExtendSim is used in

Adopter since 2011 MGT 565/675 • Business Process Management
Professor Dennis Jamrose

Type of course

25 undergraduate and graduate students

How ExtendSim is being used in the course

This course was developed to follow current trends in the job market. It focuses on process improvement and achieving operational and strategic business excellence through the design and improvement of an organization's process with particular attention to the resource function. Students use ExtendSim to study, to help understand, and to show improvements in processes.

Student projects

A class project is required for students that will involve a small group of students (2-3) detailing the current state of a process, identifying issues and areas of possible improvement, and selecting one or two areas to improve. ExtendSim is used to simulate and defend the students' suggested improvements.

Ease with which students learn to model with ExtendSim

Easily. But students need practice, practice, practice

Benefits attained through the use of ExtendSim

Students are able to visualize the process they observed, change it, and see rather quickly the impact of their redesign efforts.

Paper submitted based on models developed in this course

Elena Ervin, Steve Martin, Jason Smith, Olga Zhdanava, and Greg Winkeler, "Simulation of Ticket Entry and Resolution, MGT 565/675, 2011.

Additionally, ExtendSim has been used in the following course

MGT 711 • Measurement and Management of Quality in Health Care
Dr. Corinne M. Karuppan

Type of course

Graduate course with 30 students

How ExtendSim typically is used in this course

ExtendSim was used for process improvement projects and to simulate different process configurations teaching the simulation of clinical processes. Students simulated health care processes; the benefits of parallel processes were emphasized.

Projects fulfilled by students using ExtendSim

Assignments involving the analysis and improvement of clinical processes with use of Stat::Fit in conjunction with ExtendSim. Emphasis on parallel processing.

Ease with which students learned to model with ExtendSim

Good.

Benefits attained through the use of ExtendSim

Students have a better understanding of the interrelatedness of process steps. They gain an understanding of how simulation is a process modeling, analysis, and improvement tool. Students get to use and model actual data and redesign processes. Simulation is a concrete way of visualizing processes in action.

Another course ExtendSim was used in

Advanced Operations: Business Process Management
Dr. Corinne M. Karuppan

Type of course

Undergraduate with 30 students

How ExtendSim typically is used in this course

Use of ExtendSim in Classroom – Business Process Management Students spend about one third of the semester working on the analysis of current processes and their improved redesign. These classes are held in a teaching lab. The final team project is based on an actual business process. The report includes:

A case for redesign with financial justification.
Arrival and service time data with identification of probability distributions.
Simulation model of existing system.
Simulation of alternative designs with performance data.
Process design selection.

Ease with which students learned to model with ExtendSim

Not a problem.

Benefits attained through the use of ExtendSim

Easy to teach and learn. Enabled better visualization of processes.

Monash University Malaysia

National Tsing Hua University

Ohio University

Oregon State University

Otto von Guericke Universität Magdeburg

Institute for Logistics and Material Handling Systems
Faculty of Mechanical Engineering
Magdeburg, Germany

Course ExtendSim is used in

Adopter since 2010 Modeling & Simulation in Logistics Planning
Tobias Reggelin

Type of course

Masters course with 10-49 students, depending on the semester

How ExtendSim typically is used in the course

ExtendSim is used to show the 3 simulation paradigms and their use in different logistics planning tasks. Students learned to model simulation models on a mesoscopic aggregation level with the help of the discrete rate simulation paradigm of ExtendSim.

Student projects

Development of different small models for logistics planning tasks using discrete rate simulation.

Ease with which students learn to model with ExtendSim

Due to the comprehensive documentation, the students learned very fast. Development of small models for logistics planning tasks.

Benefits attained through the use of ExtendSim

Different simulation paradigms within one tool - continuous, discrete rate and discrete event simulation - is ideal for introducing logistics engineering students to simulation.

Additionally, ExtendSim is being used in the following course

Logistics Project Work
Tobias Reggelin

Type of course

Undergraduate with 70-80 students, depending on the semester

How ExtendSim typically is used in this course

Eight to ten student groups with 8-9 students in each group solved a logistics planning problem with the help of a simulation study with ExtendSim.

Student projects

Simulation of a supply chain between a producer and a market and evaluation of different order strategies.
Simulation of a distribution network for delivery to different customers.
Simulation of a material flow within a production line and evaluation of different setting-up strategies.
Simulation of a transportation network and comparison of different routing planning algorithms.
Simulation of a material transportation system between different stages in a production line.

Additionally, ExtendSim is being used in the following course

Logistics Planning Project
Tobias Reggelin or Juri Tolujew

Type of course

Masters course with 56-60 students, depending on the semester

How ExtendSim typically is used in this course

Seven student groups with 8-9 students in each group solved a logistics planning problem with the help of a simulation study with ExtendSim.

Student projects

Simulation of a supply chain between a producer and a market and evaluation of different order strategies.
Simulation of a material flow within a production line and evaluation of different setting-up strategies.
Simulation of a distribution network for delivery to different customers.
Simulation of a transportation network and comparison of different routing planning algorithms.
Simulation of a material transportation system between different stages in a production line.
Theses for students' Masters and Bachelors degrees.

The Pardee RAND Graduate School

Poznan University of Technology

Faculty of Civil and Transport Engineering
Division of Transport Systems
Poznan, Poland

Course ExtendSim is used in

Adopter since 2020 Simulation in Logistics 1 & II
Prof. Hanna Sawicka

Type of course

10 to 13 Masters level students

How ExtendSim typically is used in the course

Presentation of the main factors determining the proper design of internal logistics (in storage facilities) and external (in the distribution network of goods). The subject matter of the course also includes the acquisition of practical skills in phenomena and logistic solutions' simulation modeling.

Student projects

Production process of eletrotechnical devices.
Processes on fuel station.
Warehouse processes.
Distribution process (production, transport, warehousing).
Methodology of simulation design - design principles, main stages, practical tips.
Presentation of ExtendSim simulation tool: work area, libraries, objects, types of flows, parameters of objects, principles of model construction, presentation of an example application of a tool - case of packing finished products.
Modeling key flows of goods (human resources, handling devices / means of transport, pallet space, etc.).
Construction of a conceptual model of the transport system, selection of elements and their parameterization (means of transport, routes, speeds, etc.).
Construction of hierarchical models.
Parameterization of the model, conducting experiments, interpretation of the solution.
Contemporary trends in the field of simulation modeling, including optimization in simulation.

