Simulation Spotlight

Estimating the capacity of a region to serve pandemic patients in need of hospital services is crucial to regional preparedness for pandemic surge conditions. This paper explores the use of techniques of stochastic discrete event simulation for estimating the maximum number of pandemic patients with intensive care and/or in-patient, isolation requirements that can be served by a consortium of hospitals in a region before requesting external resources. Estimates from the model provide an upper bound on the number of patients that can be treated if all hospital resources are re-allocated for pandemic care. The modeling approach is demonstrated on a system of five hospitals each replicating basic elements (e.g. number of beds) of the five hospitals in the Johns Hopkins Hospital System in the Baltimore-Washington, D.C. Metropolitan area under settings relevant to the COVID-19 pandemic.

Although there are opportunities to reduce electrical energy demand in unit processes of mechanical pulp-based paper and paperboard production, this may not be financially beneficial. This is generally because energy optimization opportunities connected to reduced refiner electricity demand in mechanical pulping systems also results in less steam available for the drying of the paper. As modern high consistency refiner systems produce approximately one ton of steam for each MWh of electricity when producing one ton of pulp, a reduction in electric energy demand leads to increased fuel demand in steam boilers to compensate for the steam shortage. In this study, the authors investigated what the financial and environmental situation would look like if they were to expand the system border from a paper mill to a larger system consisting of a mechanical pulp-based paper or paperboard mill, a district heating system with an incineration boiler and a chemical pulp mill. For this purpose, the authors used the FrontWay module with ExtendSim which dynamically allows them to evaluate different scenarios. Their results shows that there is great potential to reduce both carbon dioxide emissions and production costs for industry sites and society by means of these tools.

The SARS-CoV-2 pandemic has driven a need for models that can predict transmission among populations and test the effectiveness of proposed interventions to control it such as testing, quarantining, vaccinations, and nonpharmaceutical interventions. This report describes a hybrid approach that is mostly agent based, but utilizes Ro and time frames from ordinary differential equation (ODE) models to estimate infection rates and reduce data requirements. The ExtendSim model developed is intended to inform management decisions regarding testing and quarantine policies and technologies.

This article investigates outfitting an amphibious platform with an electromagnetic railgun (EMRG), which is a high velocity weapon that can fire projectiles at ranges up to 100 nautical miles. An EMRG would provide the amphibious fleet with offensive capability, as well as defensive capability against surface threats, missiles, and airborne threats. Because the railgun remains in the early stages of development, the Navy’s railgun prototype has been modeled in ExtendSim. Detailed assessment of changes to EMRG design suggest that improvements to the probability of hit of the EMRG has a greater impact on performance than improvements to either cycle time or engagement range. This provides an opportunity for tradeoffs to be made in the design of the railgun and its projectile in which the power requirements (and size) can be scaled down without negatively impacting effectiveness, provided the probability of hit of the projectiles is not reduced.

This video details the construction and implementation of a model that meets the challenge of designing a new hospital. Rob Brownie discusses how Insight Acumen used simulation to move from a planned pilot system to an effective, efficient operation that is able to forecast future demand with reasonable confidence.

Integrating sustainability aspects with operational production scheduling proved to yield significant results for a chewing gum company. Minimizing energy costs just by scheduling the operations on a production is significant on an environmental level, even more than on economical levels. Finding a suitable changeover schedule can make huge differences on the production level, whether minimizing energy costs, minimizing the number of stops and increasing the production line productivity. Going with the simulation approach lead to the testing of many scenarios in a very short time period, giving more time for result analysis and finding ways to reduce the energy consumption even more, whether by finding a more suitable changeover schedules, or discovering bottlenecks that would not have been discovered by other solution techniques. The speed-scaling strategy proved to have a far more important role than just reducing the energy consumptions on machines by slowing them. Utilizations of production lines can be increased if the position of bottlenecks can be identified and the machine speeds are increased slightly.

To determine the operational reliability of a remotely controlled siphon system in multi-wetland systems, an ExtendSim model was built to simulate the siphon flow rate and the time to empty to the wetlands. The siphon system mostly consists of water level switches, air vents, bilge pumps, and an actuated butterfly valve. In this study, the ExtendSim reliability block diagram (RBD) module is employed to assess a remotely controlled siphon system’s operational reliability. The Monte Carlo simulation results from the RBD model demonstrates that the non-repairable siphon system’s operational availability can be enhanced from 0.683 to 0.855 within a 1-year life cycle by increasing the safety factor to 2 for the vulnerable components, such as the water level switch and the air vent. The value can increase to 0.999 when adopting an on-site maintenance strategy. Based on the analysis of multiple scenarios and maintenance strategies, a suitable architecture of the siphon system will guide the field construction work for 12 wetlands in Texas.

