Conference Sponsor Keynote

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2 Conference Sponsor Keynote Multi-Agent System Modeling in FlexSim Bill Nordgren President/CEO - FlexSim Software Products, Inc. Abstract FlexSim s People Module is a powerful multi-agent system modeling tool. It allows you to quickly model groups of people (or even single individuals) and how they interact with their environment using simple process flows. This presentation will explore multi-agent modeling and when combined with FlexSim s A* (AStar) navigation system demonstrate how you can effectively model these complex situations. Other topics covered include recent updates to FlexSim s bone animations, which add a level of realism to the People Module visualization, as well as new features added to the A* navigation system. Bio Bill Nordgren is President/CEO of FlexSim Software Products. He was a co-founder of ProModel Corporation in 1988 and was Vice President until In 1993 Bill founded F&H Simulations, Inc. (now FlexSim Software Products Inc.) and introduced Taylor II, Taylor ED, and FlexSim into the market. Bill is an adjunct professor in Brigham Young University s College of Engineering and has authored several papers dealing with simulation project management and queuing theory. He is also a co-author of Applied Simulation: Modeling and analysis using FlexSim. In 2018, Bill was recognized with the Albert Nelson Marquis Lifetime Achievement Award for his accomplishments in the advancement of simulation technology. Bill received a Bachelor of Science in Manufacturing Engineering Technology, and a Master of Science in CIM (Computer Integrated Manufacturing) from Brigham Young University. Page 1 of 22

3 Speakers 2018 Theme: Simulation & Digital Twins The Digital Thread how does digital manufacturing fit in? Kevin Power Business Development Manager, TATA Technologies Abstract One of the latest innovations in manufacturing is the concept of a digital thread and the associated idea of a digital twin. A parallel innovation is the constant improvement in the capability and depth of digital manufacturing technologies which allow for simulation of manufacturing processes. So, how do these two innovations fit together? How does an overall digital twin / digital thread strategy incorporate a digital manufacturing initiative? The presentation will focus on a description of a possible digital twin strategy and how the technology available in digital manufacturing incorporated into that strategy. Included will be some examples of how the digital manufacturing and actual operations can be mirrored in the virtual and actual worlds. Does your company have a strategy to use digital manufacturing in an overall digital thread project? Bio Kevin Power has worked as a solution architect, account executive and electrical engineer with Tata Technologies over the last seventeen years. During this time, he was involved with the implementation of various CATIA V5 and Teamcenter deployments for customers in the automotive and aerospace industries. He has taught CATIA and PLM topics to a wide range of students and authored many methodologies and best practices for clients. After been involved with CATIA, he held the position of PLM Services Manager in Tata Technologies and was responsible for developing and deploying service offerings to various clients along with providing pre-sales support. Recently, Power has expanded his scope to other offering from Tata Technologies, including MOM systems. Power also held the position of Lead Electrical Engineer at Tata Technologies and has been responsible for the design of electrical systems for automotive programs and BEV powertrains. Power holds a bachelor s degree in electrical engineering along with various professional qualifications. Page 2 of 22

4 How IIoT Could Elevate Simulation from a Tactical Tool to a Strategic Decision Ian McGregor Director, Emulate3D Abstract It's often said that a simulation model is only as good as the data driving it. Assuming that's at least partially true, what opportunities does the IIoT offer simulation analysts and users? With greater access to high-quality real-time data and faster and cheaper processing to make use of it, how should we modify our approach to take advantage of this? This presentation shows how the elements are in place to take simulation to a higher level, where the ability to create and drive reliable Dynamic Digital Twins will increase the value of their output and make them a standard part of critical manufacturing and production processes. Bio Ian McGregor is a co-founder of Emulate3D and has been one of the three Director-owners since the company's creation in Emulate3D develops a range of engineering software designed to assist with off-line virtual commissioning (Emulate3D Controls Testing), data-driven throughput simulation and analysis (Sim3D), and demonstration, prototyping and layout software, (Demo3D and Layout3D). In 2014 Emulate3D was awarded a Queen's Award for Enterprise in the Innovation category, for which Ian was presented to Her Majesty the Queen Elizabeth II. Prior to creating Emulate3D Ian worked extensively with various simulation products worldwide; living and working as an engineer in the US for four years, Japan for one year, Singapore for eighteen months, and France for ten years. He has a Bachelor of Science degree in Mechanical, Aeronautical, and Production Engineering, a Diplome d'ingenieur in Applied Computing, a Master of Science degree in Computer Integrated Manufacturing, and is a Chartered Member of the Institute of Mechanical Engineers. Page 3 of 22