Ease with which students learn to model with ExtendSim

As ExtendSim is a fairly intuitive tool, learning did not cause any significant problems. Students learned the basics fast.

Benefits attained through the use of ExtendSim

At the beginning of the course students were more familiar with optimization techniques, thus learning ExtendSim was a new experience and it extended students' knowledge in the new area - simulation. Moreover, they had an opportunity to solve complex problems with non-deterministic data, which is in my opinion a benefit, as well.

The main benefit is the ability to model, simulate and analyze internal and external logistics, especially complex systems with hierarchical structure. They can model flow of information and goods, analyze deterministic and non-deterministic information, as well as carry out distribution fitting.

Radford University

Saint Bonaventure University

St. Joseph's University

Haub School of Business
Department of Decision & System Sciences
Philadelphia, PA USA

Course ExtendSim is used in

Adopter since 2011 Process Simulation & Analysis
Business Process Modeling & Analysis
Professor Virginia Miori

Type of course

Graduate course growing from 9 students in 2011, to 200 students now!

How ExtendSim typically is used in the course

ExtendSim was used as the primary software tool in the class, being taught for 6 of 8 weeks in the class. It is the primary tool for modeling business processes. The entire course is centered around the use of the Student version of ExtendSim.

Student projects

Students completed multiple homework assignments using ExtendSim and one major case in ExtendSim. The total accumulated time for the assignments was 5 weeks. The case required evaluation of data and statistical fit along with post simulation statistical hypothesis tests.

Ease with which students learn to model with ExtendSim

Many students took to simulation quite easily. Others had a more difficult time but I was able to record class sessions and allow them the opportunity to review the class again and again. Over the years, we have adapted our teaching in order to provide students with learning support. Because of this, we have seen students learn with greater ease. As the software has been enhanced, our students have also benefited.

Benefits attained through the use of ExtendSim

Using ExtendSim creates a solid understanding of process evaluation. By the end of the course, students realize how important precision in describing processes really is.

It has helped students to understand the idea of process thinking. Though many students begin without any idea of this thought, they were able to become capable at planning and mapping processes. In addition, they developed stronger programming skills, better ability to understand and model processes, better ability to see the big picture in problem solving. These greater student capabilities translate to professionals with more skills and a greater likelihood that they will use simulation in their jobs. We can teach our students about the concept of benchmarking and help them see different ways to model operations. ExtendSim lends itself so well to these tasks.

ExtendSim is a simulation language that works independently of Excel. It shows the students what is out in the world and allows them to carry this back to their own jobs. It expands their ability to contribute in the workplace and expands their ability to conceive of other approaches to problem solving.

Other comments

We continue to rely on ExtendSim and to be happy with it as a tool.

St. Mary's University

South China Agricultural University

Southern Connecticut State University

Technical University of Kosice

Technological University Dublin

Universidad Austral

Facultad de Ingenieria
Maestría en Gestión de Operaciones
Pilar, Buenos Aires, Argentina

Course ExtendSim is used in

Adopter since 2015 Simulación Discreta
Prof. Victor Herrero

Type of course

35 to 40 Postgraduate students working toward a Masters in Operations Management

How ExtendSim typically is used in the course

We have used the ExtendSim software for the dictation of Discrete Simulation for a Master's Degree in Operations Management at Austral University. This software makes it possible to complement the theoretical learning of the subject through the implementation of specific applications of problems in the Operations environment capable of being solved through modeling and simulation. Its great versatility, simplicity and coverage allow rapid learning of its use and focus on solving the problem under study, allowing a wide scope and deep level of detail. In the classes we have also used Stat::Fit software that contributes well in the activity of data collection, goodness-of-fit tests and parameterization of the models.

The objective of the course is to provide the basic knowledge necessary to handle the techniques of simulation methods by discrete, dynamic and complex events to pose and solve typical problems of queues, waiting times and other operational phenomena with the help of computer simulation tools such as ExtendSim, with the purpose of being able to design specific logistic and productive systems and to evaluate hypothetical situations with the use of the resources involved. Students must solve cases through group work. Specifically, at course completion, students should be able to:

Master complex problems using specific modeling techniques as well as simulation and computational optimization to find efficient solutions.
Make management decisions based on the use of these techniques.
Lead the activities of an organization in the areas of Operations, Supply Chain, and Projects.

Student projects

During the course the students solve 5 cases:

Case 1: Manufacture of Printed Circuits
Case 2: Manufacture of two Products with three components each
Case 3: Manufacture of 2 Products with 3 components with set-up times
Case 4: Manufacture of 3 products with tables of values of the transformation times. Random demand
Final exam: Improvement of a process in the face of certain imposed conditions

Ease with which students learn to model with ExtendSim

As it is a matter of a postgraduate course where the previous background of the students can be diverse, normally it requires at the beginning a leveling of the basic concepts (of systems, statistics, techniques of data analysis, process analysis, etc.), then venture deep into those corresponding to simulation itself. Depending on such diversity, the ease with which students learn the modeling and simulation techniques may vary, sometimes adding additional support classes is required.

Learning curve depends on each student's previous curricular training. In general, they incorporate the use of basic software in two or three meetings The greatest difficulty is in understanding the processes and in representing them. There is a tendency to use the software without sufficient prior analysis..

Benefits attained through the use of ExtendSim

Become familiar with the various applications in relation to operations simulation
How to study a system and understand its variables and parameters
Knowledge of methods to model and simulate computer operations
How to manage variability and make decisions based on computer simulated results
Take sensitivity of the behavior of the processes to different conditions and to the variation of behavioral factors

Other comments

When the size and complexity of the model grow (and then the number of blocks), the simulation speed is significantly affected. The base programming could be improved to optimize memory consumption.

Imagine That Inc. response -- We are always working to optimize the efficiency of models. Part of what gives ExtendSim its strength is that it is a compiled application...the downside of that is that sometimes it might take a bit longer to run a model. But it shouldn't be that bad. Sometimes there are certain model building techniques that might slow a model down. We would be happy to look at the model that is running slowly for you to see if there might be some slight modifications we could suggest that might increase the simulation speed. Please contact our Support Department at https://extendsim.com/support/support-help and ask them to help you figure out what might be slowing the run speed down.

Universidad de Piura

Universidad de Talca

Universidad ORT Uruguay

Universita Di Roma

Universität Duisburg-Essen

University of Alberta

Alberta School of Business
Department of Accounting, Operations, & Information Systems
Edmonton, AB Canada

Course ExtendSim is used in

Adopter since 2012 Simulation & Computer Modeling Techniques in Management - OM 422/622
Chris Neuman

Type of course

Undergraduate with 35 students

How ExtendSim typically is used in the course

The second half of the course is an introduction to discrete event simulation. Students used ExtendSim to complete a group project, one quiz, and two assignments.

