IM521E - Discrete Event System Simulation

IM729 - Discrete Sytems Simulation

ExtendSim was introduced to the students by the instructor teaching them how to open and run models, then explaining the main tool bars and libraries used in the modelling processes. A simple model was selected and built by the instructor from scratch, then the students tried to model it themselves with assistance given by the teaching assistant, if required. A basic discrete event model tutorial from the ExtendSim User Guide (Car Wash Model) was given to the students to build step by step to teach students how to model real case studies.

Students are divided into teams to work on their projects. Each team selected a process with a problem needing to be solved through the use of simulation. Teams underwent all the simulation steps necessary to end up with a solution to their problem. Projects developed by the students were in different fields:

	Banking
	Car wash
	A small hypermarket (superstore combining a supermarket and a department store with the business model of focusing on high-volume, low-margin sales)
	Gas station
	MacDonalds Drive Thru

Some students continued their research and used ExtendSim LT for their final year projects.

A textbook that supports delivery of this course would be nice. The text should include several problem sets along the required input data.

Imagine That Inc. response: The eBook ExtendSim for Discrete Event System Simulation (included with ExtendSim LT and all full versions of ExtendSim) in conjunction with the Banks, Carson, et al. text Discrete-Event System Simulation, helps instructors more easily communicate simulation concepts and make simulation more accessible to students.

This is a simulation modeling class teaching the fundamentals of proper simulation modeling. ExtendSim was the only software we used in this course to learn and master the concepts.

Term projects demonstrating mastery of the fundamentals of good simulation modeling to 'realistic' scenarios. The modeling was done exclusively using ExtendSim.

Ability to try out all the principles of good simulation modeling. Fantastic aid to teaching manufacturing concepts as well (push vs. pull, scheduling strategies, etc.) Ease of animation makes it easy to 'grab' student's interest - but more importantly, helps me teach model validation and verification.

In my department, I had to teach myself to use ExtendSim. As such, my students are somewhat limited to my abilities and skill. Occasionally, I still struggle with 'how to do something' that I want to include in a lab exercise or term project. However, I do find the examples in the online manual very helpful. If anything, more examples for instructors would be greatly appreciated.

Yes.
MET 410 MET 510
Manufacturing Resources Management

Computer Integrated Manufacturing

Manufacturing Analysis

MBA 6610
Designing, Managing, and Improving Operations

Decision Support Systems
COM671

Supply Chain Design
DM407

It was used to develop and analyze supply chains

Each one did a final project. Some of the best were:

	Market access gateway model of stock trading system
	Traffic signaling system
	Staffing of customer service operation
	Raw material supply plan

Supply Chain Design
DM 405-01

Design of Manufacturing Systems and Processes
DM 407

In this course, students will learn the significance and ramifications of “Lean Manufacturing” practices and advantages they provide to a manufacturing company. They will learn how to analyze the cross functional processes and to understand how strategic business objectives are translated into specific actions involving facilities, equipment, new skills, and process improvements that must be achieved . Tactical planning and execution design are introduced using specific analytical techniques including:

	statistical segmentation of demand
	production and inventory considerations of facility and product design, including the impacts of variability
	use of statistical segmentation for make-to-stock, make-to-order, and make-to-plan strategies
	introduction to replenishment techniques including: level loading, rhythm cycles and considerations for safety and cycle stock
	use of postponement strategies in optimizing inventory control

Business Process Management

Simulation discussions for second half of the course uses ExtendSim as the software.

Class projects including examples and group project course.

Business Process Management

A course in the design and analysis of business process. Students will be introduced to the concept of business processes, including their cross-functional nature, design, operation, and management. Students will design, chart, and analyze processes and analyze business cases using the ExtendSim simulation software.

As part of the outcomes from the course, students will know how to communicate orally and in written format, and students will be able to critically analyze business problems from a process perspective and improve businesses through the analysis. Simulation models using ExtendSim will be developed and analyzed.

Operations Management in the Supply Chain

Discrete simulation. Layout factory planning and simulation of people productivity.

Student teams used ExtensSim to simulate processes in medical settings.

Analysis of customer flows in pharmacy setting. Analysis of patient flows in walk-in clinic settings.

