WSC 2002

WSC 2002 Final Abstracts

Manufacturing Applications Track

Monday 10:30:00 AM 12:00:00 PM
Manufacturing 1

Chair: Deb Medeiros (The Pennsylvania State University)

Simulation-Based Analysis of a Complex Printed Circuit Board Testing Process
Jeffrey S. Smith and Yali Li (Auburn University) and Jason Gjesvold (Soldering Technology International, Inc.)

This paper describes a simulation-based analysis of a printed circuit board (PCB) testing process. The PCBs are used in a defense application and the testing process is fairly complex. Boards are mounted on a test unit in batches and go through three thermal test cycles. As boards fail testing during the thermal cycling, operators can either replace the failed boards at fixed points during the cycling or can allow the test unit to complete the testing cycle before removing failed boards. The primary objective of the simulation study is to select an operating strategy for a given set of operating parameters. A secondary objective is to identify the operating factors to which the strategy selection is sensitive. Initial testing indicated that failed boards should be replaced as soon as possible under the current operating configuration of the sponsor’s facility. Secondary testing is also described.

A Simulation Study of High Power Detonator Production Transition
Johnell Gonzales-Lujan and Robert J. Burnside (Los Alamos National Laboratory) and George H. Tompkins (Los Alamos)

Due to changes in production requirements the current facility was no longer adequate. A simulation study was conducted to help quantify the impacts of additional capacity, when that capacity should be brought online, and how to manage production in the interim before the new facility is available.

Capacity Analysis of Multi-Product, Multi-Resource Biotech Facility Using Discrete Event Simulation
Prasad V. Saraph (Biological Products, Bayer Healthcare)

Use of simulation for capacity analysis is an upcoming field in Biotech industry. This paper discusses an application of discrete event simulation in the multi-product and multi-resource Filling Freeze-Drying facility of Bayer Corporation’s Berkeley site. The SIGMA® simulation model was used to estimate the current and future throughput capacity by taking into account current operations and various capital and efficiency improvement projects planned for near future. The model also identified certain project clusters with potential for large capacity gains, which otherwise would not have been visible. The model and its outcome are in use since 2001.

Monday 1:30:00 PM 3:00:00 PM
Manufacturing 2

Chair: Todd Lebaron (Brooks Automation)

Shop Scheduling Using Tabu Search and Simulation
Daniel A. Finke, D. J. Medeiros, and Mark T. Traband (The Pennsylvania State University)

An important goal in scheduling products through a manufacturing facility is to assure that the work is completed as close as possible to its due date. Work that is late creates downstream delays, while early completion can be detrimental if storage space is limited. This paper reports initial results in developing a scheduling procedure for an automated steel plate fabrication facility. The approach uses Tabu search combined with simulation to schedule product through a set of machines. Performance of the procedure is evaluated by comparison to the optimal solution for small problem instances, and to a good heuristic for larger problems. Results show that the Tabu search method works well for this problem. Combining Tabu search with simulation allows the incorporation of more realistic constraints on system operation.

A Simulation Study of Robotic Welding System with Parallel and Serial Processes in the Metal Fabrication Industry
Carl R. Williams and Peraset Chompuming (University of Memphis)

This paper presents the usefulness of simulation in studying the impacts of system failures and delays on the output and cycle time of finished weldments produced by a robotic work cell having both serial and parallel processes. Due to multiple processes and overlapped activities, process mapping plays a significant role in building the model. The model replicates a non-terminating welding fabrication system with duplicate stochastic events caused by system failures and delays. A full factorial model is employed and analyzed to examine the main and interaction effects of five major types of system failures and delays via multiple regression analysis. The analysis derived from the full factorial model shows that material handling carrier delays have the most significant impact on the cycle time. This case study illustrates a modeling approach with system verification and validation revealing fundamental system design flaws which cause a significant loss of production.

Creation of a Self Adaptive Simulation for Radex Heraklit Industries
Shabnam Tauböck, Christian Wartha, and Michael Steiner (ARC Seibersdorf Research), Gerhard Pirkner (Didier-Werke AG, Werk Marktredwitz) and Felix Breitenecker (Vienna University of Technology)

The main goal of this project was to create a simulation of the production plant of Radex Heraklit Industries (RHI) that offers the possibility to change the structure of the model by adding machines and furnaces and change system parameters. The large amount of data needed soon implied the use of a database connected to the simulation. This resulted in a simulation that not only imported the needed data for simulating but also data concerning the whole model structure. Only a basic structure is implemented and according to the data imported from the database the full simulation model is created on resetting. This offers a high flexibility: machines can be added and removed, parameters changed as well as the whole course of manufacture only by editing the corresponding data in the database. The data collected during simulation allows a precise analysis and comparison of single simulation runs.

