Whirlpool and The University of Michigan Collaborate on a Simulation Project Using ProModel Software

Embarking on a simulation project can seem like a daunting task at times, especially if the project must be completed above and beyond one’s normal responsibilities.  During those times, it is beneficial to consider engaging a partner to help.

Of course ProModel provides professional model building and consulting services, but another alternative is to partner with a University that teaches ProModel, MedModel or Process Simulator.  This type of industry | academia collaboration is a win-win for both organizations.

Please check out this very successful simulation project by Whirlpool on which they partnered with the University of Michigan. The article was published in PlantServices.com.

Click here to see a list of colleges and universities using ProModel software products.  If you would like more information about our academic program, please contact us at education@promodel.com or 801-223-4601.

 

 

Get Ready for Fall Semester. Now is the Time to Add Simulation to your Curriculum!

Chrsitne Bunker Linked In

Christine Bunker Academic Program Director

Teaching simulation to your students will give them a head start when they reach industry. Learn some of the benefits of including simulation as you teach techniques for process improvement.

  • Accurate Depiction of Reality
  • Insightful System Evaluations
  • Dynamics for Predictive Analysis
  • Understand Interdependencies
  • Better Experimentation and Data
  • Animated Visualization
  • Advanced Optimization Techniques
  • Bottom Line Savings (Hard Dollar, Soft Dollar, and Labor Savings along with many Intangible Benefits)

For more details on any of these topics visit Justifying Simulation to understand the benefits of simulation.

Learn More about the ProModel Academic Program

To learn more about the academic program, please visit our website or review the ProModel Academic Overview.

If you’re interested in joining the growing ranks of ProModel educators or have any questions, please contact us at education@promodel.com to apply for a full professional license for academic use.

From Reality to Model

Adjunct Prof Mark Klee Headshot

Mark Klee; Adjunct Professor – Eastern Kentucky University

I know what you are thinking “From Reality to Model” shouldn’t that be the other way around? As an engineer at Toyota for the past 24 years I often encounter manufacturing processes that have slowly de-optimized. And now, just by walking by the processes on the floor, I can see waste (motion, waiting, over-processing). I know this means that the these processes need some work.

Our typical method of improving these processes would be to employ the traditional Toyota Production System tools. We begin with observation and time study. Then we use video for motion analysis making these processes visual on paper with standardized work combination tables, standardized work charts, and production capacity calculations. Through these simple analysis tools, the waste in the process becomes more obvious and begins to generate ideas for improvement.

This is typically done one process or one zone of processes at at time. It is also usually done with paper, pencil, and stopwatch. The methods have proven time and again to be effective for process improvement and an effective method of developing engineers as well as manufacturing floor members in process improvement.

After the waste is discovered and the improvement ideas generated it is time to try some improvement ideas. The process visualization and capacity calculation documents are then modified to simulate the improvement idea. Then it is time to try the modified process on the production floor. The concept is tested in a controlled environment. After success is documented, the process standards are modified the team is trained to the new standard.

Using ProModel works very well with the Toyota Production System and as a method for developing manufacturing engineers, manufacturing floor members and students in manufacturing focused curriculum. In Eastern Kentucky University’s Applied Engineering and Management class, we follow this progression.

  • We first focus on learning process observation and visualization skill using the standard Toyota Production System tools.
  • Next we learn the processes of implementing controlled change in a mass production environment. We learn and practice these skills on the manufacturing floor to gain real world experience.
  • After learning the basics of observation and improvement, we come back to the classroom where we employ ProModel to fine tune our processes and learn if there are any opportunities for optimization that may have been overlooked.
  • With ProModel we can also test scenarios that may be difficult to test on the actual production floor like moving a piece of equipment, modifying a cycle time, changing a conveyor length or changing a delivery frequency.
  • These trials can be done as quickly as you can change the numbers in the model allowing for many more cycles of trial and error or trial and success in a shorter time.

As a result of the course and ProModel, students have deeper understanding of both the theory and application of process improvement allowing them to be an instant contributor to a manufacturing organization upon their graduation.

In the end, deeply understanding the current reality through observation, documentation, and modification of the current process helps us make a more accurate model. The result of the more accurate model is further optimization. This deepens learning and the improvement cycle continues.