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 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.

Managing Medical Services

October 22 to December 10, 2012

Providing some coherence to the Carey Business School's treatment of this subject matter, two interrelated topics will be hone in on.

	First, the course wrestles with the unique and multi-dimensional types of variability that customer involvement brings to Service settings. This includes issues such as variable arrival and processing times. Plus, it also includes several types of variability unique to services such as customer willingness to cooperate, and differing levels of customer skills and requirements.
	The second focal point is how to think analytically about problems in settings with a lot of "noisy" data.

This course teaches that one can build upon a foundation of tools such as Theory, and Discrete Event Simulation to bring order out of the apparent chaos of typical medical service settings.

Immersion Colloquium on Improving Outpatient Clinic Processes

January 20 to May 1, 2013

The chief “real world lab” for this project is a clinic in Physical Rehabilitation and Rehabilitation department of the Johns Hopkins Hospital in east Baltimore. While efforts will evolve as data and insight is gathered into actual operations, the treatment of this subject matter will be concentrated on three interrelated sets of issues. 

	Process analysis and process reengineering will be a chief focus. This is required to improve process flows and several measureable metrics such as waiting times and asset utilization.
	In addition, there will be focus on scheduling issues for the clinic that take into account factors including no-show rates, processing times, and system variance.
	Several issues in the area of inventory management will also be addressed. These issues will include consideration of reorder systems, inventory tracking, and inventory security. Some measure of yield management will be involved when considering patient scheduling.

Service Operations Management

This course offers central managerial concepts for the service operations area. The issues in service operations are addressed in both tactical and strategic levels. This course introduces some of the basic tools and models used in service operations, but focuses more on their applications, rather than on derivations or mathematical analysis. Simulation modeling using ExtendSim will be introduced.

Modeling and Simulation for Logistics Planning

This course was developed to follow current trends in the job market. It focuses on achieving operational and strategic business excellence through the design and improvement of an organization’s processes with particular attention to the resource function. Topics covered include:

	principles of business process design
	workflow design tools
	modeling and simulation of business processes
	measurement of business process performance and process benchmarking
	management and support of business processes

At the completion of this course, students will be able to:

	identify the key processes in an organization
	align processes with market-driven organizational strategies
	diagram the flow of activities in the key processes of an organization
	identify the processes which are candidates for redesign
	manage process flows
	Model and simulate business processes; measure business process performance
	Be able to identify the proper members of a process management team

For the complete course syllabus, click here.

In this course the fundamentals of discrete event simulation are discussed. The tables below identify the concepts learned in each course. The application used to learn these concepts is Bank teller scheduling. Topics learned in MGT4233:

	Common Random Number Distributions
	Use of Random Number Generators
	Managing Random Number Seeds
	Sending Items and Information through a simulation
	Modeling: Use of multiple trials Queuing Systems Labor Schedules Changing Arrival rates Trial & Error Search for good solutions
	Basic Building Blocks: Create Items Queues (FIFO, Renege) Activities Plotters Routers Decisions Statistics (Queue, Activities, Cost)
	Using Named Connections
	Cloning inputs and outputs
	Exporting results to Excel

Bank Teller Scheduling courseLearningCurve: Reasonable, give the richness of the software's capabilities and our limited time

Visualization of dynamic system operations

Not really

Yes, same course

This course focused on analyzing management decisions that involved uncertainty, risk, and complexity with a strong emphasis on applications and on the use of appropriate decision analysis techniques and software tools. Students did in-class assignments and homework using ExtendSim and one or more small-team projects that utilized the tools and techniques covered in class.

	Common Random Number Distributions
	Use of Random Number Generators
	Managing Random Number Seeds
	Sending Items and Information through a simulation
	Modeling: Use of Confidence Intervals Effect of multiple trials Queuing Systems Labor Schedules Changing Arrival rates Set Up Times/costs Cycle Time
	Transient Effects and How to deal with them
	Terminating and Non-Terminating Systems
	Trial & Error Search for good (best?) solutions
	Use of an Optimizer for Automated Search & Confirming "Optimal" Solution
	Use of Attributes / Properties
	Basic Building Blocks: Create Items Queues (FIFO, Renege, Resource) Activities Plotters Routers Decisions Statistics (Queue, Activities, Cost)
	Using Hierarchical Blocks
	Using Named Connections
	Cloning inputs and outputs
	Exporting results to Excel

ExtendSim was used in group model building sessions for finance modelling and simulation.