Monday 3:30:00 PM 5:00:00 PM
Manufacturing 3

Chair: Ed Williams (University of Michigan, Dearborn)

Discrete Event Simulation in Automotive Final Process System
Vishvas Patel, James Ashby, and John Ma (General Motors)

The Final Process System is an important part of the entire quality assurance system in the automobile manufacturing process. Operators and machines perform a series of crucial testing procedures before shipping a vehicle. Many complex factors impact the system throughput. The important ones are first time success rate, repair and service routing logic, process layout, operator staffing, capacity of testing equipment and random equipment breakdown. Discrete Event Simulation is a tool of choice in analyzing these issues in order to develop an effective and efficient process to ensure the system throughput. Using a case study from the automotive industries, this paper discusses the methodology of modeling and studying the Final Process System. The concepts and methods presented here are also applicable to other discrete manufacturing processes.

A Simulation Study of an Automotive Foundry Plant Manufacturing Engine Blocks
Sang D. Choi, Anil R. Kumar, and Abdolazim Houshyar (Western Michigan University)

This paper discusses the initial efforts to implement simulation modeling as a visual management and analysis tool at an automotive foundry plant manufacturing engine blocks. The foundry process was modeled using ProModel to identify bottlenecks and evaluate machine performance, cycle times and production data (total parts, rejects, throughput, products/hr) essential for efficient production control. Results from the current system identified assembly machine work area as the bottleneck (although utilization was greater than 95% for two assembly machines) resulting in high work-in-process (WIP) inventory level, low resource and machine utilization. Based on these results, optimal numbers were identified through use of scenarios by varying the number of assembly machines and processing time of each machine. In addition to these scenarios, strategies for production control involving buffer sizes were also made.

Manufacturing Process Modeling of Boeing 747 Moving Line Concepts
Roberto F. Lu and Shankar Sundaram (The Boeing Company)

Thousands of jobs performed on the Queen of the Sky, the Boeing 747, final assembly line for each airplane. When the decision was made to implement a moving line for the final assembly of the 747 it was absolutely necessary to evaluate many aspects of these jobs. Discrete Event Simulation models were constructed to analyze 747 final assembly moving line scenarios throughout several phases. These models not only presented visual understanding of different concepts, but also provided quantitative analysis of suggested scenarios to the moving line team. The results are highly optimized production flows and processes, reducing cost and flow time from the traditionally 24 days to the targeted possible 18 days. This work outlines some of the moving line concepts, modeling objectives, and simulation analysis. Utilizations of different assembly positions were yielded as the result of discrete simulation modeling of the 747 final assembly operation.

Tuesday 8:30:00 AM 10:00:00 AM
Transportation and Material Handling

Chair: Chad DeJong (Intel Corporation)

Complexities of AGV Modeling in Newspaper Roll Delivery System
Daniel J. Muller and Sarah M. Cardinal (Brooks-PRI Automation, Inc.) and Juergen Baumbach (Swisslog Logistics Inc.)

Swisslog Logistics Inc., a leader in Automated Guided Vehicle (AGV) technologies, proposed to update a major Northeastern newspaper company’s AGV press delivery system. The project requirements included the development of a simulation model to confirm the proposed vehicle quantity and controls as well as evaluate the performance of the AGV system in response to the following three operating scenarios: 1) Press Changeovers, 2) Peak Production/Demand (3 Hours), 3) Weekly Production Schedule. The model provided Swisslog and its customer with the capabilities to evaluate dynamic vehicle scheduling, task priorities, press changeover requirements, vehicle routings and battery charging logic. This paper shall present the concepts and techniques used to model the detailed AGV components necessary to successfully meet the project’s objectives.

Solving Logistics and Transportation Problems in a Job Shop
Kambiz Farahmand and Arun Balasubramanian (Texas A&M University)

A discrete event simulation model was developed to study the flow of material and product in a shop floor. It uses real time data available from a job shop solely dedicated to non-commercial contracts and as such deals with very seasonal demand. The objective of this model is to provide the shop with a decision support tool that will assist in evaluating the movement of products throughout the shop. The simulation will be useful in assessing the length of queues formed at each shop as well as in pointing out bottlenecks. Actual operational and flow data are utilized in developing the model. The simulation is implemented using the Arena software. In effect, the model is to be used for a better understanding of operation of the shop floor and better utilization of all the available resources.