Student projects

The final project required students to develop a model of a retail service facility and to examine the impacts of various service changes (operating hours, policies affecting arrival and service rates) on various performance metrics. Past projects include a group project requiring students to model a barbershop and use the model to investigate the impact of shift schedules on various system metrics.

Ease with which students learn to model with ExtendSim

Students appeared to understand how to model relatively quickly, which was impressive given it was not only their first introduction to Extendsim but to visual simulation in general.

Benefits attained through the use of ExtendSim

With Extendsim, students were able to move quickly from zero experience to building reasonably complicated models. They also learned the benefits of visualization when eliciting buy-in from decision makers. Having ExtendSim allowed students to put their theoretical learning about discrete event simulation to use in a way that encourages them to retain the information.

Students benefited from hands-on experience with commercial-level software and developed an appreciation for the skills that go into creating a model, as well as the benefits of DES as an analytical tool for complex systems. The ability to quickly construct models using blocks and connectors. This enables rapid prototyping as well as good experience. It allows me to coach students to create a basic model first, then add complexity on an incremental basis.

Other comments

We really appreciate the opportunity to use this software in the course. The feedback we have gotten from students makes clear that they find access to software like this a valuable addition to the course.

University of Applied Sciences Augsburg

University of Auckland • Business School

University of Auckland • Engineering

University of British Columbia

University of British Columbia
Norman B. Keevil Institute of Mining Engineering
Vancouver, BC Canada

Course ExtendSim is used in

Adopter since 2014 Modeling & Simulation - MINE350 & MINE553
W. Scott Dunbar

Type of course

45-60 third year students, depending on the semester

How ExtendSim typically is used in the course

ExtendSim is being used for the simulation of mining and mineral processing operations. It's also being used to illustrate methods for simulation of continuous and discrete event industrial processes for problem solving purposes. Also used to illustrate the use of probability models and to model logistics in mine operations and flows in mineral processing plants.

During the course, we solve 2 problems using continuous modeling and a third with discrete event modeling. Each requires estimating the distributions and probabilities of the outputs of models with random inputs. This can be done analytically in two of the problems. Simulation using ExtendSim is required for the other problem.

See sample Trucks Crusher Conveyor Stockpile problem used in the course...

Student projects

Shovel-truck logistics in an open pit
Spread of an epidemic
Vancouver airport
Mine concentrator plant
Flows in flotation circuits
Simulation of mine haulage shovel operations with complex fleet assignment schemes
Simulation of mine tailings runout as a result of an impoundment breach
Simulation of a mine maintenance system
Model of control of crusher circuit
Simulation of mineral processing

Ease with which students learn to model with ExtendSim

There is a short learning curve. Students are fairly proficient in building discrete event models with ExtendSim within less than 1 week. Starter tutorial given. Some also programmed blocks. The students were first-time users of ExtendSim and found it very easy to use. Within a month students understood the basics of discrete event simulation..

Benefits attained through the use of ExtendSim

Rapid understanding of how to model and effects of random variables. Increased understanding of the role of random processes in industrial systems. ExtendSim has a simple, yet intuitive interface with good examples. It gives students a better understanding of probability and uncertainty, plus boosts their confidence in modeling difficult problems. It gives them a deep understanding of modeling and models for mineral resources.

University College London

University of Colorado - Boulder

University of Houston - Clear Lake

University of Indianapolis

University of Iowa

Tippie College of Business
Business Analytics Department
Iowa City, IA USA

Course ExtendSim is used in

Adopter since 2013 Operations Management
Prof. Jeffrey Ohlmann

Type of course

Undergraduate course with 435 students<

How ExtendSim typically is used in the course

ExtendSim used as part of team project to simulate a business process.

Student projects

Yes. One course project. Students not required to build model from scratch. Only take functioning model and modify it.

Ease with which students learn to model with ExtendSim

ExtendSim very user-friendly.

Benefits attained through the use of ExtendSim

ExtendSim is a great tool to "visualize" impact of uncertainty and countermeasures to address it.

ExtendSim is also used in

Business Process Analysis - MSCI 3030
Jeffrey Ohlmann and Michael Altemeier

Type of course

Undergraduate course with 180 students

How ExtendSim typically is used in the course

Students use ExtendSim to model business processes and gauge impact of improvement ideas. It is used for homework assignments, lab exercises, and examinations.

Student projects

Students completed homework assignments and a Kaizen project using ExtendSim. Plus, the final exam is administered in the computer lab using ExtendSim.

In addition to this course, ExtendSim is being used by the Tippie Analytics Cooperative for more advanced projects. The Tippie Analytics Cooperative works with national and international brands to creatively solve some of the most challenging problems facing business today. Clients come from nearly every industry vertical and represent organizations of all sizes. In one of the more recent projects, Patient flow and optimization - University of Iowa Hospitals and Clinics, students from the Tippie Analytics Cooperative worked with massive amounts of patient encounter data to reveal bottlenecks and opportunities as patients arrive and flow through the multiple engagements that constitute an appointment. Insights provided by the students help UIHC improve the patient experience by driving operational efficiencies, optimizing staffing, and streamlining patient visits.

Ease with which students learn to model with ExtendSim

Moderate learning curve. I create video tutorials on specific ExtendSim logic. Students are directed in weekly lab sessions for in-person help. The combination of these two things allow students to learn ExtendSim well.

Benefits attained through the use of ExtendSim

Relatively user-friendly, but still flexible enough to model real problems. The point-and-click interface of ExtendSim makes it easy to get started. Students can see the effects of variability and the impact of process improvement efforts to directly observe course concepts (queueing, impact of variability, process improvement, etc.). It allows students to test and observe.

University of Mons

University of Moratuwa

University of North Carolina Wilmington

University of Rochester

Simon School of Business
Rochester, NY USA

Course ExtendSim is used in

Adopter since 2010 Service Operations - OMG 412
Phillip J. Lederer

Type of course

Second year MBA elective course taken by 20-32 students

How ExtendSim typically is used in the course

ExtendSim is a central part of the course. It is used to supporting notions of service operations models highlighting service flow, capacity planning, bottleneck analysis, just the concept of what a discrete event simulation means and how to interpret the statistics.

