Papers

ExtendSim powered tools, modeling methodologies, and techniques are discussed here. To learn about how ExtendSim is being used in specific industries, please see Industrial Solutions.

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Theory of ConstraintsReducing the resource workload, setting task priorities, and providing expert assistance when needed can dramatically change the culture of large multi-project environments for the better. Play VideoIn the presentation "Improving Performance in a Multi-Project Environment: A Systematic Approach to Resource Loading", Robin Clark uses ExtendSim to demonstrate a Theory of Constraints200% to 600% improvement in project value. MITREMITRE’s Modeling Environment for Service Oriented Architecture Analysis (MESA) addresses performance engineering challenges, such as how to plan and construct a Service-Oriented Architecture (SOA). This ExtendSim based tool allows users to integrate SOA infrastructure models with other models, Performance Engineeringsuch as business/user process models.
Value-Stream MappingVSMSx, a value stream map simulator using ExtendSim, is a generic multiple-use tool for building simulation models of value stream maps. It is supported by a database for inputs and outputs that can be manipulated remotely. The advanced processing power achieved by incorporating simulation with paper-and-pencil value stream maps enables a number of key performance measures to be extracted, including utilization of workers, utilization of processes, overall equipment efficiency, late deliveries, throughput, inventory fluctuation levels and time spent as work-in-process. Thus, managers and decision makers can see the impact of a lean transformation prior to implementation by predicting how a system would behave. TMC.netIt literally puts a value stream map in motion. Davies ConsultingMilitary and civilian communities face the challenge of preparing for and responding to change through policy development, budgeting, planning and infrastructure investment, as well as through periodic event management/recovery activities. These two communities have evolved characteristically distinct analytical approaches to assess and manage risks - neither approach fully satisfying the new challenges of resilience, which demand robust but flexible systems and underlying collaboration across the community. ResilienceConsidering modeling approaches currently used within these communities to identify strengths, potential synergies and application implications, research suggests future development of hybrid methodologies which facilitate civil-military collaboration toward the new objective of community resilience.

 

General Articles on Simulation

Winter Simulation Conference Roadmap to Success: Your First Simulation Model
Robin Clark, The QMT Group & Dave Krahl, Imagine That Inc.
Winter Simulation Conference 2011


Success in your first simulation model is crucial for the overall prospects of a new simulation program. Here we will outline the building of your first simulation model with emphasis on the overall process and what it takes to be a successful model builder.PDF
Software Engineering Institute Moving Up the CMMI Capability and Maturity Levels Using Simulation
David M. Raffo, PhD and Wayne Wakeland, PhD, Carnegie Mellon University
Software Engineering Institute, January 2008


This report shows how process simulation modeling (PSIM) can help companies improve processes and achieve higher levels of process maturity and capability as called for by the Capability Maturity Model® Integration (CMMI®)1 [SEI 2006]. CMMI was developed by a team consisting of members from industry, government, and the Software Engineering Institute (SEI).This report is aimed at practitioners, especially software development project managers, and researchers studying software development processes. The report describes a variety of PSIM applications and discusses how PSIM has helped organizations to improve their implementations of CMMI areas toward higher levels of process capability, maturity and performance.PDF
Analytics Magazine The ABCs of Simulation Practice
Jerry Banks and Randall R. Gibson

Analytics Magazine, Spring 2009


Letter by letter, the authors summarize 26 of what they consider to be important components for applying knowledge and judgment to simulation problems. They do not claim that these are “the” 26 components. Other simulation analysts could have another set, or they could have multiple components for one letter of the alphabet.PDF

Case StudiesPapers

Naval Postgraduate School A model-based systems engineering methodology for employing architecture in system analysis: developing simulation models using systems modeling language products to link architecture and analysis
Paul T. Beery, B.A., Rutgers University, 2009, M.S., Naval Postgraduate School, 2011
Naval Postgraduate School, June 2016


This dissertation contributes to model-based systems engineering (MBSE) by formally defining an MBSE methodology for employing architecture in system analysis (MEASA) that presents a comprehensive framework detailing the relationship between system architecture products and external models and simulations used to analyze system performance and feasibility. Specifically, the research combines the use of Systems Modeling Language (SysML) products and operational simulation models to support assessment of system requirements for systems engineering. The MBSE MEASA transforms operational needs into preferred system configurations through the analysis of detailed simulation models. The research does this by using designed experiments to generate architecture tradespace visualizations that highlight the impact that system design parameters, system-environment interactions, system operational implementation, and system component interactions have on system performance. The research demonstrates a procedure for iterations of the methodology when analysis suggests potentially impactful design, operational, or environmental variables (as well as potential interactions between those variables). The research develops and analyzes notional architecture products and simulation models of United States Navy mine warfare systems to demonstrate an application of the MBSE MEASA.Next page
Winter Simulation Conference ExtendSim Technology: Scenario Management
Dave Krahl
Winter Simulation Conference 2011


Simulation models are typically built to obtain an understanding of the system dynamics and compare alternatives. ExtendSim’s Scenario Manager provides an easy interface to evaluate different model configurations and explore the effects of model parameters. Scenario management provides for a systematic, controlled approach to the investigation of a system or process. Among other things, it can be used for problem solving ("what are the main factors contributing to the problem"), parameter design ("how well does the system/process perform given specified factors"), and robustness studies (what is the best configuration of factor values to maximize/minimize variations in response".) Thus it has a very broad application across all disciplines.PDF
Innovative Decisions, Inc. Integrating Equation-Based Models and Bayesian Networks
Dave Brown, Innovative Decisions, Inc.