	Common Random Number Distributions
	Use of Random Number Generators
	Managing Random Number Seeds
	Sending Items and Information through a simulation
	Modeling: Effect of multiple trials Queuing Systems Labor Schedules Changing Arrival rates
	Trial & Error Search for good (best?) solutions
	Basic Building Blocks: Create Items Queues (FIFO, Reneg) Activities Plotters Routers Decisions Statistics (Queue, Activities, Cost)
	Using Named Connections
	Cloning inputs and outputs
	Exporting results to Excel

This course will focus on analyzing management decisions that involve uncertainty, risk, and complexity. There will be a strong emphasis on applications and on the use of appropriate decision analysis techniques and software tools. The analytical methods to be studied will include Systems Simulation, Monte Carlo Simulation, Forecasting and Decision Trees. ExtendSim is one of the packages that will be used to analyze decision problems in these areas. Class exercises and cases will be used by the instructor to provide a hands-on approach to learning how to use the software. Students will do in-class assignments and homework using the software, and one or more small-team projects that utilize the tools and techniques covered in class.

Logistics Project Work Simulation

10 Student groups with 8 students in each group solved a logistics planning problem with the help of a simulation study with ExtendSim.

Modeling and Simulation for Logistics Planning

To show the 3 simulation paradigms and its use for different logistics planning tasks. course

Development of small models for logistics planning tasks.

Within the bachelor course “Logistics project work simulation”, ExtendSim was used by about 80 students. ExtendSim was available on 31 work stations in the computer lab and the students had access to these computers 24 hours a day, 7 days a week. In addition, three teachers had a fully featured license on their computers. All students had a basic knowledge in the area of simulations, based on at least one introductory course in discrete event, as well as in continuous simulation concepts. Furthermore, all students were familiar with general statistical and analytic methods. The targets of learning in the course can be summarized in the following:

	Processing an own simulation project within a group of 8 students.
	Specialized knowledge in logistics, modeling and simulation, theory of probability and statistics, project management and problem solving, data collection and analysis.
	Comprehension of dynamic logistics phenomena, identification of possibilities and understanding of algorithms to generate stochastically data.
	Knowledge about the processes of simulation.
	Training of skills in innovations: Generation of variants, planning of experiments.

The topics of the simulation projects were:

	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.

Aside from this course, ExtendSim was used in “Modeling of logistics networks” as a master course, with about 10 students. ExtendSim was utilized to show simulation techniques and real-world examples. The students also had access to the computer lab, described above, and could train their simulation skills. The basic contents of this course were:

	Basic knowledge of simulation: definitions, models of material flows, classes of logistics resources and objects, flow diagram, graph and matrixes, funnel model and waiting queue model
	Description and valuation quantities for logistics processes
	Introduction of simulation tool: ExtendSim
	Introduction of planning tool: 4flow vista
	Planning and implementation of experiments
	Presentation and analysis of results
	Development of models
	Preparation and implementation of simulation models
	Visualization of results
	SCOR model, ARIS model and process chain model

All students in this course had a good knowledge of simulation and were trained in different simulation studies.

Based on the topics of the lectures and topics of the simulation projects, the students used the discrete-event-oriented part of ExtendSim. The following libraries were relevant to processing the projects:

	Item Library (e.g., Create, Get, Information, …)
	Value Library (e.g., Constant, Equation, Display Value, …)

Besides libraries, functions like the internal ExtendSim databases were used, as well as the possibility of linking data to Microsoft Excel documents.

Very valuable were the items for storing data and processing data transformation/manipulation. Furthermore, the object “Equation” was frequently used to perform analysis and to prevent the usage of other graphical items.

The manual is too extensive for short-term projects or projects of limited scope. An introduction to the manual, which explains the appropriate utilization would be beneficial at this point. It would provide help to those users who are not familiar with simulation but want to gain a quick insight into ExtendSim.