Brief Bio:

Mark Klee, BS Eastern Kentucky University 1990, MS Purdue University 1992
Toyota Motor Manufacturing Kentucky 1994-Present
Eastern Kentucky University Adjunct Faculty 2012-Present

Real-World Simulation Examples for Student Learning

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Prof Hassan Rajaei Ph.D. – Bowling Green State University; Department of Computer Science

Objectives

Simulation is a powerful tool for teaching students about the techniques as well as providing deeper understanding of courses such as networking, operating systems, operational research, just to name a few. Simulation is a well-known technique for evaluating what-if scenarios and decision making in industry, defense, finance, and many others. Students quickly realize these values and want to learn how to master this technique.

Teaching simulation techniques often requires attractive problem assignments. Real-world has numerous examples that excite students to study and motivate them focusing on their learning objectives. Further, it challenges them to develop models to reflect the reality. Clear examples can teach students how to collect data, develop the base model, improve it to advanced models, analyze the obtained results, and think about the usability of their simulation results. These learning outcomes can clearly demonstrate valuable educational objectives.

A simulation tool like ProModel has numerous example models in its library, but the educational objectives can be best achieved through step-by-step experimental development of useful samples. ProModel can be a great help by exploring the details of similar examples.

This article, presents an example where a group of students developed a simulation model for the Bowling Green State University (BGSU) Students Union Cafeteria. Managing a university dining hall often exhibits challenges for the food services located in it. This study focused on reducing the average waiting time of the diners, while increasing overall efficiency of the services.

Simulating the Nest Cafeteria

This project focused on finding solutions for the Falcon’s Nest Cafeteria to increase the efficiency and decrease the average time of the customer spent in the system.

Overview of the Nest: Students cafeteria at BGSU functions as an important part of the University’s dining service. This cafeteria serves thousands of students every day. During the rush-hours of lunch and dinner, this place gets really congested with long queues contributing to long waiting times. In this simulation, the Nest model consists of five main components: Customers, Servers, Locations, Queues, and Cashiers.

Using ProModel: This tool was selected for multiple reasons: a) the availability; b) the course used the tool and trained students; c) the tool supports discrete-event systems; d) large number of library models; e) statistical analysis and output results; f) animations.

Problems Encountered: The main problem faced was lack of statistics and accurate information. Other barriers included project time limit and lack of deeper familiarity of ProModel.

Possible Solutions: Based on primary analysis, two potential solutions were feasible:

1) Increase the attractiveness of other food stations which have lower waiting time;

2) Increase number of food servers.

Three approaches to reach the goals:

a) Ask the SME to provide all data and statistics;

b) Make a very detailed model over the actual system;

c) Combination of (a) & (b) methods.

Approach c was adopted for the study.

Simulation Models

Four models were developed: 1) base, 2) intermediate, 3) advanced, 4) final

Base Model: The base model had very basic setups with one food station and one cashier. The objective was to test the station service and the customers’ arrival, and their flow in the system.

Intermediate Model: All food stations were added according to the Nest along with the logic for entities to move through the system with a shared queue.

 Advanced Model: The advanced model includes all queues targeting to obtain realistic statistics using several scenarios (Figure 1).

Figure 1

Figure 1:  The Advanced Model improved from the intermediate one

Final Model: After developing three scenarios, obtaining good confidence, making sure they were on the right track, students moved towards developing the final model shown in Figure 2. It was implemented using a time schedule to simulate the rush hour and normal operating hours.

Figure 2

Figure 2:  Final simulation model for the Falcon’s Nest Cafeteria

Results and Analysis

In this simulation, students first aimed to find an ideal solution to demonstrate how to reduce the waiting time. It turned out that such a scenario would need more implementation time. Instead, students focused on two solutions:

1) To make other food stations more attractive;

2) Adding additional workers to the top three food stations. Test cases were developed for each solution.

The result shown in Figure 3 demonstrate a reduction in the average time compared to the baseline, except Case 3. The figure suggests an 11.1% decrease in average time spent in the Nest.

Figure 3

Figure 3: Solution 1 demonstrating reduction of Average Time in the system

Next method focused on improving the waiting time by adding food runners to 3 populated stations. This method was simulated and tested with 4 scenarios, and was compared with the baseline.

Figure 4

Figure 4: Solution 2, advocating one additional worker at each food station

As was expected, by adding a food-runner to each station the average time of the customers would decrease, however, certain stations would benefit most. If case 4 is adopted, there would be a 12.6% reduction in time spent by customers. If only 1 food runner is added, then the result yields only to 6.1% decrease in average time spent in the system by customers.