Tuesday 10:30:00 AM 12:00:00 PM
Best Modeling Methods

Chair: Marvin Seppanen (Productive Systems)

Virtual Factory – Highly Interactive Visualisation for Manufacturing
Wolfgang Mueller-Wittig, Reginald Jegathese, Meehae Song, Jochen Quick, Haibin Wang, and Yongmin Zhong (Nanyang Technological University)

Funded by the Agency for Science, Technology and Research - A*STAR - Singapore, CAMTech is collaborating with a Singaporean research institute and two industry partners with the objective to improve electronics assembly processes. The goal of this project is to visualise the behaviour of an electronics assembly industry based on discrete events simulation. The traditional scenario - from the customer placing order for a product to delivery - goes through various phases including manufacturing the product. Several major electronics manufacturing stages can be addressed: fabrication, assembly, testing, and packing. Each of these stages accounts for set up, process, failure, and wait time periods. A delay in one process will accumulate over to the future delays. To simulate the discrete events a general-purpose simulation system has been employed. For modelling and visualisation CASUS (Computer Animation of Simulation Traces) system has been used and refined developed by Fraunhofer Institute for Computer Graphics (Fraunhofer-IGD).

Turn Lost Production Into Profit – Discrete Event Simulation Applied on Resetting Performance in Manufacturing Systems
Björn Johansson and Jürgen Kaiser (Chalmers University of Technology)

World-class utilization of manufacturing resources is of vital importance to any manufacturing enterprise in the global competition of today. This requirement calls for superior performance of all processes related to the manufacturing of products. One of these processes is the resetting of machinery and equipment between two product runs, which will be the focus area of this paper. This paper examines to what extent Discrete Event Simulation (DES) can be applied to the evaluation of resetting performance in manufacturing systems. For this purpose, a DES model of a factory unit in Sweden is used for the research trials, derived from real manufacturing situations. During the case study, DES has shown to be a potential tool for the evaluation of resetting processes. The results from the simulation runs provided valuable information for improvement initiatives. Among other findings a solution is proposed, that turns losses into profit.

Documentation of Discrete Event Simulation Models for Manufacturing System Life Cycle Simulation
Jan Oscarsson and Matías Urenda Moris (University of Skövde)

The concept of life cycle simulation appeals to most production engineers. There is a problem with simulation models of manufacturing systems; they may be highly complex and time consuming to develop. They embrace a considerable experience, which is gained through the development process of the simulation model. It is therefore not enough to develop an accurate simulation model. The model must be understood, updated, reused and inhered by others. One way to achieve these goals could be through use of a standardised documentation, which in turn explains the model and how it has been developed. This paper presents a method for how simulation models can be documented by standardised notations. The documentation is adapted to different users of the simulation model.

Tuesday 1:30:00 PM 3:00:00 PM
Productivity Improvement

Chair: Joe Hugan (Forward Vision)

Shifting Bottleneck Detection
Christoph Roser, Masaru Nakano, and Minoru Tanaka (Toyota Central Research and Development Laboratories)

This paper describes a novel method of calculating the sensitivity of the manufacturing system throughput to the variables of the machines. The sensitivity analysis needs only a single simulation, yet is easy to use and provides accurate results. This sensitivity analysis is then used to predict the change in the system throughput due to a change of the variables of the machines provided that the system change does not significantly change the bottleneck. These predictions can be used for a local optimization, allowing the use of a steepest descent optimization algorithm. The method is based on improving the momentary shifting bottlenecks. The shifting bottlenecks are detected using the shifting bottleneck detection method based on the active duration, i.e., the time a machine is active without interruption. The method is easy to understand and easy to implement in existing simulation software.

Throughput Sensitivity Analysis Using a Single Simulation
Christoph Roser, Masaru Nakano, and Minoru Tanaka (Toyota Central Research and Development Laboratories)

This paper describes a novel method of calculating the sensitivity of the manufacturing system throughput to the variables of the machines. The sensitivity analysis needs only a single simulation, yet is easy to use and provides accurate results. This sensitivity analysis is then used to predict the change in the system throughput due to a change of the variables of the machines provided that the system change does not significantly change the bottleneck. These predictions can be used for a local optimization, allowing the use of a steepest descent optimization algorithm. The method is based on improving the momentary shifting bottlenecks. The shifting bottlenecks are detected using the shifting bottleneck detection method based on the active duration, i.e., the time a machine is active without interruption. The method is easy to understand and easy to implement in existing simulation software.