Hajj is a mass gathering event that takes place annually in Makkah, Saudi Arabia. Typically, around three million people participate in the event and perform rituals that involve movement within strict space and time restrictions. Despite efforts by the Hajj organizers, such massive crowd gatherings and movement causes overcrowding problems at the Hajj sites.There are are two important rituals that are performed by all the pilgrims at the same venue on the same day - Tawaf, followed by Sayee. Several previous simulation studies on Hajj have focused on the rituals individually. This paper studies both events jointly, rather than separately. Using ExtendSim, the authors integrate the Tawaf and Sayee rituals into one model. The validated model was applied to a wide range of scenarios where different percentages of pilgrims were allocated to the various Tawaf and Sayee areas. The effect of such allocations on the time to complete Tawaf and Sayee indicate strategies for managing these two key Hajj rituals.

The application of mesoscopic discrete rate simulation models for two typical planning tasks in the automotive industry are demonstrated by the authors to illustrate the capability of this modelling class to meet the requirements of logistics and production planners by providing more accurate simulation results. Typically, planning engineers solve these tasks with detailed microscopic simulation models because of the availability of object-based discrete event simulation tools in the automotive industry, which leads to complicated and slow models. However, the combined use of discrete rate and discrete event modeling in mescoscopic models can represent logistics flow processes on an aggregated level through piecewise-constant flow rates by applying the discrete rate simulation paradigm instead of modelling individual flow objects leading to fast model building and computation.

How might one both prevent and control an epidemic spreading of disease (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 a carrier in different ticket queue configurations was compared. Based on the results, several tips and advice was developed for customers and market managers.

This report presents an integrated simulation-based approach to study the on-site production of concrete frameworks by considering the multiple effects of weather on work task productivity and concrete curing process. The ExtendSim model created reports simulated construction time, cost, and CO² emissions for a specific construction setup to facilitate planning and decisions related to resource allocation strategies, construction schedules, different concrete types (including climate-improved concrete), and curing measures for different types of expected weather conditions.

Using an ExtendSim Research Grant for her Masters thesis, Ms. Stauffer is providing an academic addition to the existing literature to better improve further knowledge of switchgrass supply chain needs and management. Working in conjunction with Oak Ridge National Laboratory (ORNL), The Center for Bioenergy Innovation, and the US Department of Energy's Office of Science, Ms. Stauffer submitted and was awarded first place in the poster competition at the Northeast Agricultural and Biological Engineering Conference (NABEC). Once her project is completed, ORNL will be utilizing this data to further their efforts in industrial scale research of bioenergy production from switchgrass.

A portal is designed to support hospitals and regional administrators in responding to the current COVID-19 pandemic and other disease outbreaks. Using mathematical modeling, this collaboration of experts provides recommendations to help hospitals adapt and coordinate to meet demand surges. MASH-Pandemics can:

• Recommend how to increase capacity by providing alternative standards of care, changing operations,or managing demand
• Assess how hospitals can work together to build strong regional responses
• Estimate and prioritize critical supply needs to mobilize supply chains and other external supports
• Measure the evolving response capacity and capability of hospitals

To truly estimate the life cycle of a building, it’s important to find a way to quantify the usage intensity of its individual components. Generally, many factors have an impact on the life span of the components in a building, such as product quality, maintenance, and visitor interaction with the building components, but how can you do that in a building type where user structure and interaction are too complex to analyze, such as in a shopping mall? Using ExtendSim, Shujing Deng created an agent-based model of a real shopping mall with over 100 shops on two floors. Adding the logic of a decision-making mechanism to enable the monitoring of all the interactions between customers and the main building components in the mall, the dynamics of user-space relationships within the shopping mall can be observed, exposing the usage intensity regarding building components. Running different scenarios, simulation results indicate the usage of building components mainly depends on the total number of the consumers in the mall interacting with the objects.