The deployment of ExtendSim uncovered the following problems:

	References of database variables to tables are very complicated
	Selected variables in “Equation-Blocks” are hardly customizable
	Positioning and relocation of blocks: single connector lines remain in the original position after relocation
	C++ programming, especially with regard to the compiler: compiler does not provide the position of code errors

ExtendSim was used within three classes at the Masters level as described below.

Within the class "Logistics Project Work Planning", ExtendSim was used by 6 students. ExtendSim was available on 31 work stations in the computer lab and the students had access to these computers 24 hours a day, 7 days a week. In addition,
two teachers had a fully featured license on their computers. All students had a basic knowledge in the area of simulations, based on at least two introductory courses in discrete event, as well as in continuous simulation concepts. Furthermore, all
students were familiar with general statistical and analytic methods. The targets of learning in the course can be summarized in the following:

	Specialized knowledge in logistics, modeling and simulation, theory of probability and statistics, project management and problem solving, data collection and analysis.
	Comprehension of dynamic logistics phenomena, identification of possibilities and understanding of algorithms to stochastically generate data.
	Knowledge about the processes of simulation.

The task for the simulation project was the simulation based dimensioning of a logistics center: "Finished goods are delivered from different production sites to a logistics center. In this center, the products will be consolidated, stored, picked, packed, and shipped. A logistics planner has been assigned the task to determine the correct dimensions for the distinct areas of the logistics center. Furthermore, he is supposed to calculate the required resources such as forklifts or picking staff to ensure seamless operations. The planner has already recorded data and processes and has begun to develop a conceptual model for simulation. The planner, however, has unexpectedly left the company and is no longer available. It would be your job to take over his tasks. As of now, there is only the data of your predecessor available. Further, more detailed data will be provided."

Furthermore, ExtendSim was used in the class "Model Based Analysis of Logistics Networks" with about 20 students. ExtendSim was utilized to show simulation techniques and real-world examples. The students also had access to the
computer lab, described above, and could train their simulation skills. The basic contents of this course were:

	Introduction of simulation tool: ExtendSim
	Presentation and analysis of results
	Visualization of results

All students in this course had a good knowledge of simulation and were trained in different simulation studies.

Finally, ExtendSim was used in the class "Application of Logistics Simulation" with 5 students. ExtendSim was utilized to show simulation techniques and real-world examples. The basic contents of this course were:

	Introduction of simulation tool: ExtendSim
	Presentation and analysis of results
	Visualization of results

All students in this course had a good knowledge of simulation and were trained in different simulation studies.

Based on the topics of the lectures and topics of the simulation projects, the students used the discrete-event-oriented part of ExtendSim. The following libraries were
relevant to processing the projects:

	Item Library (e.g., Create, Get, Information, …)
	Value Library (e.g., Constant, Equation, Display Value, …)

Besides libraries, functions like the internal ExtendSim databases were used, as well as the possibility of linking data to Microsoft Excel documents.

The main advantages which could be seen were the simple and fast training period and the intuitive usage of almost all objects. Very valuable were the items for storing data and processing data transformation/manipulation. Furthermore, the object "Equation" was frequently used to perform analysis and to prevent the usage of other graphical items.

The ExtendSim manual can be used to read more about specific items and objects and is very extensive. Nonetheless, the structure is non-redundant and that makes it difficult, especially for non-native English speakers, to understand every detail. That led to problems in understanding all the configuration possibilities of blocks and to additional training support.

In addition, the great possibility to model almost everything in a graphical way makes it difficult for beginners to structure their models in a clean way.

Within the bachelor course “Logistics project work simulation” (Bachelor level course taught in Winter 2010-11) ExtendSim was used by about 100 students. ExtendSim was available on 31 work stations in the computer lab and the students had access to these computers 24 hours a day, 7 days a week. In addition, three teachers had a fully featured license on their computers. All students had a basic knowledge in the area of simulations, based on at least two introductory courses in discrete event, as well as in continuous simulation concepts. Furthermore, all students were familiar with general statistical and analytic methods. The targets of learning in the course can be summarized in the following:

	Processing an own simulation project within a group of 8 students.
	Specialized knowledge in logistics, modeling and simulation, theory of probability and statistics, project management and problem solving, data collection and analysis.
	Comprehension of dynamic logistics phenomena, identification of possibilities and understanding of algorithms to generate stochastically data.
	Knowledge about the processes of simulation.
	Training of skills in innovations: Generation of variants, planning of experiments.

