i Papers | Simio

Papers

Automatically generating Flow Shop Simulation Models from SAP Data (BearingPoint GmbH)

Automatic model generation, the consequential reduction of problem solving cycles and the need for a higher degree of data integration have long been characterized as significant challenges in the field of simulation of manufacturing systems. Especially operationally used manufacturing simulation models require a high degree of modeling detail and thus depend on a significant amount of input data. In many cases, the time and effort required to manually build such a detailed model and keeping it up-to-date are prohibitive. This paper describes a practical case in which entire simulation models of a complex and large scale automotive flow shop production were automatically created from an automotive company’s SAP and MES systems in order to support operational planning purposes and reduce operational logistical risks, such as production disruptions caused by stock-out situations at the manufacturing line.

Read more.

RPS Simulation of US Air Force F-16 Fleet Phase Maintenance Cycle (USAF)

In fleet management, aircraft undergo phase inspection to maximize aircraft availability. An aircraft is grounded after reaching a maximum threshold of flight hours accrued since its last phase inspection. To manage this process, planners use a time distributed index to track the phase cycle of individual aircraft and keep the planes respectively in-phase. As planes break and maintenance lines become backed-up, the avail-ability of aircraft diminish; the desired effect for the mission is lost, and the constant use of spare planes invite future scheduling hazards. In this example, planners are constantly faced with determining schedules with several random factors and risk. The model presented here via Simio is a risk-based planning and scheduling simulation to identify risk and account for randomness in phase cycles. The result of this model provides the planners the opportunity to input an actual schedule into the system, assess fleet health, and conduct what-if analysis.

Read more.

A 401(k) Market Simulation To Evaluate Autoportability For Small Investors (Retirement Clearinghouse, LLC)

One of the most pressing issues in the current 401(k) retirement system is the problem of employees cashing out their accounts when they leave a job. This is especially true for accounts less than $5,000. After leaving a job, approximately 60% of these individuals will cash out within a year and approximately 90% will cash out within 7 years. Retirement Clearinghouse, LLC (RCH) has proposed changes to the retirement system where a clearinghouse will find an employee’s new 401(k) through records matching technology and automatically merge the previous 401(k) with the new 401(k). The name for this new process is autoportability. This simulation evaluated the impact of autoportability on the retirement market and it demonstrates that on a cumulative basis over the 40-year time horizon, cash outs decline from $320 billion to $164 billion, while Roll-Ins increase from $15 billion to nearly $130 billion, helping millions to preserve their retirement.

Read more.

Automated Production System Simulations Using Commercial Off-the-shelf Simulation Tools

A multi-year research project focused on a global aerospace company’s design-to-production transition, and in particular how to answer production-related questions much earlier in a program’s design cycle than is possible today. A fundamental difficulty is that the time and expertise required to formulate appropriate analysis models prevents their routine use, especially in new program development. The project’s goal was to reduce these requirements, and by late 2014 a methodology had been developed for on-demand analysis generation to answer routine questions about production systems. A pilot project was conducted in 2015 to demonstrate efficacy, that an implementation of the methodology could in fact reduce by at least an order of magnitude the time required to answer a frequently-asked question, in a repeatable way while specification of the products, their process plans, planned facilities, and available resources were frequently changing. This paper summarizes the methodology, its pilot project implementation, and preliminary results.

Read more.

Agent-based modeling and simulation with Simio

Agent-based modeling and simulation is a relatively modern approach to modeling systems. It allows modeling of the dynamics of complex and cybernetic systems. These are often self-organizing systems which produce emergent effects, e.g. the escape behavior of people. The goal is the design of a library for agent-based simulation in Simio.

Read more.

Optimization of Storage Allocation using an automatically generated Warehouse Simulation Model (BearingPoint GmbH)

Classical planning approaches of storage allocation decisions are often conducted iteratively with significant manual effort. Warehouse layouts are generated on the basis of planners’ experiences with the target to reduce the operators’ travel distances and thereby to increase productivity. By combining optimization and simulation in a software-based planning tool, a multitude of mathematically optimized storage allocation scenarios can be generated and analyzed to improve traditional planning approaches. This paper describes a practical case of a German automotive manufacturer’s warehouse allocation problem that is approached using an evolutionary meta-heuristic. The best solutions of the optimization are loaded into a large scale, automatically generated simulation model and evaluated using the company’s real-life data.

Read more.