5 Improve Your Product's Quality using the Digital Twin Curtis DeSaele, Director of Technology, Waltonen Abstract Most quality improvements are made on the plant floor, once a quality issue is identified. Being reactive to quality will allow openings for your competition to leap frog you and win business. Use the digital twin to peer into the crystal ball of your product launch. Create a digital twin of your product s dimensional quality using 3D Tolerance Analysis to simulating part tolerances AND variation introduced by manufacturing and assembly processes. These digital twin tools predict amounts of variation, and identifies what causes them. Use the digital twin to fix issues before product release, and improve your product s quality. What three questions will be answered by this session? 1. How you can use the digital twin to evaluate product quality? 2. How the digital twin will allow you to optimize your design before product release? 3. How the digital twin saves time and money, and frequently reduces engineering changes by 30% Bio Curtis DeSaele has more than 30 years experience in manufacturing and product and engineering. Since 1984 he has been in the forefront of Digital Simulation, specifically related to virtual prototyping and dimensional quality. Curtis is recognized internationally as an expert in Digital Simulation using 3D Tolerance Analysis Simulation tools. Having worked for companies like EDS, GM, Siemens, UGS, PLM Software, and various engineering service companies, Curtis understands strategic and tactical business implementation of Digital Simulation tools. At these companies, he gained experience as a software programmer, corporate instructor/mentor, and user of multiple 3D Tolerance Analysis Simulation tools. For the past 12 years, Curtis has worked as a consultant within multiple industries: defense, aerospace, transportation, heavy industry, medicine, agriculture, energy, and consumer products. He has taught/helped clients with quality problems using Digital Simulation and 3D Tolerance Analysis Simulation tools. In addition to directly using 3D Tolerance Analysis Simulation tools, Curtis has experience using all the major CAD software, all the major PDMs, many different CAE tools, and multiple Digital Simulation software tools for robotic programming, plant planning, human ergonomics. Curtis enjoys the blending new technology, software, and best-in-class processes into new applications or industries, while driving quality and reducing overall costs. Page 4 of 22

6 General Simulation Topics Simulation Helping a Hospital Improve Operations Edward J. Williams, Sr. Simulation Analyst, PMC Abstract Discrete-event simulation now has a long and distinguished track record of guiding improvements to queuing systems subject to severe operational and budget constraints and also held to lofty expectations of service speed and quality. Historically, this track record began with simulation applications to manufacturing operations. These applications have now expanded far beyond manufacturing plants, to include supply-chain distribution systems, transport terminals, service industries (e.g., hotels and restaurants), and health care delivery in hospitals, clinics, and doctors and dentists offices. Relative to the application of discrete-event simulation discussed in this presentation, a large medical center in the Midwest region of the United States availed itself of the ability of simulation to guide improvements to and expansion of the emergency department and the surgical suite over a planning horizon of nearly a decade. This medical center serves a large urban area and the surrounding rural areas, and anticipates considerable pressure of increasing demand for its services. This increasing demand is attributable to significant demographic trends such as increasing density of population and gradually increasing average age of this population. Bio EDWARD J. WILLIAMS holds bachelor's and master s degrees in mathematics (Michigan State University, 1967; University of Wisconsin, 1968). From 1969 to 1971, he did statistical programming and analysis of biomedical data at Walter Reed Army Hospital, Washington, D.C. He joined Ford Motor Company in 1972, where he worked until retirement in December 2001 as a computer software analyst supporting statistical and simulation software. After retirement from Ford, he joined PMC, Dearborn, Michigan, as a senior simulation analyst. Also, since 1980, he has taught classes at the University of Michigan, including both undergraduate and graduate simulation classes using GPSS/H, SLAM II, SIMAN, ProModel, SIMUL8, Arena, or Simio. He is a member of the Institute of Industrial and Systems Engineers [IISE], the Society for Computer Simulation International [SCS], and the Michigan Simulation Users Group [MSUG]. He serves on the editorial board of the International Journal of Industrial Engineering Applications and Practice. During the last several years, he has given invited plenary addresses on simulation and statistics at conferences in Monterrey, México; İstanbul, Turkey; Genova, Italy; Rīga, Latvia; and Jyväskylä, Finland. He served as a co-editor of Proceedings of the International Workshop on Harbour, Maritime and Multimodal Logistics Modelling & Simulation 2003, a conference held in Rīga, Latvia. Likewise, he served the Summer Computer Simulation Conferences of 2004, 2005, and 2006 as Proceedings co-editor. He was the Simulation Applications track coordinator for the 2011 Winter Simulation Conference and the 2014 Institute of Industrial Engineers annual conference, and was a Manufacturing Track coordinator for the 2015 Winter Simulation Conference. His addresses are williame@umich.edu or ewilliams@pmcorp.com. Page 5 of 22