The resulting simulation projects, meaning the ExtendSim models, will be available for download soon. The topics of the simulation projects were:

	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.

Aside from this course, ExtendSim was used in “Modeling of logistics networks” (a Master level course taught in Winter 2010-11) by about 30 students. ExtendSim was utilized to show simulation techniques and real-world examples. The students also had access to the computer lab, described above, and could train their simulation skills. The basic contents of this course were:

	Basic knowledge of simulation: definitions, models of material flows, classes of logistics resources and objects, flow diagram, graph and matrixes, funnel model and waiting queue model
	Description and valuation quantities for logistics processes
	Introduction of simulation tool: ExtendSim
	Introduction of planning tool: 4flow vista
	Planning and implementation of experiments
	Presentation and analysis of results
	Development of models
	Preparation and implementation of simulation models
	Visualization of results
	SCOR model, ARIS model and process chain model

All students in this course had a good knowledge of simulation and were trained in different simulation studies.

Based on the topics of the lectures and topics of the simulation projects, the students used the discrete-event-oriented part of ExtendSim. The following libraries were relevant to processing the projects:

	Item Library (e.g., Create, Get, Information, …)
	Value Library (e.g., Constant, Equation, Display Value, …)

Besides libraries, functions like the internal ExtendSim databases were used, as well as the possibility of linking data to Microsoft Excel documents.

The main advantages which could be seen were the simple and fast training period and the intuitive usage of almost all objects. Very valuable were the items for storing data and processing data transformation/manipulation. Furthermore, the object “Equation” was frequently used to perform analysis and to prevent the usage of other graphical items.

The ExtendSim manual can be used to read more about specific items and objects and is very extensive. Nonetheless, the structure is non-redundant and that makes it difficult, especially for non-native English speakers, to understand every detail. That led to problems in understanding all the configuration possibilities of blocks and to additional training support.

In addition, the great possibility to model almost everything in a graphical way makes it difficult for beginners to structure their models in a clean way.

ExtendSim was used to help students development modeling and process design skills and to support quantitative analysis of models.

Each student was required to prepare a semester long project and present it to the class.

Excellent and intuitive GUI.

Possible general support models targeted at MBA students.

Yes, but term unknown.

Operations Management for MBAs
MGNT 624

Business Process Design and Analysis

ExtendSim LT was used as the primary tool for modeling business processes in this course. Students first learned how to evaluate and describe business processses, then learned about the nature of simulation in general. ExtendSim was then introduced as a structured tool to perform complex and elegant simulations. Students develop an intemediate understanding of ExtendSim using concepts ranging from basic modeling to use of resources, multiple queue disciplines (including balking) along with setting and using attribute values and data collection and analysis.

Students completed five projects using ExtendSim. These began with a simple process and culminated in a project which required an intemediate level of understanding of ExtendSim.

Applied Business Intelligence

The course DSS 430 is an undergraduate version of the DSS 650. The content and syllabus remain the same, but this course is offered to particularly promising undergraduates.

The course ran during the months of July and August. It was a graduate course of all online students. I was able to incorporate aspects of the User Guide (a really nice document, by the way) along with my own examples into the class. I'm happy to report that there were no instances in which Extendsim displayed bugs. In addition, I got a number of quite favorable comments about the capabilities of the software. Several students expressed an interest in using the software in their jobs as well.

A you have moved forward in versions of Extendsim, you have made some great changes. I first used version 6 and found it to be somewhat cumbersome as did my students. Version 8 has put an end to all of this. I truly enjoy using and teaching this software.  It is definitely a challenge for the less logical/quantitative students, but an incredibly valuable learning tool in all cases.

For the fall semester, we are rolling out the use of the network version.

Applied Business Intelligence

Using Laguna and Marklund text Business Process Modeling, Simulation and Design in conjunction with ExtendSim, this course combines perspectives of business along with industrial and systems engineering to create a broad, quantitative modeling approach.