Computer Simulation of Administrative Processes for Resource Planning and Risk Management (National Institutes of Health)

A variety of challenges are inherent to the provision and management of administrative services in a federal agency, including the Office of Research Services (ORS) at the National Institutes of Health (NIH). Many administrative functions are both regulatory and policy driven, and requirements are constantly changing. As the NIH research mission requirements change and evolve, the demand and nature of administrative support evolves as well. Resources need to be planned for and the proper tools are required to be in place in this dynamic environment in order to achieve success in providing the required administrative services, in a timely manner, with quality outcomes. The output of these processes in most, if not all, cases is ‘intangible’ and process visibility is limited. Computer simulation techniques will be utilized to develop a more in-depth understanding of these administrative functions, develop recommendations for improved resource allocation, productivity and quality improvement, and enhance communication and visibility of these processes among customers and stakeholders.

Read more.

Eradicating the Average: Answering Complex Healthcare Questions Using Discrete Event Simulation (Array Advisors)

Traditionally, architects rely on average utilization benchmarks to determine appropriate department sizes when planning a new facility. While these averages might adequately predict space for the design of an office building or parking lot, they sometimes fall short of accurately determining the amount of space needed for healthcare facilities. A community hospital in a costal Mid-Atlantic state is experiencing significant emergency department (ED) holds due to a lack of inpatient capacity. Analysis of patient arrival and unit assignment data led the team to believe that treating observation patients in inpatient units is causing the capacity problem. A discrete event simulation (DES) model helped determine the appropriate size of an observation unit needed to reduce ED holds and relieve current inpatient pressures.

Read more.

Empty Container Stacking Operations: Case Study of an Empty Container Depot In Valparaiso Chile

This study analyzes the handling operations performance at an Empty Container Depot that serves different shipping lines operating with the port of Valparaíso, Chile. With the aid of a discrete event simulation model built in Simio that interacts with an SQL Server database, we seek to improve container stacking policies and to redesign the depot’s layout such that truck turn-around times decrease.

Read more.

Raising the Dynamics: Simulation-Based Performance Analysis for Lelystad Airport

Amsterdam’s Schiphol capacity is limited to 500,000 air traffic movements per year and currently is reaching the limit. For that reason, Schiphol Group decided to divert the non-hub related traffic to the regional airport in Lelystad. This airport will be upgraded to handle commercial traffic, mainly low cost carriers. We used a divide and conquer approach in SIMIO modules in which we included the main elements in the system namely airspace, runway, taxiways and airport stands for analyzing the future performance and potential operative problems of the airport. An analysis of the different operative areas of the system was performed and we could identify problems due to the emergent dynamics once the different subsystems interacted between them.

Read more.

Simulating a Pre-Archival System

We developed a simulation model in SIMIO representing the system elements of the pre-archival process taking place at the largest archival services company in Israel. The pre-archival process usually involves a data entry operator manually registering retrieval information of boxes and files arriving on a roller-conveyor before they are assigned a space at the storing facility. The operators sit around the conveyor and pick a barcoded box. Using the simulation model we explored the behavior of the original system and identified opportunities for efficiency improvement. Initial changes in the system have shown an improvement in the system’s capacity of up to 15% over several months. The following sections provide the system descriptions and features of the modelling components.

Read more.

Simulation of Triaging Patients Into an Internal Medicine Department to Validate the Use of an Optimization Based Workload Score

This extended abstract provides an overview of the development of a simulation model to be used in the assistance of triaging patients into the Hospital Internal Medicine (HIM) Department at The Mayo Clinic in Rochester, MN in an effort to balance workload among the department services. The main contribution of this work is the development of a score that measures provider workload more accurately. Delphi surveys, conjoint analysis, and optimization methods were used in the creation of this score and it is believed to better represent provider workload. Preliminary results were based on the proportion of time of a month that each service was at or above “maximum utilization”, which is how workload is currently viewed at an instance. A simulation model built in SIMIO 8 yielded a 12.1% decrease in the proportion of time that a service was at or above their “max utilization” on average, while also seeing a decrease in the average difference among these proportions by 8.3% (better balance among all services).

Read more.

SAP PP/DS versus Simio for Production Scheduling

This article will answer the following questions. What are the Differences in Production Scheduling Between PP/DS and Simio? What is Each System Essentially Designed to Model? What Types of Manufacturing Environments Work for Each? What are the Available Views in Each Application? Where does Each Application Stand in Terms of Reporting? How Does Each Application Deal with Constraint Based Planning? How are the Applications Setup? How do the Applications Compare in Terms of Integration to ERP Systems?