Concluding Remarks

This article presents an example of a real-world case study conducted by a group of students as a term project in a simulation techniques course shared by senior undergraduate students as well as graduate students. An important result of this study demonstrates how deeply the students were engaged in their learning objectives of the course. In a short period of time, they conducted a complete case study including: observation, gathering data, analyzing the problem at hand, developing models, confirming with the subject matter expert, documenting, and delivering the results. The full article is published in ASEE 2017 Annual Conference.

Professor Hassan Rajaei Ph.D.  

Hassan Rajaei is a Professor of Computer Science at Bowling Green State University, Ohio.  His research interests include Distributed Systems & IoT, Cloud Computing, High Performance Computing (HPC), Computer Simulation, Distributed Simulation, with applications focus on communications & wireless networks. Dr. Rajaei has been active in simulation conferences (e.g. SCS SprintSim, WSC) as organizer as well as research contributor. Dr. Rajaei received his Ph.D. from Royal Institute of Technologies, KTH, Stockholm, Sweden and he holds a MSEE from Univ. of Utah.

ProModel/MedModel 2018 What’s New Webinar

2018 What's New Header

We will be conducting a live ProModel / MedModel 2018 Release Webinar on Wed Nov 15 from 1-2 pm ET.

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The webinar will give you a look at the updated look and feel of the application’s more modern, fluent user interface that provides more ease and control of your model building experience. This significant version will include such features as a Ribbon Toolbar, Docking Windows, and Right-Click Context Menus as described below:

  • Ribbon Toolbar: The traditional menus and toolbars are being replaced with a fluent Ribbon toolbar like you find in Microsoft Office applications. The new Ribbon will make it easier to access the various modules and features within the application and better facilitate touch screen and high-resolution devices.

Ribbon Toobar screen shot

  • Docking Windows: Windows will be docked within the new workspace interface, which means that when you adjust the size of one window, the others automatically resize accordingly. Say goodbye to overlapping windows. You will also be able to stack windows on top of each other and quickly access them from their respective tab thus saving valuable view space.

Dock Screen Shot

  • Right-Click Context Menus:  Context menus will be available in every table and accessible by right-clicking in any field within that table. For example, you will be able to quickly delete, insert or move a record with a simple right-click of the mouse.

Right Click Screen Shot

Join the webinar to hear all about what’s new in the ProModel / MedModel 2018 Release on Wed Nov 15 from 1-2 pm ET.

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Ancillary Tools Helpful for a Successful ProModel Discrete Event Simulation Project

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Prof. Scott Metlen Univ. of Idaho

Introduction

Using ProModel to teach process management inadvertently necessitates that students become more proficient with many tools centered on data and working with people. Of course, students learn many aspects of ProModel such as the need to understand parts of a process; these include locations, entities, arrival rates, process logic (LEAP), variables, and attributes.

They also learn about graphics, Statfit, batch/group, create, order, wait until, logic statements that operationalize business rules, and many other commands that help to model a process. However, when conducting a successful large process improvement project using discrete event simulation for an organization, students need to become proficient with many other tools to best utilize ProModel over the course of semester long projects.

Project Management Methodology

Understanding and being able to set up a project using project management methodology is critical to having a successful ProModel project. As in any project the scope and expected outcomes need to be delineated. To design the work break down structure for the project it is also critical to understand what tasks need to be accomplished to produce the final output, and when those tasks need to be completed.

Tasks include developing the scope and expected outcomes working with the project sponsor, analyzing and preparing data for entry into ProModel, base model construction, verification and validation of the base model, determining what treated models to build, statistical analysis of the outputs from each model relative to the base model, cost/benefit analysis, and a report delineating findings and recommendations. Each team in the class I guide has to complete a Project Execution Plan (PEP) and then discuss in their final paper how well they met their time gates, why they did or did not meet those dates, and what they did to catch up if they did not meet those time lines. There are times in the project where they learn the lesson of not utilizing the ‘student syndrome’.

Relationship Management

To do a good job of all the tasks mentioned above, students have to become accomplished at relationship management. They have to visit with their sponsor not only about the scope and expected outcomes, but what data and information is needed to complete the project. There will be missing data, acronyms that need to be explained, assumptions that have to be made and supported due to the missing data and information, uncertainty about the proper rule to guide the logic, and many other items to discuss on at least a weekly bases with the sponsor. Oftentimes it is being uncomfortable talking to a sponsor that leads to procrastination and missed time gates.