Productivity Improvement in the Wood Industry Using Simulation and Artificial Intelligence
Felipe F. Baesler, Milton Moraga, and Francisco J. Ramis (Universidad del Bío-Bío)

The objective of this article is to present the results obtained after using a simulation optimization methodology applied to a production line from a secondary manufacturing wood processing plant of a well known Chilean mill. For this reason a simulation model constructed in a simulation software called ARENA, was integrated to a genetic algorithms heuristic. The results obtained show that using a different configuration of the plant resources, it is possible to reduce the total average cycle time in approximately 18%. The resource configuration needed to reach this result was obtained evaluating just 1.6% of the total number of possible combinations.

Tuesday 3:30:00 PM 5:00:00 PM
Manufacturing Modeling Architectures

Chair: Young Jun Son (University of Arizona)

Manufacturing Adapter of Distributed Simulation Systems Using HLA
Hironori Hibino (JSPMI), Yoshiro Fukuda (Hosei University), Yoshiyuki Yura (Shimizu Corporation), Keiji Mitsuyuki (Denso Corporation) and Kiyoshi Kaneda (Makino Milling Machine Corporation)

In this research, the distributed simulation system to easily evaluate a very large manufacturing system by synchronizing several different simulators is developed. We designed the distributed simulation system using High Level Architecture(HLA) as IEEE1516 standard. A manufacturing adapter to connect manufacturing system simulators with HLA using a plug-in style is proposed. The developed distributed simulation system is confirmed using a case to evaluate a hypothetical manufacturing system which produces motors. Three major commercial based manufacturing system simulators as QUEST, SIMPLE++, and GAROPS are connected using the developed manufacturing adapter. The storage model method to connect simulation models and synchronize the simulators is used in the case study. The case study is then carried out to evaluate the performance of the cooperative work.

An Architecture for a Generic Data-Driven Machine Shop Simulator
Charles McLean, Al Jones, Tina Lee, and Frank Riddick (NIST)

Standard interfaces could help reduce the costs associated with simulation model construction and data exchange between simulation and other software applications -- and thus make simulation technology more affordable and accessible to a wide range of potential industrial users. Currently, small machine shops do not typically use simulation technology because of various difficulties and obstacles associated with model development and data translation. This paper provides an overview of work currently under way at the National Institute of Standards and Technology (NIST) to develop a software architecture, standard data interfaces, and a prototype generic machine shop simulator that can be readily, reconfigured for use by a large number of small machine shops. It also reviews prior work in this area and describes future work.

Architectural Concepts for a System Simulator for Concurrent Prototyping of Equipment and Controls
K. Preston White, Jr., Ryan Fritz, Stephen Horvath, Carlos Orellana, and Jonathan Wohlers (University of Virginia) and Richard G. Fairbrother and William S. Terry (Lockheed Martin Distribution Technologies)

AutoMod is a leading discrete-event simulation package widely applied in the modeling and analysis of distribution systems. Included in the AutoMod software suite is the Model Communications Module (MCM), which allows an executing simulation to open socket connections and to send and receive messages via TCP/IP network protocol. In this paper we report on a pilot study which explores the functionality of the MCM. In particular, we develop and implement an architecture that can be used to design, test, verify, and optimize control system software interacting with a discrete-event simulation of the system to be controlled. This architecture supports concurrent engineering of controls and hardware prototypes. Application of this architecture can significantly reduce the duration and cost of development cycles for new equipment and systems. In addition, this architecture can be applied to investigate the feasibility of implementing engineering changes in systems currently deployed.

Wednesday 8:30:00 AM 10:00:00 AM
Manufacturing Modeling Methods

Chair: K. Preston White (University of Virginia)

Use of GI/G/1 Queuing Approximations to Set Tactical Parameters for the Simulation of MRP Systems
S. T. Enns (University of Calgary) and Sangjin Choi (Korea Institute of Energy Research)

There is a lack of prescriptive methods for setting lot sizes and planned lead times effectively in MRP systems. Recent research has suggested the application of queuing relationships. This study experimentally investigates the use of GI/G/1 relationships for lot size selection along with the use of exponentially smoothed feedback for dynamic planned lead time setting. Results show that assumptions regarding lot interarrival time variability have a large effect on lot sizes and performance.