The main objective of this course is to provide students with an understanding of the many analytical tools that can be used to model, analyze, understand, and ultimately design business process.  Discrete event simulation is among the most powerful of these tools.

Four sections of this graduate course are offered annually, reaching approximately 80 students. The course is in its third year.

Students were given the option to use Extend 6 (provided with the Laguna/Marklund text) or ExtendSim 8 as provided through the ExtendSim Adopter program. 

At the start of the semester, solutions to problems from the book were created in ExtendSim 8 giving Dr. Miori the opportunity to fully examine the capabilities and improvements in version 8. I was generally very pleased. ... I also referenced the User Guide extensively and found it to be complete and helpful.

Students found ExtendSim 8 to be much more direct and logical than Extend 6. Teaching ExtendSim 8 was found to be much easier. Dr. Miori has used a number of different complex simulation languages in the past and feels that ExtendSim certainly is a very solid and useful language.

Students all felt that this was a great product to learn and it assisted them in fully understanding process mapping and subsequent simulation/what-if analysis.

Advanced Topics - Modeling and Simulation
(undergrad and graduate cross-listed)
COM 671

In the Fall 2011 semester, Prof. Fink used ExtendSim in the Modeling and Simulation class which is offered every couple of years. The course is designed to cover four major areas of modeling, including physical modeling, process modeling, intelligent agent modeling, and 3-D visual modeling. These areas are central to the course as the course is part of a concentration in computer gaming. ExtendSim is taught and used explicitly for the process modeling component of the course, though the students are also allowed to use it in the intelligent agent modeling portion if they so chose. The course is cross-listed as an undergraduate and graduate level course.

In the Fall of 2011, 8 students enrolled in the course: 4 undegrads and 4 graduates. Undergrads were allowed to work in pairs if they so chose, so a total of 7 projects were generated in the course using ExtendSim. In order to get the knowledge needed on a process to model, it was suggested that students go to the Science Channel's Web site "How It's Made", so the subjects selected almost all had to do with manufacturing, though one model had to do with how a device functions. For further details, click here to see the actual assignment. The following were the areas modeled by the students:

	How a speaker works
	Manufacture of a pocket knife
	Manufacture of a baseball
	Manufacture of an 1873 model Colt
	Manufacture of an ice cream cone
	Manufacture of a fireman's helmet
	Manufacture of a CRT

There was quite a diverse set of areas chosen by the students and, based on their subject area, each used different libraries. One studetn even created a few blocks for her own library. Most also used the hierarchical capability of the tool, and several used the graphical user interface capabilities.

Analysis and Design of Operations

This year one MBA course provides an overview of the productive system for products and services, focusing on process characteristics and techniques used for process management.

	Process Line Balancing
	Queue management
	Inventory Management

Operations Management

Simulacion

Computer Simulation Systems

Introduction to modeling and simulation

	Introduction to modeling: Concept model and its applications.
	Systems: concept, types and their main characteristics.
	Simulation: general definitions and terminology used.

Review of Statistical concepts

	Probability Distributions: main features, what they indicate?, When to use each.
	Data Collection: sources of obtaining information, fitting a probability distribution of input data. Selection of probability distributions of input data. Goodness of fit tests: Chi-square, KS and Media squared errors.

Simulation perspective

	The general character of the simulation: The simulation clock. Scope of the simulation.
	The importance of simulation in operations research, programming and resource allocation, manufacturing and quality.
	Simulation versus other alternatives.
	Advantages and disadvantages of simulation.
	Steps in a simulation study.
	Advantages and disadvantages of existing simulation programs.

Modeling basics

Basic concepts of modeling and simulation: entities, creation, movement, wait command, attributes, processes and destruction. The nature of the movement of transactions.

Basic operating model

	Model a system with a single workstation.
	Creating sets of blocks.
	Introduction to the model entities.
	Place of waiting entities.
	Allocating resources to entities.
	Indicators of time delays.
	Releasing resources.
	Counting events.
	Destruction of entities.
	Initial set of experimental items: Describing the simulation project. Controlling the number of entities. Describing the ranks, resources and accountants: the elements QUEUE, RESOURCE and COUNTER. Controlling the number of replicas.