7 Remote Operation of a Semi-Automated Forklift Abdulhameed Al-Shaebi Research Engineer, Raymond Corp. Abstract In today s material handling industry, the basic forklift movements, traveling and lifting, are simply being automated, however the load handling operation is still a challenging task. Therefore, the development of remote-control capabilities where a skilled operator only intervenes to perform the complex task is a key step towards improving warehouse efficiency. However, it is a challenge to justify the associated investment without employing simulation. Demo3D plays a key role in quantifying the benefits and impacts of the remote operation implementation. In addition, Demo3D is used to evaluate different camera placement scenarios. This presentation provides detail on the remote operation, Demo3D role, and the expected benefits. Figure 1 an operator doing load handling remotely Page 6 of 22

8 How Long? Well, that Depends: Simulation in Critical Chain Project Management Kevin Kohls President, Kohls Consulting Abstract Woe the Project Manager. Few people are held more accountable for work that have absolutely no control over than PM s. They do few of the tasks in the projects. None of the resources work for them. And the due dates are set by sales people who will give whatever completion date gets the Purchase Order from the customer. But if their project is late? They get the bulk of the blame. But let s face it, most of the projects are late, almost by design. So why is that? In this presentation, we ll take a look at the application of the Dependency Variation Analysis model, the second generation of what was developed in GM as part of the Throughput Improvement Process. I started TIP over thirty years ago, and it s now used in every GM plant and for all future plant process designs. These same concepts can be extended into other areas, such as Project Management. For those using simulation, these concepts will be familiar. Projects are not really separate independent tasks, but a system network with interdependent events. The tasks are not performed by isolated, disconnected individuals; but are a limited pool of resources with limited amounts of time and a varying amount of interdependent commitments. And tasks? Good simulation engineers know that durations always vary. Always. And people who are assigned work tasks know this, too. But project management software somehow doesn t believe this. Task time are always a single number that reflects the average, not a distribution. The need for this single number causes data collection for PM sound more like a negotiation. PM: How long will it take to get the new machine installed? Engineer: That depends. If everything goes well, probably a week. But more often than not, it takes two. PM: The software needs a single number. I ll put in 7.5 days. Engineer: I said more often than not, and I said weeks. We always end up working 7 days, with overtime. (Gets out calculator and thinks about the last tongue lashing from the big boss for being late) Better put in, um, 18 days. PM: 18 days! The project is going to be late as it is. The big boss is pissed about the current completion data, and Sales is lying to the customer and is saying it will be done on time! They ll know you are padding this estimate. You ve got to come up with a better number than that. These are concepts easily handled by simulation. How long? PM s ask the engineers for a range, like 40 to 80 hours with a team of two machine builders. Great, lets set that up using a distribution with a 20/80 rule using a specific distribution (one with a long tail, perhaps?). Let s add all of those tasks into the model. Now, ask the big Page 7 of 22

9 boss how often do you want to deliver products to your customers on time? Fifty percent? Not likely. A target of 95% is probably what executives expect, and that s sets the confidence level. Now you are starting to challenge the paradigms of Project Management. Averages, at best, mean you would be on time 50%. That leads up to the next key concepts we learned from the TIP process at GM positive variation in a system of dependent events cannot make up for negative variation, and time lost on the constraint can never be recovered. These same concepts apply to the dependent tasks and the constraint resources in Project Management. After those considerations, even fifty Percent looks optimistic. Finally, attempting to get a project back on track is a stressful, chaotic process that usually occurs on the final lap, involves expensive overtime, and ensures that every other project behind it will be late as well. A simulation model, however, will not only allow your probability of on time completion to increase, but it will allow you to perform what if. Brainstorming through alternative solution of changing assignments, priorities, etc., allows team members to solve these problems before they become nightmare problems. I ll go through a case study of the work I did at REX Materials using the DVA process, and a simple, interactive demonstration of the training game I used there to go through some of these key concepts in the time that is available. Page 8 of 22