The software fits quite well into the topic of the course which was managing service systems. In terms of applications, the package was used by students to model various service operations. Many of the cases were based upon Harvard Business School cases (BAT, Benihana, CVS).

A car wash (an exercise from ExtendSim examples).
Police dispatching policies for patrol cars.
Planning capacity for a drive up gas station/convenience store.
Managing a technical call center and priority rules (BAT case).
Capacity analysis of a restaurant (Benihana of Tokyo).
Process improvement of a retail drug store (CVS case).
Modeling services in a bakery, barber shop, and supermarket.
Organizing a salesforce (Baria Harvard Case).

pdf button Click here for an example of a typical homework assignment.

Training materials

I was greatly aided by Robin Clark who shared his knowledge of ExtendSim with me.

I continued to make tutorial videos to help my students learn ExtendSim. I added a couple of new ones on more detailed issues.

I created a couple of new videos. The most important was on interpreting statistical results. Here I show that events in ExtendSim simulations are correlated so that the Central Limit theorem does not hold. This is important to note when viewing averages and variances output.

Ease with which students learn to model with ExtendSim

Most mastered it. With my video tutorials they pick it up rather quickly. The ones who put in the effort, find success.

Benefits attained through the use of ExtendSim

Fundamental is learning the benefits and limitiations of simulation. Using ExtendSim strengthened students analytic ability. Students learned to do simulation. The visual interface of ExtendSim is its most attractive feature.

Additional comments

I appreciate the support of the company when I get stuck trying to model activities or am confused about a feature.

University of Southern California

Marshall School of Business
Department of Data Sciences and Operations
Los Angeles, CA USA

Course ExtendSim is used in

Adopter since 2011 Discrete Event Simulation for Process Management
Prof. Amy Ward

Type of course

Graduate course with approximately 45 students

How ExtendSim typically is used in the course

This is a half-course focused entirely on Discrete-Event Simulation. The course is derived from an earlier full semester course, Simulation for Business Analytics. That course was split into half-semester courses.

Student projects

There is a project for this course, required to be done in ExtendSim.

Ease with which students learn to model with ExtendSim

Fine.

Benefits attained through the use of ExtendSim

It is reasonably intuitive to get started, once the basics of discrete-event simulation are known. The user interface is the best aspect of ExtendSim.

Additionally, ExtendSim has been used in the following course

Simulation for Business Analytics - IOM 599
Prof. Amy Ward

Type of course

Graduate course with 30 students

How ExtendSim typically is used in the course

The approach of this new course was to build simulation models to answer practical questions that are motivated by business decisions. For example, simulation was used to:

Estimate the return of an index-based stock market portfolio.
Determine if project deadlines could be met.
Decide on the staffing level and workload division in a service system.
Locate company production facilities.

Over the course of building these simulation models, both the power of simulation and some of its pitfalls and limitations were discovered. The course consisted of:

Lecture
Homework assignments
Take-home assignments
Project

Student projects

One end-of-term group project. Each group had 4 to 5 students. Various applications (inventory management, call center, etc) were represented by each group

Ease with which students learn to model with ExtendSim

Really depended on how comfortable the student felt with prob/stat and modeling.

Benefits attained through the use of ExtendSim

The class was a mix of non-technical MBA students and more technical Masters students interested in Analytics. I am not sure I could have done discrete event simulation without the easy graphic interface.

Additionally, ExtendSim has been used in the following course

Dynamic Programming and Markov Decision Processes - IOM 677
Prof. Amy Ward

Type of course

PhD course with 6 students

How ExtendSim typically is used in the course

Sequential decision making under uncertainty. ExtendSim will be used to simulate policy performance, especially in cases where the problem is not tractable analytically.

I devoted one course lecture (3 class hours), on Friday April 13, to teaching the students how to use ExtendSim. In this lecture, the students learned how to build the model in the paper by Levent Kocaga and myself, Admission Control for a Multi-Server Queue with Abandonment, in ExtendSim. This was a very nice use of ExtendSim, because we were able to show that the theoretical results and approximations developed in Kocaga and Ward matched the ExtendSim simulations.

The lecture on ExtendSim was given by Dave Krahl of Imagine That Inc. and Robin Clark from QMT Group. Dave and Robin additionally showed the students much more advanced models that could be built using ExtendSim. I asked the students for feedback on this lecture, and they said that they found the lecture very useful.

It was possible for Dave and Robin to give the lecture because they were already in the Los Angeles area for an INFORMS conference. Hence it made sense to arrange for them to give a half-day open ExtendSim session to users in the Los Angeles area, and then another half-day session oriented directly for the students in my IOM 677 course.

The course IOM 677 is intended for PhD students, and there were 6 PhD students enrolled in the course. Part of my inteneded purpose in teaching ExtendSim is that I believe it can be useful for the students as they pursue their PhD research. I have used ExtendSim many times myself in my own research, in order to validate theoretical approximations or test proposed policies, and have been very satisfied. Therefore, I wanted the students to be aware of how they could use this in their own research. Although I did not have a specific homework problem that involved ExtendSim (because simulation is a little off-topic for a Markov Decision Process Course), I feel comfortable that that goal was achieved.

Thank you very much for giving me the opportunity to be an ExtendSim Adopter. I hope to be able to continue this status in the future.

Additionally, ExtendSim has been used in the following course

Queueing and Stochastic Networks - IOM 674
Prof. Amy Ward

Type of course

PhD course wtih 9 candidates

How ExtendSim typically is used in the course

Queueing phenomena that arise in engineering and business systems will be modeled and analyzed in this course. The queueing is generated by resource contention when there is uncertainty.

Early on in the course, I devoted one lecture to the basics of using ExtendSim, and demonstrated to the students how to build a couple basic queueing models in ExtendSim. We then discussed how to estimate performance measures for those models such as the mean time in queue. This allowed me to assign homework problems to the students that required the use of ExtendSim. The problems I assigned were as follows:

HW #2, Problem 4. The students were asked to find the limiting probabilities, and the expected number of customers waiting at each station, for a particular Jackson network configuration. This can be done through exact analytic formula (and that exact analysis was taught in class). The students were then asked to simulate the network using ExtendSim, and to see that their simulation answers matched their analytic answers.
HW #4, Problem 2. The students were asked to develop a heavy-traffic approximation for the mean number of customers in the system for a GI/GI/1 queue, under two different distributional assumptions for the service times that were not exponential. Note that there are no exact analytic formulae for steadystate performance measures for this system, and so the students had to rely on approximation formulae (which we developed in class). The students were then asked to simulate the GI/GI/1 queue using Extend in order to understand the situations in which their approximation formulae performed well.
HW #4, Problem 3. The students were asked to develop a heavy traffic approximation for the mean number of customers at each station in a network that consisted of two GI/GI/1 queues in tandem. Again, there are no exact analytic formulae available and so the students had to rely on approximation formulae. The students were then asked to simulate the network using Extend in order to see how their approximation formulae performed.