How effective are formalized collaboration strategies when responding to a disaster incident involving mass casualties and area-wide damage? How best can patients be transferred and resources, including staff, equipment and supplies, be shared across hospitals? ExtendSim was used to help quantify hospital system resilience to pandemic, MCI, and disaster events with damage. Patient flows through 9 critical units of multiple hospitals spaced over a large metropolitan region were analyzed to determine impacts on critical resources, physical spaces, and demand. Hospital resilience to these hazard events was evaluated to show the potential of strategies involving not only transfers and resource sharing, but also joint capacity enhancement alternatives to improve post-disaster emergency health care service delivery through joint action.

Due to the globally increasing concern of public health regarding food safety, and quality, the management of agri-food supply chains (ASC) has become even more complex given its special characteristics of perishability, uncertainty of supply and demand, and managing the carbon dioxide equivalent emissions produced throughout the supply chain due to cooling, transportation, and disposal of fresh produce. Using ExtendSim, researchers modeled a two-echelon real life supply chain to study the effect of changing order quantity under uncertain demand and lead time on a set of economic, social, and environmental performance measures. Model results help to minimize food wastage, offer higher quality fresh produce, and lower emissions while maintaining the highest profit and an acceptable service level.

Reentrant flow lines are a special type of production flow line in which a job may visit a machine or group of machines more than once. This reentrancy characteristic results in higher variability of cycle time and throughput rates when compared to traditional production flow lines. A simulation study using ExtendSim shows that by dividing a production line into segments using different CONWIP levels affects the line performance. In fact, in some instances, compared to a single segment CONWIP and push system, using segmented CONWIP can achieve the same throughput rate in a shorter cycle time.

Lignocellulosic biomass derived fuels and chemicals are a promising and sustainable supplement for petroleum-based products. Currently, the lignocellulosic biofuel industry relies on a conventional system where feedstock is harvested, baled, stored locally, and then delivered in a low-density format to the biorefinery. However, the conventional supply chain system causes operational disruptions at the biorefinery mainly due to seasonal availability, handling problems, and quality variability in biomass feedstock. Operational disruptions decrease facility uptime, production efficiencies, and increase maintenance costs. For a low-value high-volume product where margins are very tight, system disruptions are especially problematic. In this work we evaluate an advanced system strategy in which a network of biomass processing centers (depots) are utilized for storing and preprocessing biomass into stable, dense, and uniform material to reduce feedstock supply disruptions, and facility downtime in order to boost economic returns to the bioenergy industry. A database centric discrete event supply chain simulation model was developed, and the impact of operational disruptions on supply chain cost, inventory and production levels, farm metrics and facility metrics were evaluated. Three scenarios were evaluated for a 7-year time-period:

1. bale-delivery scenario with biorefinery uptime varying from 20 to 85%
2. pellet-delivery scenario with depot uptime varying from 20 to 85% and biorefinery uptime at 85%
3. pellet-delivery scenario with depot and biorefinery uptime at 85%

In scenarios 1 and 2, tonnage discarded at the field edge could be reduced by increasing uptime at facility, contracting fewer farms at the beginning and subsequently increasing contracts as facility uptime increases, or determining alternative corn stover markets. Harvest cost was the biggest contributor to the average delivered costs and inventory levels were dependent on facility uptimes. We found a cascading effect of failure propagating through the system from depot to biorefinery. Therefore, mitigating risk at a facility level is not enough and conducting a system-level reliability simulation incorporating failure dependencies among subsystems is critical.

Establishing a pricing strategy and managing inventory of perishable products can easily be a retailer’s nightmare. How do you maximize revenue while minimizing food waste? As a product nears the end of its lifetime, will customers still purchase it at the same price as when it was fresh? If you reduce the price as the product ages, what might that price point be so customers will purchase it and you will be left with little to no waste? Or do you cut inventory so product will sell out before it ages, but leaving some customers without needed product? This paper investigates dynamic pricing strategy with the objective of maximizing revenue and minimizing food waste to ensure sustainability and customer satisfaction.

Reentrant flow lines are a special type of production flow line in which a job may visit a machine or group of machines more than once. This reentrancy characteristic results in higher variability of cycle time and throughput rates when compared to traditional production flow lines. A simulation study using ExtendSim shows that by dividing a production line into segments using different CONWIP levels affects the line performance. In fact, in some instances, compared to a single segment CONWIP and push system, using segmented CONWIP can achieve the same throughput rate in a shorter cycle time.

