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

Rajaei_Hassan

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.

Decision Support Tool Promotes Army’s Supply Chain Readiness

Two Department of Defense publications recently ran articles on the Army’s continuous pursuit of  supply chain excellence.  Our men and women in the military cannot do their jobs without the right materiel at the right place, at the right time, in the right quantity, and the right condition. ProModel Corporation is the software developer behind the Decision Support Tool (DST) featured in both articles.

Learn more about ProModel and our products, in booth #200 at the upcoming AUSA Global Force Symposium and Exposition on Mar 26-28 at the Von Braun Center in Huntsville, AL.

Decision Support Tool Promotes Army’s Supply Chain Readiness

“DST gives materiel managers the capability to realign equipment on their property books to maximize readiness or fulfill high-priority requirements. A plan that once took days to create can now be completed in minutes. With just a few clicks of the mouse, property book officers can optimize their formation, synchronizing existing equipment on-hand against authorization.”

– Lt. Col. Rodney Smith, chief, Distribution Integration Division, DMC.

Read full Army.mil article

AMC (Army Materiel Command) Restoring its Atrophied Repair Parts Inventory

Using a new system called the Decision Support Tool that Army Sustainment Command runs out of Rock Island Arsenal, Ill., “for the first time in my career, we can really see ourselves, and so we know where every single piece of equipment in the Army is, whether you are in the active component, the Reserve component or the National Guard. It’s never been that way; it’s very powerful.”

Army Materiel Command – General Gus Perna

Read full Defense News article

Huntsville Utilities Knows How to Win Back Customers

Watch this presentation from the 2017 E Source Forum Conference given by Huntsville Utilities on how they rebuilt customer relationships and prioritized customer experience (CX). ProModel played a role in this turnaround as mentioned starting at the 6:40 mark.

Speaking of Huntsville Alabama – We will be at the annual AUSA Global Force Symposium and Expo at the Von Braun Center in Huntsville, AL Mar 26-28. Stop by ProModel booth #200 and check out our latest products and releases.

ProModel Named to “20 Most Promising Simulation Solution Providers” by CIOReview

ProModel has been recognized among an elite group of companies that are featured in the simulation special edition of CIOReview magazine. CIOReview is a print magazine that explores how firms execute the their business and maximize their growth. Keith Vadas, President and CEO of ProModel, was interviewed by CIOReview for the magazine’s cover story.

CIOReview-cover

Challenged with making better decisions faster in an environment of constant change, today’s enterprises are turning to simulation as an enabling platform for decision support. The ability to capture the behavior of complex processes, then quickly create and run alternative scenarios enables enterprises to move from reactive to predictive and prescriptive decision-making. ProModel provides simulation tools and proven end-to-end solutions used by over 60% of the Fortune 500 and across the Public Sector…

Click here to view the full article on CIOReview.com or Read the CIOReview digital magazine article

CIOReview

ProModel and MedModel Optimization Suites 2018

Kevin Field

Kevin Field – Product Manager

This past December we released ProModel and MedModel 2018. You can see all the updates for each product at their respective “What’s New” website pages:

ProModel 2018 – What’s New?
MedModel 2018 – What’s New?

Please click on the video below to see some of the highlights of what’s new in ProModel/MedModel 2018.

ProModel and MedModel Simulation technologies and services help to plan, design and improve manufacturing, logistics and healthcare systems. They accurately represent real-world processes, including their inherent variability and interdependencies, in order to rapidly and easily conduct predictive analysis on multiple scenarios. You can virtually optimize your systems around your key performance indicators, before investing in any changes.

carilion 3rd floor

Proposed Hospital Floor Layout

ProModel Proposed Future Assembly Idea Zf_2.mod

Proposed Mfg Layout

This new release focused on significantly enhancing the UI as well as improving access and navigation to build modules, which helps reduce modeling time.

Here are just a couple of the new features and functionality:

Ribbon UI

The traditional menus and toolbars have been replaced with a fluent Ribbon bar like the one you find in Microsoft Office applications. The new Ribbon makes it easier to access the various modules and features within the application and better facilitate touch screen and high-resolution devices.

PM2018 Ribbon Toolbar

Quick Access Toolbar

Add highly used ribbon buttons to the Quick Access Toolbar (QAT) for fast and easy access to the program functionality they provide (located in the upper left corner of the application). Either select an option from the Customize menu or right-click on a button in the ribbon and choose to add it to the QAT.

customize-quick-access-toolbar

Docking Windows

Windows are now 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 can also stack windows on top of each other and quickly access them from their respective tab thus saving valuable view space. Windows even proportionally adjust when you resize the entire application.

docking-windows

You can also learn more about this release at the recording of the What’s New? Webinar  as well as a recent ProModel | MedModel 2018 Refresher Training webinar.

Don’t forget, you can also read about all the updates for each product at their respective “What’s New” website pages:

ProModel 2018 – What’s New?       MedModel 2018 – What’s New?

We would love to hear your feedback so please feel free to leave a comment below or to contact me with your thoughts and suggestions at kfield@promodel.com.  Happy Modeling!


American Food Manufacturer Shows Packaging and Palletizing Improves Production and Plans for Growth with the Use of Simulation

CHALLENGES

An American food manufacturing facility was looking to buy a new palletizer for their packaging/palletizing floor. The manufacturing group needed to perform a capacity analysis of the 13 existing palletizers in the facility which supported 29 production lines. The company was facing challenges keeping up with consumer demand for their popular products. ProModel was brought in to build a pilot model of the packaging and palletizing floor.

OBJECTIVES

The first set of objectives were to analyze and understand the following elements of the current operations:

  1. Case type throughput for an eight-hour shift
  2. Packaging line downtimes
  3. Palletizer utilization

The next set of objectives involved analyzing the impact of different changes to the system:

  1. Cases per pallet
  2. Conveyor length
  3. Adjusting palletizer downtimes

SOLUTION

A ProModel consultant and the company’s personnel worked together to build a pilot model. Packing lines to conveyors to palletizers are represented in the simulation model shown below.

The diagram does not reflect the actual conveyor layouts, but by using data provided by the company, actual conveyor speeds and distances were taken into consideration. The conveyors and palletizers being considered for future expansion were also included in the model.

SS-Palletizer-Improvement_Image_3

More changes to the system can be analyzed since the simulation model is extremely customizable. For example, as additional downtime information is collected, the model can be dialed in to better reflect actual operations. The model allows for other process changes over time too like cycle times, introduction of new cases and new palletizers.

As a result of the success of the pilot model, this company and ProModel will be working together to model another palletizing floor of the facility. The one change that the client requested is that actual conveyor layouts be reflected in this second model to better illustrate how they impact production flow.

VALUE PROVIDED

The company has a model of each palletizing floor. These models can be connected and the organization can test and evaluate changes and expansions to the entire palletizing portion of their facility to guarantee that variations and increases in consumer demand will be met.