Read more.

Simio Model to Improve Procedure Scheduling in Outpatient Surgery Suite

A simulation model built in Simio was used to study the current schedule of the procedures for an Outpatient Surgery (OPS) Suite. Simio was used to build an open 1-year calendar as the schedule of the OPS. The calendar is represented by a table in Simio where the number of rows represents the days in the year and the number of columns represents the number of time slots in the day based on the shortest appointment. There are 3 rooms in the OPS, hence, 1 calendar was built for each room. The calendar (table) cells are filled with zero if the time slot is available or one if the time slot has been already reserved or blocked. According to the annual demand achieved from the historical data [made and scheduled dates], the simulation is run to book appointments in the available slots based on specific rules. The simulation model is used to study different scheduling modules like blocking certain rooms at specific times for some procedures. This white paper mainly discusses how Simio made this complicated exercise an easy and enjoyable technique to implement.

Read more.

Use of Simulation and Modeling for Efficient and Effective Scheduling of Offshore Supply Vessels (Shell E&P Company)

The solution, modeled from land transportation optimization systems, consists of three primary tools—one for real time status of the vessels, another for up-to-date demand requests, and finally a scheduling system. Due to the variability of weather, permissible delivery times, loading and unloading times, vessel traffic, and changing geographical locations of floating rigs, it became clear that the scheduling tool should be built on a spatially aware, discrete event simulator and be capable of assessing the risks of a given schedule.

Read more.

Agent-Based Simulation for Composite Manufacturing Technology Evaluation (Boeing Research and Technology)

This study was requested by manufacturing technology groups within Boeing to evaluate the feasibility and capability of AFP for use on a specific part for an airplane program in development. The requestors were interested in estimating how the current state of the art would perform on a given part in a proposed production system. Furthermore, they were interested in developing a set of parameters and minimum allowable values for use in a Request for Proposal (RFP) document. The customer provided a set of decision variables, KPIs, and system properties as detailed in Table 1. They also provided high-level part geometry and production rate requirements.

Read more.

Discrete Event Simulation of Virgin Australia's Domestic Aircraft Gates at Melbourne Airport (Virgin Australia)

A new gate plan at MEL was being considered which decreased Virgin’s utilization of the existing common user terminal and increased utilization of the dedicated Virgin terminal. While all scheduled aircraft arrivals and departures could be scheduled with the decreased gate capacity, there was some concern on potential impacts to OTP due to off schedule arrivals and departures and lack of flexibility to make changes during day of operations. In addition to OTP impacts, the potential negative guest experience due to increased aircraft queuing for gate on arrival and increased utilization of the gate without an aerobridge was of concern.

Read more.

Smart Simulation: Integration of Simio and Matlab (Western New England University)

The proposed SIMIO step integrates a simulation software to a computational agent in order to perform high computational operation like optimization. Several applications are presented to illustrate the potential of the proposed CallMatlab step instance in order to implement IOS modeling. However, this step is not limited to perform optimization and could be utilized to execute any type of calculation whichever user desires. We believe this addition, adds a new dimension to simulation modeling approach. This would enable experts to enjoy the modeling simulation while implementing their own logics and decision making tools within the simulation run.

Read more.

Traffic Signal and Operations Optimization Study

The heavily traveled commuter corridor carries over 30,000 vehicles per day with average annual traffic increases of between nine and ten percent. The project corridor includes seven signalized intersections and three non-signalized intersections, including an non-signalized entrance and exit to a large grocery store. The current system experiences many traffic accidents as travelers are attempting to access and depart the store. Traffic analysis was conducted to determine traffic flow patterns by time of day in order to determine the number of signal timing plans is needed for the duration of a day. Analysis was conducted using SIMIO modeling software. The model was compared and calibrated to observed conditions to validate the model before analyzing scenarios of optimized coordinated signal timing plans along the corridor

Read more.

Tutorial: Tips for Successful Practice of Simulation

In spite of what you might have heard, doing simulation projects well is not easy. There are many ways that even an experienced simulationist can fail. In this paper we have discussed some common traps and ways to avoid them. While following these suggestions will not guarantee a bull’s eye, it will certainly improve your chance of hitting the target.

Read more.