Lignocellulosic biomass derived fuels and chemicals are a promising and sustainable supplement for petroleum-based products. Currently, the lignocellulosic biofuel industry relies on a conventional system where feedstock is harvested, baled, stored locally, and then delivered in a low-density format to the biorefinery. However, the conventional supply chain system causes operational disruptions at the biorefinery mainly due to seasonal availability, handling problems, and quality variability in biomass feedstock. Operational disruptions decrease facility uptime, production efficiencies, and increase maintenance costs. For a low-value high-volume product where margins are very tight, system disruptions are especially problematic. In this work we evaluate an advanced system strategy in which a network of biomass processing centers (depots) are utilized for storing and preprocessing biomass into stable, dense, and uniform material to reduce feedstock supply disruptions, and facility downtime in order to boost economic returns to the bioenergy industry. A database centric discrete event supply chain simulation model was developed, and the impact of operational disruptions on supply chain cost, inventory and production levels, farm metrics and facility metrics were evaluated. Three scenarios were evaluated for a 7-year time-period:

1. bale-delivery scenario with biorefinery uptime varying from 20 to 85%
2. pellet-delivery scenario with depot uptime varying from 20 to 85% and biorefinery uptime at 85%
3. pellet-delivery scenario with depot and biorefinery uptime at 85%

In scenarios 1 and 2, tonnage discarded at the field edge could be reduced by increasing uptime at facility, contracting fewer farms at the beginning and subsequently increasing contracts as facility uptime increases, or determining alternative corn stover markets. Harvest cost was the biggest contributor to the average delivered costs and inventory levels were dependent on facility uptimes. We found a cascading effect of failure propagating through the system from depot to biorefinery. Therefore, mitigating risk at a facility level is not enough and conducting a system-level reliability simulation incorporating failure dependencies among subsystems is critical.

Establishing a pricing strategy and managing inventory of perishable products can easily be a retailer’s nightmare. How do you maximize revenue while minimizing food waste? As a product nears the end of its lifetime, will customers still purchase it at the same price as when it was fresh? If you reduce the price as the product ages, what might that price point be so customers will purchase it and you will be left with little to no waste? Or do you cut inventory so product will sell out before it ages, but leaving some customers without needed product? This paper investigates dynamic pricing strategy with the objective of maximizing revenue and minimizing food waste to ensure sustainability and customer satisfaction.

This study builds on earlier research which focuses on the use of combined simulation methods to support healthcare demand predictions. The authors developed a hybrid simulation model composed of two submodels which were built using different simulation paradigms. Both models, i.e. a population model based on a continuous modeling approach and an arrivals model built with discrete-event methodology, were created in ExtendSim. This combined model simulates the consequences of demographic changes, the variability in incidence rates that result from an aging population, and the seasonal fluctuations in epidemic trends on future demand for healthcare services.

OCEAN-CERTAIN was an ambitious collaborative project with natural scientists, working with the ecosystem and the biological pump, and social scientists studying possible consequences for society who worked to create more certainty about the contributions of our oceans during climate change. Climate change poses serious risks for both natural systems and human beings, and plausible and feasible policy decisions and strategies to mitigate these risks are urgently needed. However, there are important knowledge gaps surrounding the large-scale natural processes and interactions with social-economic processes that play an important role for our oceans. The multi-disciplinary project OCEAN-CERTAIN (Ocean Food-web Patrol – Climate Effects: Reducing Targeted Uncertainties with an Interactive Network) aimed to shed light on these processes.

Using a combination of metamodel simulations, system dynamics with the custom-designed GUI functionalities of ExtendSim, Ocean Certain has created a a powerful tool for the evaluation and demonstration of policy alternatives under different climate and socio-economic conditions. This decision support system was designed to serve as knowledgebase and knowledge generator to examine the feedback mechanisms linking the ocean food web system to the social-economic system of the coastal zones.

Simulations offer valuable insights into how an instrument can be expected to perform and can also point to areas for improvement. In the case of polarimeters described in this article, it is of interest to simulate the motion of the analysing polarizer relative to the fixed defining polarizer as this forms the basis for the optical rotation measurements. To make the simulation more realistic the author incorporated additional factors including (i) the broadband nature of the LED’s emission spectrum, (ii) the variation of the specific rotation of the sample as a function of wavelength, (iii) the spectral response of the detector and (iv) the temperature at which measurements are performed.