Model Verification and validation

	Verifying and validating the model: Performing test runs. Monitoring the operation of the model.
	Checking and correcting errors. Using animation as a tool for verification.
	Validating the model structure and data. Testing the model performance.
	Building confidence intervals.
	Calculation of the number of runs necessary to ensure the accuracy of the results.
	Analysis of the results for strict and not strict systems.

Evaluating different alternatives

	Variance Reduction Techniques.
	Using design of experiments to evaluate different alternatives.
	Selection of the performance measure to evaluate.
	Definition and use of seeds to make separate runs.
	Application of factorial’s fractional designs for simulations with many runs.

20

Business Process Reengineering
MAT 09

Dati Reti e Sistem
SECS-S01

Managerial Control ("Operatives Controlling")

Business training has been shaped by sound skills in the areas of cost accounting and financial statements. This course aims to expand upon skills learned in the "Cost and performance accounting" and "Financial Accounting" courses. The course will not only include those concepts but other that are already established and proven in the German academic and practical fields. This course introduces students to System Dynamics. Using bio-cybernetic intelligence discipline enables managers to create more goal-oriented companies.

The Universität Duisburg-Essen has been a long time ExtendSim user using ExtendSim for many courses throughout the years, case study seminars, and for Bachelor and Master Theses.

Bioprocess Systems Engineering

OM 422 B1/OM 622 B1
Simulation and Computer Modeling Techniques in Management

Civil 792: Discrete Event Simulation in Construction

Giving tutorials and developing assignments and projects by the students

12 course

Simulation for Designing and Planning Construction Operations

To design and plan construction operations by means of probabilistic or stochastic simulation. At the end of the course, the student should:

	Graphically represent construction operations using discrete-event simulation software.
	Build computer simulations (models) of construction operations and verify its operation be as close as possible to reality.
	Explain the model and apply statistical validation techniques.
	Model the uncertainty related to construction operations in terms of dynamic relationships and durations.
	Understand and interpret the outcomes of a simulation model and describe them in terms of statistical parameters.
	Apply different experimental design techniques to effectively use simulation models.
	Develop a modeling and simulation project from start to finish.

BUAD 449 emphasizes structuring of operations management (OM) problems to facilitate improvement of business processes. Topics include design (or redesign) of customer service processes, focusing on cycle time reduction, design of manufacturing, service, and logistics processes, emphasizing lead time reduction and the use of technology to support design activities.

The final project will involve the use of ExtendSim to simulate an existing business process. Working in teams, changes to a system will be suggested and performance of the modified process with status quo to determine the extent of changes that have been realized will be compared.

CIS 151 - Intro to Information Systems

CIS 454 - Business Intelligence

Service Operations Management

ExtendSim was a central part of the course. The simulation package fit 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
	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)

What is most enlightening is the list of homework assignments related to ExtendSim.

Training materials
I was greatly aided by Robin Clark who shared power point slides which provided a quick and useful introduction to using ExtendSim. He also was very helfpful to me in learning some of the more obscure features of the package.

I helped my students learn ExtendSim by making a series of video tutorials which I posted on the class website. The tutorials were each about 10-20 minutes long and focused on an increasingly complex set of modeling skills. In all I made 6 tutorials. The students really liked "seeing how it was done" I made sure to pace them slowly enough so that the features of ExtendSim could be absorbed. I used the Macintosh software called "Screenflow" to capture the ExtendSim screen and provided verbal narration.

Course syllabus & assignments
Download the syllabus of the class which shows the sequence of topics taught and specifically how ExtendSim was used.

Service Operations Management

The service sector dominates the economies of most developed nations. Worldwide, services account for 64% of GDP and 40% of employment, and in the United States the service sector accounts for 76% of GDP and 85% of employment. In addition to the "pure" service sector, the delivery and support of many goods involves a significant service component. The challenges involved in managing services have been complicated by globalization, for many services are now delivered by service supply chains that involve multiple firms and cross national boundaries.

In this class students will develop both quantitative tools and qualitative models in ExtendSim that will help to manage in this complex environment. The class focuses on four topics: (i) managing variability in services, (ii) the operations/marketing interface, (iii) demand and revenue management and (iv) process improvement in services.