Virtual Reality Simulation of a Mechanical Assembly Production Line
Deogratias Kibira and Chuck McLean (National Institute of Standards and Technology)

This paper presents our work on the application of virtual- reality simulation to the design of a production line for a mechanically-assembled product. The development of this simulation was undertaken as a part of the Manufacturing Simulation and Visualization Program at the National Institute of Standards and Technology in Gaithersburg, MD. The major research problem is the partitioning and analysis of the assembly operation of the prototype product into different tasks and allocation of these tasks to different assembly workstations. Issues such as cycle times, material handling and assembly line balancing complicate the problem. This paper demonstrates the difficulties of using simulation modeling for concurrent graphical simulation of assembly operations and discrete event analysis of a production process in the same model. It also points out the need to speed up the modeling process and reduce the level of effort required in the construction of a simulation model.

An Approach and Interface for Building Generic Manufacturing Kanban-Systems Models
Edward J. Williams (University of Michigan - Dearborn), Onur M. Ülgen (University of Michigan) and Chris DeWitt (Production Modeling Corporation)

Simulation of manufacturing systems, historically the first major application area of discrete-event process simulation, is becoming a steadily more proactive and important strategy for achieving manufacturing efficiency. Concurrently, lean manufacturing has become a nearly essential corporate strategy to compete successfully in an increasingly austere and global business environment. Furthermore, industrial engineers responsible for supporting successfully competitive manufacturing operations have less and less time available for manipulating details deep within a simulation model in order to evaluate numerous complex alternatives. Convergence among these trends motivated the development of a generic manufacturing kanban-systems simulator that has Kanban inventory optimization capability, and an accompanying interface, described in this paper.

Wednesday 10:30:00 AM 12:00:00 PM
Simulation of Manufacturing Operations

Chair: Cindy Schiess (Design Systems, Inc.)

Optimum-Seeking Simulation in the Design and Control of Manufacturing Systems: Experience with OptQuest for Arena
Paul Rogers (University of Calgary)

This paper presents some of my experience in applying a commercial optimum-seeking simulation tool to manufacturing system design and control problems. After a brief introduction to both the general approach and to the specific tool being used, namely OptQuest for Arena, the main body of the paper reports on the use of the tool in tackling two manufacturing system design and control problems, one very simple and one significantly more complex. The paper concludes with some material highlighting how easy the tool is to apply to this kind of problem and also presents some thoughts on how the tool might be enhanced to improve its value.

Optimization of Operations in a Steel Wire Manufacturing Company
Jai Thomas, Jayesh Todi, and Asif Paranjpe (Western Michigan University)

The project was conducted in a high quality steel wire manufacturing company with the production capacity of over 120,000 tones/annum. The wire drawn from the high speed wire drawing (KOCH) machine is fed as the raw material for BEKEART (zinc coating galvanization) furnace. The problem faced by the company is the variability in the amount of input to the furnace, which results from the breakdowns occurring on the KOCH machine resulting in low production. Any downtime in the process occurring at the KOCH machine adversely affects the productivity of the BEKEART furnace, as a result of which the total production on this line suffers and hence the profits of the company. Simulation study was done with the objective of increasing the throughput and ensuring smooth product flow through the system by finding the optimum arrival batch size.

Optimization of Buffer Sizes in Assembly Systems Using Intelligent Techniques
Fulya Altiparmak and Berna Dengiz (Gazi University) and Akif A. Bulgak (Concordia University)

When the systems under investigation are complex, the analytical solutions to these systems become impossible. Because of the complex stochastic characteristics of the systems, simulation can be used as an analysis tool to predict the performance of an existing system or a design tool to test new systems under varying circumstances. However, simulation is extremely time consuming for most problems of practical interest. One approach to overcome this limitation is to develop a simpler model to explain the relationship between the inputs and outputs of the system. Simulation metamodels are increasingly being used in conjunction with the original simulation, to improve the analysis and understanding of decision-making processes. In this study, artificial neural networks (ANN) metamodel is developed for simulation model of an asynchronous assembly system and ANN metamodel together with simulated annealing (SA) is used to optimize the buffer sizes in the system.

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