Crude-By-Rail Transload Terminal Simulation

A midstream petroleum company was designing and developing improvements at an existing facility to increase their crude-by-rail terminalling and transloading business, accomplished by expanding and reconfiguring their rail / truck infrastructure to create a new interface point between pipeline and rail transport. The company recognized the need to apply modeling and simulation technology to represent the new crude loading system in a dynamic environment, therein incorporating inherent variability, to validate the design and make informed decisions. There was the specific need to verify the process design throughput of the loading facility, in the holistic context of the anticipated logistics and business/market environment.

Read more.

Simulation of Theme Park Ride Design and Operations

Simulation was used to help design engineers better understand the operating dynamics of a unique, not-yet-built theme park ride to gain insight into whether or not the ride is likely to function as designed while keeping within safety parameters. The analysis also assessed different methods of configuring ride operations to maintain maximum rider throughput and avoid interruptions to the rider experience resulting from delays in the load/unload station.

Read more.

A Discrete-Event Simulation Approach to Identify Rules that Govern Arbor Remodeling for Branching Cutaneous Afferents in Hairy Skin (University of Virginia)

In mammals, touch is encoded by sensory receptors embedded in the skin.For one class of receptors in the mouse, the architecture of its Merkel cells, unmyelinated neurites, and heminodes follow particular renewal and remodeling trends over hair cycle stages from ages 4 to 10 weeks. As it is currently impossible to observe such trends across a single animal’s hair cycle, this work employs discrete event simulation to identify and evaluate policies of Merkel cell and heminode dynamics. Well matching the observed data, the results show that the baseline model replicates dynamic remodelingbehaviors between stages of the hair cycle – based on particular addition and removal polices and estimated probabilities tied to constituent parts of Merkel cells, terminal branch neurites and heminodes. The analysis shows further that certain policies hold greater influence than others. This use of computation is a novel approach to understanding neuronal development.

Read more.

Empty Container Stacking Operations: Case Study of an Empty Container Depot in Valparaiso Chile (PUCV, Auburn University and University of Los Andes)

This paper describes a detailed stochastic simulation model integrated with a transactional database to model operations in an empty container depot. Empty container depots are found ubiquitously in supply chains around the world but there has been virtually no quantitative research done to assess operational policies nor layout designs. In this work we determine the performance of operational policies related to the stacking and retrieval of empty containers to derive recommendations for policy improvements and, in future work, the yard layout design. A simulation model was chosen as the proper tool to address these aims because of the uncertain nature and complex handling actions of an empty container depot. Results thus far show that policies concerning remarshaling and retrieval strongly influence the efficiency of the depot operations in terms of the truck turnaround times of trucks, as well as the utilization of the resources which include yard cranes and personnel.

Read more.

Hierarchical Simulation Modelling Of Distribution Centers (Ohio University)

Order picking is the most expensive operation in a distribution center. Due to a large amount of labor used in order picking, the cost associated with the labor is high. The objective of this paper is to build a simulation model that would help distribution center managers to forecast their throughput by optimizing the worker configuration. The research uses a hierarchical approach to build a simulation model. The simulation model is divided into small submodels. The submodels are completely independent of each other. The submodels can be combined to make various different complete models. In this research, the submodels are used to build a simulation model of an actual industrial distribution center. The model is then run for twenty-four hours and the results are compared with the flat simulation model of the same distribution center.

Read more.

Simulation Modeling of Shuttle Vehicle-Type Mini-Load AS/RS Systems for E-Commerce Industry of Japan (St. Andrew's University and Chuo University)

Order picking is the most expensive operation in a distribution center. Due to a large amount of labor used in order picking, the cost associated with the labor is high. The objective of this paper is to build a simulation model that would help distribution center managers to forecast their throughput by optimizing the worker configuration. The research uses a hierarchical approach to build a simulation model. The simulation model is divided into small submodels. The submodels are completely independent of each other. The submodels can be combined to make various different complete models. In this research, the submodels are used to build a simulation model of an actual industrial distribution center. The model is then run for twenty-four hours and the results are compared with the flat simulation model of the same distribution center.

Read more.