Benefits attained through the use of ExtendSim

I view the use of ExtendSim as very important for the course. In order for the students to truly understand how to develop and use analytic approximation formulae for queueing networks that cannot be analyzed exactly, it is extremely helpful for them to also simulate the network. The simulation allows them to understand how to apply their approximation formulae to estimate performance measures of interest, and to know when there approximation formulae will work well vs when their approximation formulae may not work well. Please also see my Homeworks #2 and #4 for the exact questions referenced above.

I am very appreciative for having the use of ExtendSim for this course. Thank you.

University of Split

Faculty of Economics, Business, & Tourism
Department for Information Technology in Management
Split, Croatia

Course ExtendSim is used in

Adopter since 2014 Business Process Simulation
Mario Jadric

Type of course

Masters course with 25-35 students

How ExtendSim typically is used in the course

ExtendSim is used to demonstrate as well as practice business process simulation modelling by the students. Students were presented ExtendSim tool, which they used to deliver business process models for process optimization. ExtendSim was used for:

Presentation of the course and planned activities.
Modeling of complex systems.
Concept of simulation.
Approaches to simulation modeling.
Types of computer simulation.
The selection of simulation models.
Business processes and simulation modeling.
Projects of simulation modeling.
Choosing a process for simulation modeling.
Theory of waiting queues.
Distribution of random variable in simulation modeling.
Discrete event simulation.
Construction of discrete simulation model.
Planning simulation experiments.
Analysis of simulation results.
Concepts of business process management and simulation modeling.
The concepts of system dynamics.
Analysis of casual loops.

Student projects

Discrete event simulation modeling using ExtendSim - exercise series.
Modeling of complex systems.
Waiting queues.
Distribution of random variables in simlation modeling
Construction of discrete simulation models.
Analysis of simulation results.
Final course project - case study of real life project realization, modeling as-is and to-be real life processes
Business process simulation and optimization, plus bottleneck detection and optimization.

Ease with which students learn to model with ExtendSim

Students had no issues with learning simulation considering the tutorials & videos are in-depth. ExtendSim is an intuitive yet powerful modelling tool. Also, help and manuals available for the tool are very helpful. Besides, example models are great!

Benefits attained through the use of ExtendSim

Simulation modelling understanding & awareness for beginners and experts. Hands-on practical approach. Acquiring basic modelling knowledge as well as Discrete Event Simulation realization for our students. In-depth understanding of simulation and what-if analysis benefits for different industries. Students learned how to design processes, objects, attributes and methodology used in ExtendSim. Showing benefits of designing to-be processes of current business situation, designing as-is situation, performing analysis and designing to-be situation using advanced business process modelling. Performing what-if analysis.

Thumbs up for the great tool, demo examples/use cases as well as help files and exercises!

University of Tennessee - Knoxville

Haslam College of Business
Department of Business Analytics & Statistics
Knoxville, TN USA

Course ExtendSim is used in

Adopter since 2011 Simulation Modeling - BZAN 546
Bogdan Bichescu

Type of course

Graduate course

How ExtendSim typically is used in the course

BZAN 546 is a graduate class taught in the College of Business Administration at the University of Tennessee and focuses on modeling business processes using discrete-event simulation software. As part of the class, students built simulation models relating to the management of inventories, waiting lines, and various resources, in contexts such as healthcare, retail banking, and manufacturing. Moreover, students used ExtendSim on four homework assignments, end-of-term class projects, and the course final which dealt with capacity planning and optimization for a hospital’s outpatient clinic. Some of the course projects include:

Bus scheduling and routing for a large, on-campus, youth creativity competition.
Capacity planning and optimization for a hospital’s outpatient clinic.

In summary, the use of ExtendSim in the class:

exposed students to an industry-leading discrete-event simulation environment.
demonstrated the application of simulation concepts in an integrated, GUI-driven application environment (including elements of problem abstraction and modeling, sensitivity analysis and experimentation, heuristic optimization, animation and visualization, etc.).
helped students develop an intuitive, visual understanding of system dynamics (in contrast to, for example, formal treatments of resource management in the form of traditional queueing models).
afforded students the ability to easily and quickly perform sensitivity analyses for system improvement.
improved students’ problem solving techniques and their ability to grasp the importance of robustness and flexibility as system design principles.

Additionally, ExtendSim has been used in the following course

Decision Analytics & Simulation - MS 532
Melissa Bowers & Bogdan Bichescu

How ExtendSim typically is used in the course

MS 532 is a graduate class taught in the College of Business Administration at the University of Tennessee and the better part of the class curriculum focuses on modeling business processes using discrete-event simulation software. As part of the class, students built simulation models relating to the management of inventories, waiting lines, and various resources, in contexts such as healthcare, retail banking, and manufacturing. Moreover, students used ExtendSim on two homework assignments and one end-of-term class project, which dealt with capacity planning and optimization for a medical device manufacturer. In summary, the use of ExtendSim in the class:

exposed students to an industry-leading discrete-event simulation environment.
demonstrated the application of simulation concepts in an integrated, GUI-driven application environment (including elements of problem abstraction and modeling, sensitivity analysis and experimentation, heuristic optimization, animation and visualization, etc.).
helped students develop an intuitive, visual understanding of system dynamics (in contrast to, for example, formal treatments of resource management in the form of traditional queueing models).
afforded students the ability to easily and quickly perform sensitivity analyses for system improvement.
improved students’ problem solving techniques and their ability to grasp the importance of robustness and flexibility as system design principles.

University of Washington

University of Western Australia

University of Wisconsin - Madison

Wisconsin School of Business
Department of Operations & Information Management
Madison, WI USA

Course ExtendSim is used in

Adopter since 2013 Service Operations Management
Professor Robert Batt

Type of course

Up to 71 undergrad & 36 MBA/Graduate level students

How ExtendSim typically is used in the course

ExtendSim is used to teach basic queuing principles such as how wait time explodes as utilization approaches 1, non-linear response to server count, non-linear relationship of utilization and wait time and the benefit of pooled vs. separated servers. The students perform both in class exercises as well larger homework case analysis. We build simple queues, multi-channel queues, tandem queues, etc. We explore queue performance under different conditions. We looked at topics such as drivers of queue time, the impact of priorities, and the impact of batching.