10 Vendor Sessions (in alphabetical order by company name) Simulation Modeling for the Entire Business Lifecycle David Kirby Regional Director Abstract Simulation modeling involves creating a digital and dynamic representation of a system or process and conducting experiments to predict performance under a variety of conditions. This overview of techniques, tools, modeling methods, project management best practices and demonstration models will introduce the attendee to the art and science of simulation modeling and how AnyLogic fits into the process.. Bio David Kirby has been in the B2B software industry for almost 30 years. Most of that time was spent with two major PLM/CAD companies, helping customers through the complexities of Product Lifecycle Management and Plant simulation. With these years of experience he is helping customers from many industries solve complex problems using dynamic simulation software. David has spent most of his adult life living in the Chicago area. Also living on the East coast and Munich, Germany. Page 9 of 22

11 AutoMod : Efficiency in Analysis of Large Complex Systems Dan Muller Global Product Manager Abstract The AutoMod product continues to lead the way in efficient modeling of manufacturing, distribution and logistics operation focusing on the impact of material handling. Through the years AutoMod had maintained this focus while others products attempt to model the world. Come see why AutoMod is the product of choice for the serious simulation users that require performance, scalability, and accuracy in modeling their large operations. The presentation will be a discussion on AutoMod s capabilities to model large systems as well as the current and future development plans. The presentation will also include time for users to share their AutoMod experiences with the audience. Bio Dan Muller has worked for Applied Materials/Brooks Automation/AutoSimulations since He is currently the Global Product Manager for the AutoMod Simulation Product. He previously has worked as a Consulting Manager, World-Wide Presales, and as a Senior Simulation Analyst, conducting numerous simulation studies for over ten years in a variety of industries. He currently coordinates the simulation development activities as well as manages the AutoMod world-wide distributor network. Prior to joining Applied Materials, Mr. Muller worked as Senior Simulation Consultant for Systems Modeling Corporation and as Systems Engineer for Litton Integrated Systems. Mr. Muller received a Bachelor of Industrial Engineering from Georgia Tech in 1985 and his Master of Science in Industrial Engineering from The University of Pittsburgh in Page 10 of 22

12 Tyler Phillips General Manager - Emulate3D Page 11 of 22

13 The Application of Simio Simulation and Scheduling in Industry 4.0 Katie Prochaska Application Engineer Abstract Simulation has traditionally been applied in system design projects where the basic objective is to evaluate alternatives and predict and improve the long term system performance. In this role, simulation has become a standard business tool with many documented success stories. Beyond these traditional system design applications, simulation can also play a powerful role in scheduling by predicting and improving the short term performance of a system. In the manufacturing context, the major new trend is towards digitally connected factories that introduce a number of unique requirements which traditional simulation tools do not address. Simio has been designed from the ground up with a focus on both traditional applications as well as advanced scheduling, with the basic idea that a single Simio model can serve both purposes. In this session, we will focus on the application of Simio simulation and scheduling in the Industry 4.0 environment. Bio Katie Prochaska has specialized in multiple simulation projects in the areas of manufacturing, automation, logistics, healthcare, and food & beverage for the past 4 years. In addition to working in these application areas, she is also lean green belt certified. Her journey started when she received both her Bachelor s and Master s in Industrial Engineering from Texas A&M University in While in school, she designed and developed security service technology while working as an Industrial Engineering Intern at the Walt Disney Company. These successes enabled her to excel as an Application Engineer for Simio LLC, where she is a digital twin expert for the Industry 4.0 revolution. With all this education and experience, she is able to lead the technical support team, provide sales support, assist in the Simio product direction and successfully train clients. Page 12 of 22