Single and Multi-objective Parameter Estimation of a Military Personnel System via Simulation Optimization (University of Louisville)

A discrete event simulation model is developed to represent a forced distribution performance appraisal system, incorporating the structure, system dynamics, and human behavior associated with such systems. The aim of this study is to analyze human behavior and explore a method for model validation that captures the role of subordinate seniority in the evaluation process. This study includes simulation experiments that map black-box functions representing human behavior to simulation outputs. The effectiveness of each behavior function is based on a multi-objective response function that is a sum of squared error function measuring the difference between model outputs and historical data. The results of the experiments demonstrate the utility of applying simulation optimization techniques to the model validation phase of simulation system design.

Read more.

The Application of Simio Scheduling in Industry 4.0 (Simio LLC)

Simulation has traditionally been applied in system design projects where the basic objective is to evaluate alternatives and predict and improve the long term system performance. In this role, simulation has become a standard business tool with many documented success stories. Beyond these traditional system design applications, simulation can also play a powerful role in scheduling by predicting and improving the short term performance of a system. In the manufacturing context, the major new trend is towards digitally connected factories that introduce a number of unique requirements which traditional simulation tools do not address. Simio has been designed from the ground up with a focus on both traditional applications as well as advanced scheduling, with the basic idea that a single Simio model can serve both purposes. In this paper we will focus on the application of Simio simulation in the Industry 4.0 environment.

Read more.

A Down to Earth Solution: Applying a Robust Simulation-Optimization Approach to Resolve Aviation Problems (Amsterdam University of Applied Sciences and Ecole Nationale de l'Aviation Civile)

This paper deals with the improvement of the robustness of heuristic solutions for aviation systems affected by uncertainty when the resolution of conflicts is implemented. A framework that includes the use of optimization and simulation is described which in turn generates pseudo-optimal schedules. The initial solution is progressively improved by iteratively evaluating the uncertainty in the generated solutions and calibrating in accordance with the objective function. Simulation is used for testing the feasibility of a solution generated by an optimization algorithm in an environment characterized by uncertainty. The results show that the methodology is able to improve solutions for the scenarios with uncertainty, thus making them excellent candidates for being implemented in real environments.

Read more.

Simulation-based Dynamic Shop Floor Scheduling for a Flexible Manufacturing System in the Industry 4.0 Environment (Chuo University)

The Industry 4.0 environment enables direct communication between the manufacturer’s shop floor and a customer. Thus, the manufacturer is able to respond to the customers’ requests more quickly, meaning that manufacturers must now more tightly control the shop floor planning and scheduling. Here we present a simulation-based scheduling model for Flexible Manufacturing System dynamic shop-floor control. The customer’s order and the processing sequence table of the products are imported into the simulation model. Experiments are implemented for the case wherein the system encounters unexpected conditions. The proposed approach represents a potential tool for manufacturers to make decisions in the real time by further connecting to the Enterprise Resource Planning and Manufacturing Execution System.

Read more.

Design and Simulation Analysis of PDER: A Multiple-Load Automated Guided Vehicle Dispatching Algorithm (Rochester Institute of Technology)

Effective control strategies for automated guided vehicles (AGVs) are important to companies that operate flexible manufacturing systems in terms of maximizing productivity. In this paper, we design and analyze Pickup-or-Delivery-En-Route (PDER), a multiple-load AGV dispatching algorithm. PDER is a task-determination rule that enables a partially loaded vehicle traveling to a drop off destination to pickup and/or drop off loads that the vehicle would otherwise pass by en route to the original destination. We conduct a simulation-based experiment to evaluate the effectiveness of the PDER algorithm. The results indicate that PDER can produce significant positive impacts on throughput and time in system in flexible manufacturing systems utilizing multiple-load AGVs.

Read more.

Inside Discrete-Event Simulation Software: How It Works and Why It Matters (University of Michigan, Dan Brunner Associates LLC and Auburn University)

This paper provides simulation practitioners and consumers with a grounding in how discrete-event simulation software works. Topics include discrete-event systems; entities, resources, ciontrol ele-ments and operations; simulation runs; entity states; entity lists; and their management. The imple-mentations of these generic ideas in AutoMod, SLX, ExtendSim, and Simio are described. The pa-per concludes with several examples of “why it matters” for modelers to know how their simulation software works, including discussion of AutoMod, SLX, ExtendSim, Simio, Arena, ProModel, and GPSS/H.

Read more.