Wisconsin School of Business In 2024, we added a new Emergency Department board game to my class this year. We spent two days playing and debriefing the game. I then created an ExtendSim replication of the game which we used to see how simulation could be used to discover optimal staffing decisions. It worked really well!

Student projects

We start with building simple M/M/c queues, and then add complexity such as priorities, pooled vs. separated queues, and then eventually do the HBS Delwarca Call Center case.

Mini-cases of a car wash and a barber shop learning impact of variability, utilization, pooling queues, priorities, etc.
Spent two days analyzing and improving a call center using the "Delwarca Software Remote Support Unit" case from Harvard Business School (HBS) Publishing.
In the past, used the BAT and Benihana cases from HBS Publishing.
Plus a few instructor-created exercises
A new HBS case was added in 2021: "Breakfast at the Paramount" by Ryan Buell. Prof. Buell's note don't include simulation, so I had to design the questions and assignments, but it worked really well to look at bottlenecks and customer priorities. I highly recommend it.

Ease with which students learn to model with ExtendSim

It's always a mixed bag. Some take to it quite easily, and some really struggle. But that's true of all the quantitative topics I do. But overall, most students are able to build and manipulate queues fairly quickly. The basics are easy. Some more sophisticated things, such as batching, are more difficult. Some students get it instantly. Some struggle constantly. I don't think the variance is due to the software.

Benefits attained through the use of ExtendSim

Students get to build an manipulate queues themselves. We get to do much more complex designs than if we were limited to simple queueing formulas. We can go MUCH farther than with simple M/M/c equations. Students can design and test very complex queues quite quickly testing lots of ideas. I can teach the students much more complicated concepts (priorities, batching, etc) than I could if I stuck to Little's Law and simple M/M/c type queue equations. Students get to build their own queues and see the various performance metrics change as the students change the parameters and queue flow/design. The students can be set loose to experiment and try different ideas to improve service systems.

Wake Forest University

Wroclaw University of Science & Technology

Faculty of Management
Department of Operations Research & Business Intelligence
Wroclaw, Poland

Courses ExtendSim is used in

Adopter since 2010 Simulation Modeling
Economic Modeling and Forecasting (IEZ1532)
Jacek Zabawa

Type of course

Masters course with approximately 50 students, sometimes up to 100 students

ExtendSim use in 2022

Professor Zabawa presented two 90-minute lectures in IEZ1532 on the use of ExtendSim, teaching students how to read and analyze models, plus build their own models. As students have experience with other simulation tools, they are able to easily build ExtendSim models.

In the first lecture, issues related to continuous simulation based on the book by Prof. Bozena Mielczarek were discussed. Using an example of a simple financial model, he also presented a technique for storing the results from multiple runs in tables to demonstrate Monte Carlo simulation using the following model assumptions:

- sales volume (uniform distribution)
- unit price (uniform distribution)
- unit cost (uniform distribution)
- fixed costs (Constant block)

Results of the model showed:

- Financial profits: saved in arrays across the runs
- Financial profit: maximum, mean, variance, standard deviation, number of observations in a single run

wroclaw22 2 In the second lecture, he discussed discrete event simulation in Extendsim. He focused his presentaiton on the possibility of saving the results from multiple runs (Write blocks) and controlling the parameters of the Activity block describing the following approaches:

- using Select Value In with the Constant block
- using Select Value In accompanied by Equation and Simulation Variable blocks
- using the Equation block accompanied by Simulation Variable, Constant and Random blocks

Also discussed was the use of ModL language elements in the Equation block (for example: MOD and Switch instructions). Plus, the application of sensitivity analysis using Sensitize Parameter and Read from column x of file.

Click here to see a sample of the model used in 2022 courses and quiz questions presented to students.

ExtendSim use in 2021

Wroclaw 2021 During the classes in which I used ExtendSim (compared to the previous year) I added a model in which I presented a way to implement the assumptions about the 2 automated teller machine operating system. We assumed there were two customer streams. In the first stream of people (client 1) the client selects this ATM (atm1 or atm2) to which there is a shorter queue – I presented the use of blocks Max&Min, Select Item Out (control via connector Select). In the second stream of people (client 2) can only use atm2. In addition, I showed how to model the failure of the ATM (Shutdown block). I also presented setting numeric attribute values (rodzaj_klienta; Set and Random Number blocks) and used attribute values to control random time distribution parameters (in Activity block).

After each meeting with students, I checked the acquired knowledge by collecting answers to sample questions, such as:

Which block is used to model service stations?
How can you model a case in which the distribution of servie time at the server depends on te value of the specified attribute but the distribution type is always the same?
What information can we get from the History block?

How ExtendSim typically is used in the course

This software was used as a primary modeling tool for continuous and discrete event-simulation software. Students build a simple model on their own and work in teams of two to build a model based on assumptions.

Student projects

It depends on the number of the course hours. During the course of 10 hours, students develop a model based on the assumptions in the form of text using a graphical representation of the model (in the Extendsim notation) and complement the model with the ability to record the results of several runs.

During the course of 15 hours, students develop two models for an evaluation. First, on the basis of the assumptions in the form of text, and using the graphical representation of the model (it is kind of a test designed to realize the student's skill level). Then prepare a complete model based on assumptions and graphical representation other than Extendsim). It is a task carried out in groups of two students.

Ease with which students learn to model with ExtendSim

Very fine, easy GUI, input and output connectors, easy handling of attributes.

Benefits attained through the use of ExtendSim

ExtendSim is powerful software in which we can build very complex models, develop our own library of blocks, and it has good integration with external data. We also appreciate its:

Easy handling of attributes and their processing.
High correspondence between the model and the structure of the process.
Hierarchical blocks.

2020 - aspects of building models of discrete event systems presented in the course

MODEL 1
The simplest model consistent with the discrete (queuing) approach. The possibility of displaying charts was also presented.

MODEL 2
The simplest model equipped with the ability to save the results of many experiments and simple statistical calculations.

MODEL 3
Automatic sensitivity analysis and the possibility of cloning interior windows.

MODEL 4
Controlling the length of service time using an external RANDOM NUMBER block and connector D at the service station (ACTIVITY).

MODEL 5
Presentation of using the SELECT ITEM OUT switch to direct objects that do not fit in a queue to another place. Note the impact of this solution on the simulation results.