Data Sets and Simulation

Of course there is the ever present need to be able to make sense out of large sets of data and be able to convert them to information that ProModel can utilize. When dealing with nearly 12,000 different types of entities for one process, being processed through a job shop with 1400 unique process centers, the data sets become large. The route array that informs ProModel which machine which entity goes to when can become 12,000 rows and 200 columns, and the duration array can become too large and have to be split into four arrays, each with 3000 rows and 1400 columns.

There are many Excel tools that help the students explore their data sets. These tools include but are not limited to: filters, pivot tables, different types of lookup commands, find and replace, if statements, count statements, the ‘and’ function to build many lines of logic quickly, and different types of conditional formatting.

Once the base model and treated models are created and have generated 30 replications the students determine if the treatments actually made a difference by conducting a hypotheses test, if the null (the means of the samples have a high probability of being drawn from the same population) is rejected they proceed to the cost/benefit analysis. If the null is accepted, they try other treatments. If the treatment was successful, Statfit is utilized to determine the distribution of the output, at which point a Monte Carlo simulation is utilized to generate a larger sample of deltas between the base and a treated model to determine the distribution of deltas used to generate the net benefit.  That benefit could be number of extra units built, decrease in throughput time, time in system, net present value, or some other form of benefit.

Report Out

While the models are being built, the team is also working on their presentations and written reports. Thus, as they are discovering assumptions that they need to make, they are putting them into the oral and written report, thereby learning the value of parallel processing. By the time the last statistical analysis is completed, the presentation and paper are completed and ready for presentation for the teams that do a good job of following their PEP.

Conclusion

As demonstrated above there are many tools that ProModel users need to be proficient with when conducting a successful discrete event simulation using ProModel. However, perhaps it is not only ProModel and the ancillary tools that need to be taught and modeled when teaching a discrete event class, but the willingness to say, “I do not know how to do that, lets do some research and discover how”. That is the most important trait that modelers need to have, the willingness and perseverance to learn new tools and apply them in unique ways to capture unique opportunities.

Meet Professor Scott Metlen, Ph.D.

Dr. Scott Metlen earned his Ph.D. in Business Administration at the University of Utah in 2002 and is currently an associated professor of Production Operations Management at the University of Idaho. Dr. Metlen teaches Quality Management and Systems and Simulation, both are aspects of  Process Management. Prior to his academic carrier, Dr. Metlen spent 20 years managing products and processes in agriculture and food processing. Through a gift from the Micron Foundation, he has the resources to oversee at least twenty process improvement projects for various organizations per year through the classes he teaches. These projects provide meaningful experiential learning for the 40 to 80 students involved.

 

Brazilian Academic Simulation Awards Given in Honor of Rob Bateman

ProModel friends and associates, last October 12 we lost a dear friend, Rob Bateman and it is very hard to believe that a year has already passed.  Coincidentally, just a few days before the loss of our colleague, on October 6, 2015, the first ever ‘Rob Bateman’ award was delivered in the city of Joao Pessoa (north east coast of Brazil).  Here is the web site of the event:  http://www.abepro.org.br/enegep/2016/index.asp.  The Simula Brazil is a national award for simulation systems, organized and hosted by the portal “www.simulacao.net” which is sponsored by the Belge Consulting (www.belge.com.br). The award has institutional support of ABEPRO (www.abepro.org.br) and SOBRAPO (www.sobrapo.org.br) and is linked to the National Production Engineering Meeting (ENEGEP).

This award aims to encourage young students to use more simulation technology to develop projects and analyze real or fictitious situations through the use of the ProModel modeling and simulation technology (ProModel® or MedModel®) as well as assisting teachers with simulation education. The hope is that this practice will allow for better industrial engineering courses using ProModel and more simulation use in local companies, as well.  This year the award was given to the following recipients:

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Marcelo Fugihara of Belge presenting the award for originality to Jacyszyn Bachega of Universidade Federa de Goias

 

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Marcelo Fugihara of Belge presenting the award for complexity to Thiago Fernando Rosa Tedoro and Professor Jose Lazaro Ferraz of Universidade FACENS

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Here is a photo of all of the students in attendance at the event, called Enegep –  Encontro Nacional de Engenharia de Produção

We hope that this award in some small way pays tribute to our friend Rob Bateman.

Your friend in Simulation,

Alain de Norman & Belge team.