Integrating Campus Operations Decision Support Models at the National Institutes of Health (NIH) (National Institutes of Health)

At the National Institutes of Health (NIH), a federal agency supporting basic biomedical research, decision makers are faced with the challenge of identifying ways to improve the efficiency and effectiveness of research support services and challenges of doing “more with less” resources. The Office of Research Services (ORS), Office of Quality Management (OQM) provides support in solving these challenges through development of the Campus Operations Decision Support (CODS) simulation model. The model consists of a variety of software tools and techniques to model a cam-pus 3D “virtual world” that can be used in a variety of applications to better understand and enhance the delivery of services to support the research mission at NIH. The project includes sub-models that aid in analyzing pedestrian and traffic movement onto and within the campus, visitor screening, the NIH shuttle bus network, and provides for future extensibility to additional research support activities.

Read more.

Simheuristic of Patient Scheduling Using a Table-Experiment Approach - Simio and Matlab Integration Application (Northeastern University, State University of New York at Binghamton and Western New England University)

This paper focuses on optimizing patient scheduling at a breast cancer center for two types of patients: follow up and consult patients. Follow up and consult patients have different service times and follow different care pathways. The objective of this paper is to sequence the patients such that minimum average flow time is achieved for each patient type. A simheuristic framework is developed by integrating MATLAB, Simio, and Excel. Unlike existing simulation-optimization (SO) approaches that target the simulation model controls, this framework tries to optimize a data table in the simulation environment. This simulation evaluation (SE) approach could iteratively input patients arrival table into the simulation model, and obtains the expected performance of the system as a reference to generate the next solution. The obtained results from this framework are further analyzed by comparing five heuristic appointment scheduling methods.

Read more.

Using Simulation to Estimate Evacuation Times in Large-size Aircrafts: A Case Study with Simio (Universitat Autònoma de Barcelona, Open University of Catalonia - IN3, Universitat Politècnica de Catalunya - BarcelonaTech and Open University of Catalonia - IN3)

After an emergency landing, it is essential to quickly evacuate the aircraft. Typically, a maximum limit of time is set, which does not depend on the number of passengers on board, the hour (day/night), or the number of inoperative emergency exits. In order to develop strategies and protocols for efficient evacuations, it is important to define all the characteristics of the aircraft, analyze multiple scenarios that may arise, conduct a comprehensive study of passengers' behavior, and consider external factors that may affect the evacuation time. Nowadays, there are flexible and powerful object-oriented simulation tools that enable the creation of realistic models, which are useful to assess evacuation strategies by studying different scenarios. In this context, this paper presents a model to analyze realistic scenarios for the evacuation of the Airbus 380, which must be done in less than 90 seconds.

Read more.

Case Study in 3D Modeling of 2D Plan View CAD Data for Use in Computer Simulation (National Institutes of Health)

After Computing and computing graphics capabilities continue to improve and evolve. What was once science fiction, such as photorealistic real-time rendering now common in video games, to low cost virtual reality (VR), is now commonplace. As people experience these technologies in their personal lives, there is a greater demand and expectation that computer simulation utilized in a business or institutional setting have a similar degree of visually appealing content and user experience. These capabilities contribute to the acceptance and usefulness of these tools. This case study suggests an approach, as well as tools and techniques, utilized to automate and lessen the resources required to develop three dimensional (3D) models of a large campus environment from traditional two dimensional (2D) plan view computer aided drafting (CAD) data that can be utilized in computer simulation.

Read more.

Improving Historical Demand Data Through Simulation (UNAM)

Organizations collect data during different periods so that they can use them for management and business purposes. However, the data do not always come in the most suitable form for analysis, and often needs to be prepared, for which there are a variety of methods, including simulation. This paper presents a case where simulation is used as a tool to get insights into demand, based on historical data. Through simulation, we extract the most frequent demand events for two types of jobs together with the worst events. The simulation model is based on the historical data from a private oil company that operates in Mexico. In addition, we show how simulation results improve the information about Scorecard data recorded during a year of work.

Read more.

The History of Simulation Modeling (North Carolina State University and Simio, LLC)

During the past half-century simulation has advanced as a tool of choice for operational systems analysis. The advances in technology have stimulated new products and new environments without software standards or methodological commonality. Each new simulation language or product offers its own unique set of features and capabilities. Yet these simulation products are the evolution of research, development, and application. In this paper we interpret the historical development of simulation modeling. In our view simulation modeling is that part of the simulation problem-solving process that focuses on the development of the model. It is the interpretation of a real production (or service) problem in terms of a simulation language capable of performing a simulation of that real-world process. While “interpretation” is in the “eyes of the beholder” (namely us) there are some historical viewpoints and methods that influence the design of the simulation model.