MODEL 6
Model extension with a preparatory service module. It was shown how to combine two streams, how to declare attributes and their values, how to check the values of attributes in a selected place of the model, how to draw a path for objects.

MODEL 7
Presentation of static attribute attribution (in the path all objects will have the same attribute value). You can also see in the HISTORY block the simultaneous possession of two different attributes by a given object (attributes: color and I_STep = yes / no).

MODEL 11
Wroclaw 2020 model The completion (batching) technique was presented. In batching, we combine objects (it can come from different sources) and treat the rest of the model as a whole. However, objects can be separated at the selected place in the model. An example of using the batching technique is modeling employee participation in material processing.

Sample of ExtendSim usage in past courses

Wroclaw sample model 1 LESSON 1
Create an input stream in which the exponential time between arrivals is, on the average, 10 minutes. Set up a buffer that can accommodate a queue of 100 objects for a set of service stations. Each station can process 3 objects at the same time. Service time is a triangular distribution with a minimum of 8, maximum of 15, and average of 12 minutes. Check the length of the queue when the model is run 4 times for 6 hours each.

wroclaw18 2 LESSON 2
Using Global Arrays and Named Connections, take note of the number of objects output at the end of each of the runs, the final waiting time in the queue, and its average value.

LESSON 3
There are four types of items (A, B, C, & D) requiring prep work prior to servicing. Types A, B, & C are generated on an average of one every 10 minutes on an exponential distribution. The likelihood of each type being generated is:

30%

40%

30%

Type D is generated one every 10 minutes. Tip: Store information about each item’s type as a 'Type' attribute.

Prep work servicing for types A and C is performed on 3 dedicated servers. Prep time is a triangular distribution of between 5 and 10 minutes with 8 being the highest probability. Priority prepping is given to type A items.

Prep work servicing for types B and D is performed on 2 dedicated servers. Prep time for type B is a triangular distribution of between 5 and 10 minutes with 8 being the highest probability. Prep time for type D is a triangular distribution of between 5 and 14 minutes with 8 being the highest probability.

Determine how many items are generated by the system and how many of each type. Wroclaw

Tip: Use Information (Item), Select Item Out (Item), and Select Item In (Item) blocks in addition to the Data Source Create and Write blocks.

LESSON 4: Batching
There are four employees at the workshop. Unless there is an employee available, service at any station cannot begin or end. At the end of each service activity, employees rest up and begin to get acquainted with the next activity at their station (this process takes 10 minutes). As the most valuable resource, the employee is only called into service with the item they will be working on is available for service.

Wroclaw - lesson 4 Are four employees enough to maximize productivity? Or should the company hire more? Or would a reduction in staff be more beneficial?

Additionally, ExtendSim has been used in the following course

Business Modeling and Forecasting
Jacek Zabawa

How ExtendSim typically is used in the course

I introduced the experiment (a change in the way the classes). At the first session I showed (and students to repeat) how to build a very simple queuing model equipped with the ability to record the results of multiple runs (blocks a write). At the second class I presented high degree of complexity model (service attributes, batching, recurrences of objects). At the third class I presented sets of simple models which implement (separately) service attributes and batching. These models were gradually expanded. Students build simple models and then expanded them. At the next class (in January) will be a single test, performed independently, consisting of self-construction of a simple model based on the assumptions of text. I'll put the suggestions (hints) on the types of blocks that can be used. Before the test I'll do recap material. At the last class students who do not pass the test will be able to fix it. For those who have passed positively I would like to present other advanced capabilities Extendsim, perhaps it will be genetic optimization or sensitivity analysis.

Additionally, ExtendSim has been used in the following course

Financial Analysis of Company Appliations with Models
Jacek Zabawa

How ExtendSim typically is used in the course

It consisted of a lectures and seminars. During lectures I presented, among others, new edition of complete application in Extendsim allowing construction of financial statements (balance, incomes etc.). As in the previous year we also discussed its modules, such as the calculation of income and expenses for this activity-based costing. We tried to use the models for business game support.

In the seminar portion of the course, students created financial simulation models of selected economic games. Here, the tool was arbitrary, but some groups chose to implement their model in ExtendSim - due to the readability of models created in ExtendSim was particularly didactic.

Preparing for this course inspired Prof. Zabawa to prepare another paper in to formulate a methodology of modeling assumptions in financial simulations. This methodology is based on the multiplication of objects: one object for "things" and second object for "money". "Integrating discrete event simulation and financial reporting" was accepted for publication and it was presented during the 33rd International Conference Information Systems and Technology Architecture.

I used the previously improved structure of the lecture with several recordings (movies snap) on how to create models. I have presented different models for the problem of "improving equipment" and how to study the impact of such change on the financial statements. As in the previous year, we dealt with economic events "prepayment" and "delay in payment of liabilities and receivables". I also presented the design and calculation techniques of balance statement using yogurt production model that was included in the package ExtendSim.

Conference papers submitted based on Prof. Zabawa's projects

Zabawa, J. (2024). How to Facilitate Hybrid Model Development by Rebuilding the Demographic Simulation Model. In: Franco, L., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2024. ICCS 2024. Lecture Notes in Computer Science, vol 14834. Springer, Cham. https://doi.org/10.1007/978-3-031-63759-9_21.

Abstract: Demographic information can be used to analyze processes occurring in a wide range of human social activity: in the area of management, healthcare, social security systems. One of the leading methods of demographic modeling is continuous simulation based on the system dynamics approach. Reducing computation time for fast-running continuous model implementations enables efficient development of hybrid models. In the hybrid simulation model, the discrete-event simulation approach was used as one of the components. Technical and conceptual solutions to the observed problems were presented, experiments based on demographic data from the Wrocław region, Poland were performed and it was indicated that an effective hybrid simulation will allow to include additional cause-and-effect relationships in the models.

Jacek Zabawa, Bozena Mielczarek (2021). An attempt to replace system dynamics with discrete rate modeling in demographic simulations. W: Computational Science - ICCS 2021 : 21st International Conference Krakow, Poland, June 16-18, 2021 : proceedings. Pt. 4 / eds. Maciej Paszynski [i in.]. Cham : Springer, cop. 2021. s. 269-283. (Lecture Notes in Computer Science, ISSN 0302-9743; vol. 12745) DOI 10.1007/978-3-030-77970-2_21.