I would like to report on my use of the simulation package in my MBA course: OMG 412: Service Operations Management in the Fall 2010. This is a second year elective course taken by about 20 students.

The ExtendSim simulation package was a central part of the course. I attach a syllabus of the class which shows sequence to topics taught, and specifically how I used ExtendSim.

The software fit 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
	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)

What is most enlightening is the list of homework assignments related to ExtendSim.

Training materials
I was greatly aided by Robin Clark who shared power point slides which provided a quick and useful introduction to using ExtendSim. He also was very helfpful to me in learning some of the more obscure features of the package.

I helped my students learn ExtendSim by making a series of video tutorials which I posted on the class website. The tutorials were each about 10-20 minutes long and focused on an increasingly complex set of modeling skills. In all I made 6 tutorials. The
students really liked "seeing how it was done" I made sure to pace them slowly enough so that the features of ExtendSim could be absorbed. I used the Macintosh software called "Screenflow" to capture the ExtendSim screen and provided verbal narration.

Service Operations Management

Similar to Fall 2011 and 2010.

IOM-677 - Dynamic Programming and Markov Decision Processes

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.

IOM 674 - Queueing and Stochastic Networks

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.

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.

Simulation of Business Processes

The course was an introduction to discrete event simulation. Goal of the course was to learn the basic concepts of discrete event simulation then apply them to practical problems. ExtendSim is used as the tool for these applications.

The first four weeks of this course was used for a technical introduction to ExtendSim (libraries: Item, Value, Plotter). For the rest of the course, ExtendSim was used as the workhorse for many applications and exercises that are built around the conceptual concepts taught.

Each week, the students are divided into teams of two or three students who complete a short simulation project. The projects included:

	Backoffice of an insurance company
	Job shop manufacturing
	Scheduling rules
	Auto repair facility
	Buffer optimization in a Kanban system

After the course, students were able to create quite elaborate models and use most of the functionality of ExtendSim.

It was very easy to work with the program from the first week on. No big problems arose from the technical side. The main problems that students have when learning to build simulation models are conceptual problems: how to model specific situation of reality? This is not that much related to the tool itself, but rather to thinking in the structures of DE simulation.

A very good aspect of ExtendSim is that the many blocks in the Item library are rather generic in the sense that they represent a typical DE structure (queue, activity, …) in a clear and simple way, without too much fancy distractions around. This helps students to learn thinking in clear concepts.

The blocks that allow modeling of logic by means of code are great for putting into consideration more complex situations, and going from simple to complex models without losing the conceptual clarity.

The use of a simulation tool is a necessity when teaching simulation and modeling. I have not much experience with other tools, but I feel that ExtendSim is very well suited to teach simulation contexts.

Please provide a Mac version that supports the latest OS version.

Simulation in Retail and Logistics

ExtendSim was introduced by a basic course in ExtendSim functionality (item and value library). As running example, we used a blood donation center. Students had the software on their laptops and made exercises. Mixed into the ExtendSim exercises, basic concepts of discrete event simulation were taught. A theoretical block on how to interpret results of stochastic simulations was complemented with ExtendSim exercises.

During the course, students worked with different models, including a skilift and a manufacturing scheduling problem.

The course was a compact course over 2.5 days. The goal of the course was not to make the students professional simulation experts but rather to give them a hands-on experience about what is possible with simulation and how the general approach in modeling works.

During the course, running examples constituted sort of a “small project” framework where students could experience the progress of a simulation project together with learning the concepts.

Two students used ExtendSim for their master thesis where they created a model by their own, without technical assistance from professor.

Due to the simple drag & drop facilities in ExtendSim, it was easy for the students to get the basic knowledge for building their own simple models. Given the short time for this course, it was exciting to see how well the two students did who chose to use ExtendSim for their master thesis.

For this course, the best aspect of ExtendSim is the option of putting models together by dragging & dropping blocks from libraries, without the need of programming. Thus, students with little or no programming experience are enabled to use such a tool and get a feeling for simulation.

Compared to talking about simulation and the use of simulation for solving problems without the use of a simulation tool, it is much more effective to have a tool at hand that students can play with and thus gain own experiences.

It would help to have an option to use ExtendSim without the need of installing the software locally. Maybe some cloud computing option.