Defining replenishment policies for perishable products is an important activity, particularly where suppliers have a range of products. As product ranges increase, consumers can substitute products if their preferred product is out of stock. Such substitution considered simultaneously as perishability makes it difficult to achieve balanced results over different departments/companies in the face of fluctuating demand. Given these circumstances, a financially calculated replenishment policy makes communicating the impact of operational changes difficult. In contrast, non-financial measures improve the communication between departments and staff (e.g., between warehousing, procurement, and sales), and allows them to set operational targets from broad corporate strategies. This study contributes to inventory management theory by being the first research to develop a non-financial framework and demonstrate its comparability to financial approaches for perishable and substitutable inventory.

Shipbuilding is one of the most complex existing manufacturing processes. The large number of operations necessary to produce the parts that make up a vessel coupled with the need to synchronize multiple workflows and numerous resources where serial production is practically non-existent, make the management of such a production system very difficult. Simulation is an extremely powerful tool for the decision-making process to test and evaluate different scenarios, to efficiently plan future investments, to determine the allocation of resources, and to drastically reduce the risks of making incorrect decisions.

This case study uses ExtendSim to model the manufacturing process of a frigate from the shipyard of Navantia Ferr to minimize the uncertainties of its construction.

Carollo Engineers, Inc. Blue Plan-it® was selected from a shortlist of 200 firms for the 2017 Software Technology Innovation Award, given by Corporate Vision Magazine. This is an exceptional achievement, since that Carollo is really not a software company.

Developed by Carollo to help municipal service providers manage complex, interconnected water and wastewater infrastructure, storage, treatment, conveyance, and distribution systems, Blue Plan-it is a fully customizable simulation and optimization model suite developed in ExtendSim. Blue Plan-it takes an agency’s vast quantity of data, including maintenance, geographic, regulatory, and financial information, and creates a customized graphical user interface that can be easily modified, understood, and presented.

This presentation outlines the story of a Medical Device Fortune 500 company’s experience in implementing a combined simulation and optimization solution not integrated to the primary ERP system of a critical manufacturing location. You'll learn about the pros and cons, and the challenges and lessons learned, during the implementation process using a discrete simulation model using OpStat methodology launched in two critical areas in 2015 and 2016. After a weekly simulation and optimization process was enacted, customer service rose to unprecedented levels, while plant financial performance became enterprise benchmarks. The process knowledge acquired by the team during the implementation also resulted in a major shift in the nature of the work of the planning organization, evolving from a group of schedulers to a team of holistic capacity planners. To accomplish this task in an evidence-based way, a simulation model was developed using ExtendSim. This approach helped the clinical, managerial, and facility staff to not just understand their existing department workflow but also to provide them the opportunity to test trans-disciplinary scenarios to guide the design of the new emergency department. Furthermore it provided the client with the statistics to evaluate the impact a new Chest Pain & General Observation Center and Results Waiting Lounge would have on their entire system.

Up until now, most of the models developed to optimize biomass supply chains have failed to quantify the effect of biomass quality and the preprocessing operations required to meet biomass specifications on overall cost and performance. However, the IBSAL-SimMOpt method provides a novel approach for finding near-optimal solutions to the problem of designing biomass supply chains that improve the physical characteristics of the feedstock at an acceptable cost. The bioenergy sector and the research community now have access to a simulation-based optimization model with activity-based costing that is capable of representing the stochastic behavior of some elements intervening in the corn stover supply chain for the production of bioethanol. This analytical model can be used for decision making as well as educational and training purposes since it allows the user to conduct “what if” scenarios.

Subsea production and processing systems have become a hot topic among research institutes and industries. While highlighting the advantages on production and economy, the reliability issues show a different picture with limited access, difficulty of maintenance and possibly lower availability. The influence of these issues on the system performance is studied in this paper to evaluate the benefit of subsea systems.

Is it really beneficial for pharmacists to administer pandemic influenza vaccines? Absolutely! Using ExtendSim, researchers showed that weekly national vaccine administration capacity increased to 25 million doses per week when pharmacist vaccinators are integrated into pandemic vaccine response planning. In addition, the time to achieve 80% vaccination coverage nationally was reduced by 7 weeks, assuming high public demand for vaccination.