Abstract: The usefulness of simulation in demographic research has been repeatedly confirmed in the literature. The most common simulation ap-proach to model population trends is system dynamic (SD). Difficulties in a reliable mapping of population changes with SD approach have been howev-er reported by some authors. Another simulation approach, i.e. discrete rate modeling (DRM), had not yet been used in population dynamics modelling, despite examples of this approach being used in the modelling of processes with similar internal dynamics. The purpose of our research is to verify if DRM can compete with the SD approach in terms of accuracy in simulating population changes and the complexity of the model. The theoretical part of the work describes the principles of the DRM approach and provides an overview of the applications of the DRM approach versus other simulation methods. The experimental part permits the conclusion that DRM approach does not match the SD in terms of comprehensive accuracy in mapping the behavior of cohorts of the complex populations. We have been however able to identify criteria for population segmentation that may lead to better re-sults of DRM simulation against SD.

Zabawa J. (2020) "Simulation Approach in Queue Management at Supermarkets in the COVID-19 Era". Presented at the 35th IBIMA Conference, Seville, Spain. 1-2 April 2020.

Abstract: How to prevent and control of epidemic spreading of diseases (for example COVID-19) in supermarkets? To answer this question, a simulation approach was proposed. A number of simulation experiments were performed. The likelihood of close contact with carrier in different ticket queue configurations was compared. Based on the results, several tips and suggestions were developed for customers and market managers.

Mielczarek B., Zabawa J. (2018) "Modelling Population Dynamics Using a Hybrid Simulation Approach: Application to Healthcare". In: Obaidat M., Ören T., Merkuryev Y. (eds) Simulation and Modeling Methodologies, Technologies and Applications. SIMULTECH 2016. Advances in Intelligent Systems and Computing, vol 676. Springer, Cham, cop. 2018. s. 241-260
ISBN 978-3-319-69831-1

Abstract: The goal of the study is presenting a population submodel developed using the system dynamics (SD) approach and discussing solutions for the integration of the SD methodology with discrete time control in formulating long-term projections for population evolution and its influence on healthcare demand. This study relies on historical demographic data and officially formulated scenarios for the most likely population projections for the Wrocław Region. The historical parameters are applied from 2002 to 2014, and projected trends are adopted for 2015 to 2035. The preliminary findings confirm the validity of using the hybrid simulation approach for a more advanced exploration of demography-dependent health policy issues.

Bożena Mielczarek, Jacek Zabawa. "Simulation model for studying impact of demographic, temporal, and geographic factors on hospital demand". Winter Simulation Conference, 2017

Abstract: This paper reports on the results of a study that aims to develop the hybrid simulation model for estimating the level and structure of the demand for healthcare services. Research is performed for the Wrocław Region (WR), the main administrative area of Lower Silesia, the fourth largest province in Poland. An aging chain approach is implemented in the system dynamic model to forecast the number of individuals belonging to the respective age-gender cohorts over the next 20 years. The discrete event simulation model predicts the expected volume of emergency arrivals at the WR hospitals and explores the relations between demand and demographical, temporal and geographical aspects. The projections of long-term population evolutions are performed on the aggregated data and analysis is focused on pre-specified age-gender cohorts. The demographic groups are described using parameters such as birth and death rates, life expectancy, and migration descriptors. The historical data on hospital admissions are drawn from National Health Fund regional branch registry. Findings have important implications for the future decisions on distributions of the resources on the regional level.

Bozena Mielczarek, Jacek Zabawa. "Modelling Population Growth, Shrinkage and Aging using a Hybrid Simulation Approach: Application to Healthcare". SIMULTECH 2016: 75-83

Abstract: This paper describes a hybrid simulation model that integrates the System Dynamic approach with discrete time control to formulate the projections of population evolution. The study relies on historical demographic data and the officially formulated scenarios for the most likely population projections developed for the region. The results of the simulation experiments provide valuable insights into dynamics of regional demographic trends and offer a well-defined starting point for future research in the health policy field. The intensity and structure of the demand for healthcare services depend heavily on age-gender profiles that change due to ongoing extensions of the average expected length of life, the aging of population, the continuing trend of declining number of births and the steadily growing number of deaths. The preliminary findings show promise in using the hybrid simulation approach for more advanced exploration of demography dependent health policy issues.

Bozena Mielczarek, Jacek Zabawa. "Modeling Healthcare Demand Using a Hybrid Simulation Approach". Winter Simulation Conference 2016.

Abstract: This paper describes a hybrid simulation model that uses a system dynamics and discrete event simulation to study the influence of long-term population changes on the demand for healthcare services. A dynamic simulation model implements an aging chain approach to forecast the number of individuals who belong to their respective age-sex cohorts. The demographic parameters that were calculated from a Central Statistical Office Local Data Base were applied to the Wroc?aw Region population from 2002 to 2014, and the basic scenario for the projected trends was adopted for a time horizon from 2015 to 2035. The historical data on hospital admissions were obtained from the Regional Health Fund. A discrete event model generates batches of patients with cardiac diseases and modifies the demand according to the demographic changes that were forecasted by a population model. The results offer a well-defined starting point for future research in the health policy field.

Jacek Zabawa, Edward Radosinski. "Comparison of discrete rate modeling and discrete event simulation. Methodological and performance aspects." Published in Springer's book series: Advances in Intelligent Systems and Computing

Jacek Zabawa. "Discrete rate modeling approach for supply chain modeling" Presented at the Total Logistic Management Conference 2015 and published in the Czasopismo Logistyka journal in 2016.

Abstract: The paper discusses the basics of modeling inventory management system in a spreadsheet. Then the application of a discrete rate in the supply chain simulation was proposed. Assumptions of test models which utilize DRM was presented. The structure of models and specification requirements was proposed. Selected simulation experiments were performed. The results were analyzed in a specially designed spreadsheet tool. Conclusions and prospects for further research was presented.

Bozena Mielczarek, Jacek Zabawa, and Marek Lubicz. "A System Dynamics Model to Study the Impact of an Age Pyramid on Emergency Demand." In Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, 879-888, 2014, Vienna, Austria

Abstract: This paper describes a system dynamics simulation model to analyse the relationship between age pyramid and the volume of patients arriving to hospital emergency departments located in a sub-region of Lower Silesia of Poland. The study relies on demographic and historical demand data, and the cohort forecasts for the population of the region. The results of the simulation experiments provide insights into the relationship between sub-regional demographic trends and population needs in relation to hospital emergency arrivals. The preliminary findings indicate that the forecasted long-term demographic changes in the population may increase the number of emergency patients in the area.

Zurich University of Applied Sciences (ZHAW)

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