Equation-based models and Bayesian networks are not mutually exclusive methods of modeling and simulation. Based on the development of the Netica library for Extend, the two methods can be used simultaneously within the same environment.

In this paper, several models were constructed to demonstrate the utility of this approach with integrated models that contain both equation-based elements and Bayesian networks working together to create a single simulation.

The research also demonstrated the use of complex simulations to train influence diagrams. The examples discussed in this paper demonstrate the feasibility and utility of integrating Bayesian networks and equation- based models. The exploitation of this capability should lead to multiple follow-on research projects. This approach may prove fruitful in a number of scientific disciplines that make use of models and simulations.
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Portland State University Using Design of Experiments, Sensitivity Analysis, and Hybrid Simulation to Evaluate Changes to a Software Development Process: A Case Study
Wayne Wakeland, Systems Science Ph.D. Program & David Raffo, School of Business Administration, Portland State University; and Robert H. Martin, Software Management Consulting
ProSim Conference 2003


This paper applies DOE and broad range sensitivity analysis to a Hybrid System Dynamics and discrete event simulation model of a software development process. DOE is used to analyze the interaction effects, such as the degree to which the impact of the process change depends on worker motivation, schedule pressure and other project environmental variables. The sensitivity of the model to parameter changes over a broad range of plausible values is used to analyze the nonlinear aspects of the model. The end result is a deeper insight into the conditions under which the process change will succeed and improved recommendations for process change design and implementation.PDF
 
  Using Software Process Simulation to Assess the Impact of IV&V Activities
David M. Raffo, Umanath Nayak, Siri-on Setamanit, Patrick Sullivan, Wayne Wakeland
College of Engineering and Computer Science, School of Business Administration, Systems Science Ph.D. Program
Portland State University, Portland, Oregon, USA


Organizations like NASA and the US Department of Defense make heavy use of Independent Verification and Validation (IV&V) techniques to improve the quality of systems and to reduce the risks associated with the deployment of those systems. Given proper data, software process simulation models (SPSMs) can be used to quantify the costs and benefits associated with both V&V and IV&V practices on software projects, thereby enabling management to more effectively allocate scarce resources for V&V and IV&V activities.

This paper presents a large-scale software development process model that is being developed and used at NASA to apply IV&V at various points in the development process. Preliminary illustrative results show the types of analyses that can be done and point out some of the research issues associated with this work that contributes to mission assurance and success by making recommendations as to how IV&V technologies should be deployed across various projects. These recommendations support planning and management of IV&V and enable IV&V technologies to be applied to software projects more quickly, in order to achieve greater benefits at lower cost.
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OpStat Lean Simulation Models
Jim Curry, OpStat Group, Inc.
Presented at the Automated Lean & Quality Resource Center at EASTEC, May 25, 2006


Lean Simulation Models introduces the use of simulation models as essential tools for lean programs to test alternative solutions before implementing them. Mr. Curry highlights benefits of using Extend and includes screenshots of numerous sample models.PDF
Software Engineering Institute Moving Up the CMMI Capability and Maturity Levels Using Simulation
David M. Raffo, PhD and Wayne Wakeland, PhD, Carnegie Mellon University
Software Engineering Institute, January 2008


This report shows how process simulation modeling (PSIM) can help companies improve processes and achieve higher levels of process maturity and capability as called for by the Capability Maturity Model® Integration (CMMI®)1 [SEI 2006]. CMMI was developed by a team consisting of members from industry, government, and the Software Engineering Institute (SEI).This report is aimed at practitioners, especially software development project managers, and researchers studying software development processes. The report describes a variety of PSIM applications and discusses how PSIM has helped organizations to improve their implementations of CMMI areas toward higher levels of process capability, maturity and performance.PDF
Queueing Systems A Diffusion Approximation for a GI/GI/1 Queue with Balking or Reneging

Amy R. Ward (School of Industrial and Systems Engineering, Georgia Institute of Technology) and Peter W. Glynn( Department of Management Science & Engineering, Stanford University)
Queueing Systems: Theory and Applications archive, August 2005


Consider a single-server queue with a renewal arrival process and generally distributed processing times in which each customer independently reneges if service has not begun within a generally distributed amount of time. A Diffusion Approximation for a GI/GI/1 Queue with Balking or Reneging establishes that both the workload and queue-length processes in this system can be approximated by a regulated Ornstein-Uhlenbeck (ROU) process when the arrival rate is close to the processing rate and reneging times are large. This paper further shows that a ROU process also approximates the queue-length process, under the same parameter assumptions, in a balking model. This balking model assumes the queue-length is observable to arriving customers, and that each customer balks if his or her conditional expected waiting time is too large.Go to page...

VideosVideos

Play VideoImproving Performance in a Multi-Project Environment: A Systematic Approach to Resource Loading

Reducing the resource workload, setting task priorities, and providing expert assistance when needed can dramatically change the culture of large multi-project environments for the better. In the presentation, Robin Clark uses ExtendSim to demonstrate a 200% to 600% improvement in project value.

https://vimeopro.com/tocico/2016-international-conference-speaker-5-minute-videos/video/170291842