14 Integrating Operator and Material Flow evaluation in AutoCAD with your process documentation data flows Dave Sly President - Proplanner Evaluating Material Flow and Operator Flow in a workplace or factory is a basic first task of any layout and process improvement project. Since most companies use AutoCAD for their factory layout drawings, it is only natural that an analysis involving the layout occur in the same tool where the layout is defined. Having an ideal layout is essential for any dynamic process evaluation since the layout is traditionally static during such an analysis. A method of quickly evaluating operator and material flow in AutoCAD will be presented, along with typical Input/Output interface points being used today to greatly reduce the data entry required of this analysis. This method will use software such as AutoCAD, MS Excel, Workplace Planner and Flow Planner. Bio Dave Sly, President and Founder of Proplanner, a Professor of Practice in Industrial Engineering at Iowa State University and a registered professional engineer with the state of Iowa. Dr. Sly understands the issues facing the factory planner. Dave's expertise in software for facilities and manufacturing is reflected in his more than 40 papers and over 100 seminar presentations on the subject which he has pioneered for the past 35 years. Since publishing the first Factory Layout application for AutoCAD in the mid 1980 s Dr. Sly has worked with nearly 1,000 manufacturing plants in 39 different companies on projects related to Factory Layout, Material Flow Analysis, PFEP Databases, Direct Labor Measurement, Engineering Change Management, Assembly Line Balancing and Shop Floor Work Instruction publishing. Page 13 of 22

15 So you have a Digital Twin now what? Mike Rouman Senior Marketing Manager Siemens PLM Software Abstract At the 2017 Michigan Simulation User Group Conference our abstract suggested that digitalization is the new means to realize innovation for faster delivery of products while maintaining ultimate quality and, keeping product cost competitive. We also stated that Industry 4.0, digitalization, and the Digital Twin, are part of many industrial conversations which we are a part of. As evident by the theme for this year s event, indeed the Digital Twin plays a central role in the digitalization journey and has taken its rightful place in more than just industrial conversations. In this session we will present examples of fast and sophisticated analysis that leverage the Digital Twin of Production. The outcome of these analyses can be used to assess Capital and Labor required for Production. The higher the level of resemblance the Digital Twin has to its corresponding Production Physical Twin behavior, the closer the analysis will match actual Production. When the results predicted by the Digital Twin are the same as those observed when Production commences, the Digital Twin has played its part in faster delivery of products while maintaining ultimate quality and, keeping product cost competitive. Bio Mike Rouman is a Senior Marketing Manager at Siemens Product Lifecycle Management (PLM) Software, a business unit of the Siemens Digital Factory Division, a leading global provider of software, systems and services in the areas of Product Lifecycle Management (PLM) and Manufacturing Operations Management (MOM). As part of the Manufacturing Engineering Software business segment of Siemens PLM, Mike is responsible for product marketing of the Tecnomatix and Teamcenter portfolios of digital manufacturing software solutions. Mike has more than 25 years of experience in digital manufacturing engineering, sales and marketing across several industries and holds a Bachelor of Science degree in Mechanical Engineering from the University of Michigan. Page 14 of 22

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17 Vendors (in alphabetical order by company name) 30 years of market leadership in performance and accuracy of modeling large complex manufacturing, automotive, warehousing, airports, ports and logistics operations. For more information please contact: Dan Muller Applied Materials Simulation Product Manager Office Mobile Page 16 of 22

18 Forward Vision For the past 20 years Forward Vision has been a consultant and value added reseller in the discrete event and robotic simulation marketplace. Our team is ready to assist you with everything from simulation training to complete project consulting. You can find us on the web at For more information contact: Joe Hugan Forward Vision jhugan@forwardvision.com Page 17 of 22

19 Production Modeling Corporation (PMC) has been providing Industrial Engineering (IE) services worldwide for over 30 years. Our services range from New Manufacturing System Program Management to Digital Manufacturing applications as well as providing technical resources to support new and existing Manufacturing Processes. PMC has resources skilled in Discrete Event Simulation as well as a host of other IE and Material Handling Engineering (MHE) work: Time-study, CAD, 3D Scanning, Lean Systems, Material Handling Equipment Design, etc. PMC also provides a host of software and training in simulation, CAD, IE, and MHE areas. For more information contact: Production Modeling Corporation Melissa Buhalis Michigan Avenue Dearborn, MI Ext 1011 mbuhalis@pmcorp.com Page 18 of 22

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