Read more.

Wealth Distribution Simulation Using a System Dynamic Flow Model (UNAM)

In a simple economic system each agent exchange its wealth in return of commodities emerging an unequal wealth and income distribution, which has been estimated through a Pareto’s Distribution and by Gini’s Coefficient as well. This system has been long studied using different approaches, in this work a simple model of wealth distribution is enhanced through a dynamic system simulation approach implemented in SIMIO, considering the division proposed by Statistics and Information Bureau which divides population in ten equal sized monthly income class called deciles, which are represented by ten flow tanks in a fully connected network linked with FlowConnectors from the SIMIO’s flow library. Agent's wealth exchange is represented as a flow moving between tanks ruled by a specific exchanged function. Through simulation performances, using Mexico's information, a better insight and different scenarios are possible to obtain in order to support policymakers.

Read more.

A Flexible Simulation Model Aimed to Improve Inpatient Units in Health Care (Ohio University)

In the past few decades, simulation in healthcare has gained immense attention from researchers because of its ability to detect problems that help in the improvement of the facility. It is important for any healthcare to know how many beds, nurses, and therapist they need in their facility to improve their service. In this research, we have created a customized object that is used to design simulation model for progressive care unit in a hospital. The objective of this research is to a make a flexible simulation model that can easily be extended and re used to make simulation model for any facility. The simulation model built would help the health care personnel in determining the number of beds, therapists and nurses in their facility.

Read more.

Teaching Undergraduate Simulation - 4 Questions for 4 Experienced Instructors (Auburn University, Georgia Institute of Technology, Cornell University and UC Berkeley)

This paper and the corresponding panel session focus on teaching undergraduate simulation courses. The format brings together four experienced instructors to discuss four questions involving the structure and topic outlines of courses, print and software teaching materials used, and general teaching methods/philosophy. The hope is to provide some experience-based teaching information for new and soon-to-be instructors and to generate discussion with the simulation education community.

Read more.

Virtual Enterprise, a Management Training Tool (U. de Las Américas - Chile, Evirtual - Chile)

A Virtual Enterprise is a virtual environment where participants can use management applications to improve enterprise performance. The environment emulates an organization with five positions occupied by individuals. The production operations are simulated by a model receiving the actualized data. After model runs, results are used in a balanced scorecard indicating how key performance indicators were affected with the changes made. After completing the training cycle, participants mentioned how difficult was at the beginning to be involved in order to achieve the challenge of improving profitability, but after well understood the production process, with a well communication system among them, and analyzing the key indicators, they could find the causes of low productivity and improved it. In this way, they were able to understand how strategies help to improve profitability. Considering this tool as a serious game, it is expected to reach an approach to situated learning in management field.

Read more.

Modeling Approach for Managing the Demand in Congested Airport Networks: The Case of Mexico City Airport (DIMEI, Facultad de Ingeniería; Universidad Nacional Autónoma de México and Aviation Academy, Amsterdam University of Applied Sciences)

We introduce a simulation approach to assess flight demand when airport congestion is observed. The model includes flight information, airline on-time performance and flight duration and turnaround time uncertainty. When airport congestion occurs at the arrival airport, an air traffic flow management initiative is triggered as a tool for alleviating the congestion problems, particularly in the most congested slots of the airport. Analysis of selected model scenarios allows to select the parameters of the initiative where airport congestion can be minimized. The model is set up for Mexico City airport, which is Mexico’s busiest airport and highly congested. This case study describes how to model the airport network for analysing the effectiveness of specific traffic flow management initiatives in Mexico City. The flexibility of the model makes it easy to adapt it to congested airport networks in other regions of the world.

Read more.

Optimization and Simulation of an Ambulance Location Problem (INAM)

The main Campus (Ciudad Universitaria) of the National University of Mexico (UNAM) has a population density of about 259,617 people who are attended by four ambulances and 10 technicians in medical emergencies (TME). At the present time the response time of the ambulances is, on average, from 5 to 6 min to the perimeter of the main campus. The National Fire Protection Association of USA recommends that basic life support services should arrive at the scene of an emergency within 4 minutes, while advanced life support providers should arrive within eight minutes for all TME calls. So the TME´s want to find the optimum locations for the ambulances so that they can get to the patients in the shortest possible time. For this job we used simulation and integer programming to find better ambulance locations and shorten the ambulance response time in the main Campus.

Read more.