WSC 2004 Final Abstracts
Sunday 1:00:00 PM 2:30:00 PM
Manufacturing Systems Analysis and Planning
Chair: Charles Standridge (Grand Valley State University)
A systematic procedure of module-based modeling is designed and proposed to develop a simulation of any flow-type multistage manufacturing system adopting especially the dual-card Kanban system. First, functional analysis is performed to present kanban flows exactly in the same fashion in a simulation model as they are actually appeared in the real manufacturing system. One Customer module, the required number of Workstation modules, and one Supplier module make a set to develop a designated simulation. In addition, a numerical example is shown to apply the proposed procedure.
Optimal Lot-Sizing with Capacity-Constraints and Auto-Correlated Interarrival Times
Silvanus T. Enns and Li Li (University of Calgary)
There have been recent advances in using queuing relation-ships to determine lot sizes that minimize mean flowtimes when multiple product types are being produced at capac-ity-constrained resources. However, these relationships assume lot interarrival times are independent, which is not the case in most manufacturing scenarios. This study ex-amines the performance lot-sizing optimization relation-ships based on GI/G/1 relationships when lot interarrival times are auto-correlated. Simulation and response surface modeling are used to experimentally determine optimal lot sizes for a sample problem. The flowtimes for ¡§optimal¡¨ lot sizes determined analytically are found to compare poorly with with the best flowtimes obtained experimen-tally. An approah is then developed that uses feedback during simulation to adjust parameters within queuing heu-ristics that support dynamic lot-size optimization. Per-formance using this approach compares well with the best performance obtained using the much more difficult ex-perimental approach.
Simulation-Based Layout Planning of a Production Plant
Mert Altinkilinc (Old Dominion University)
This paper presents a study that uses simulation to improve shop floor performance by means of two layout types and certain operational parameters. In this study, an overview of the plant layout problem is covered for the particular company. The original motivation for redesigning the entire shop floor was the need to realize improvements in material flow and output level. First, the performance of the existing system was evaluated by using ARENA. Second, manufacturing cells were formed and group technology layout was developed by means of Rank Order Clustering (ROC) method and Computerized Relative Allocation of Facilities Technique (CRAFT). Finally, the performance of the new system was evaluated and compared with that of the current system.
Module-Based Modeling of Flow-Type Multistage Manufacturing Systems Adopting Dual-Card Kanban System
Junichi Nomura and Soemon Takakuwa (Nagoya University)
Sunday 3:00:00 PM 4:30:00 PM
New Manufacturing Modeling Methodology
Chair: Björn Johansson (Product and Production Development)
This paper presents a top-down mechanism for coordinat-ing Distributed Discrete Event Simulation (DDES) models using an MRP/ERP system as the federation coordinator. The same MRP/ERP system, which is typically used as a coordination tool for interactions between complex highly variable manufacturing systems, serves to coordinate and synchronize complex highly variable simulation models of these same systems. This research focuses on enabling each system entity modeled by DDES models to constantly correct its performance with respect to reference trajecto-ries which consist of planned orders and the size of a time bucket generated by an MRP/ERP system, and trigger a global coordinator which consists of the MRP/ERP system and adapter if necessitated by any discrepancies observed by the entity through simulation models. A global coordi-nator can synchronize timing of DDES models and provide adaptive time buckets using the cost-based mathematical model and corrected plans using the updated time bucket.
Hierarchical Production Planning Using a Hybrid System Dynamic - Discrete Event Simulation Architecture
Jayendran Venkateswaran and Young Jun Son (University of Arizona) and Albert Jones (National Institute of Standards and Technology)
Hierarchical production planning provides a formal bridge between long-term plans and short-term schedules. A hybrid simulation-based production planning architecture consisting of system dynamics (SD) components at the higher decision level and discrete event simulation (DES) components at the lower decision level is presented. The need for the two types of simulation has been justified. The architecture consists of four modules: Enterprise-level decision maker, SD model of enterprise, Shop-level decision maker and DES model of shop. The decision makers select the optimal set of control parameters based on the estimated behavior of the system. These control parameters are used by the SD and DES models to determine the best plan based on the actual behavior of the system. High Level Architecture has been employed to interface SD and DES simulation models. Experimental results from a single-product manufacturing enterprise demonstrate the validity and scope of the proposed approach.
How Factory Physics Helps Simulation
Charles R. Standridge (Grand Valley State University)
Factory physics provides a systematic description, expressed as laws, of the underlying behavior of a system. These laws can provide important assistance in performing simulation studies. They help in deciding what performance measures to collect and what alternatives to evaluate as well as in interpreting simulation results. The laws help identify the properties of systems that may be important to include in models. They provide an analytic foundation that helps in understanding the behavior of systems as well as giving insight into the types of issues addressed in simulation studies. Verification and validation evidence can be collected based on these laws. This paper examines the application of specific factory physics laws to the activities of a simulation project. Examples showing the application of these principles in industrial projects, masters level student projects, and application studies used in undergraduate and graduate simulation classes are given.
A Resource Reconciliation Mechanism for a Manufacturing Federation Coordinated Using an MRP/ERP System
Seungyub Lee and Richard Allen Wysk (The Pennsylvania State University)
Monday 10:30:00 AM 12:00:00 PM
Manufacturing Systems Control
Chair: Silvanus Enns (University of Calgary)
A New Approch to Multi-Pass Scheduling in Shop Floor Control
Taejong Yoo, Daehong Kim, and Hyunbo Cho (Pohang University of Science and Technology)
Real-time planning and scheduling in a shop floor are not easy to accomplish due to the concurrent flow of various parts as well as sharing of different types of resources. Multi-pass scheduling is a well known method for solving the aforementioned problem. Its success depends largely on selecting the best decision-making rule fast and effectively. Although many efforts have been made in the past, a way to minimize the computational load of rule evaluation and selection has yet to appear. The objective of the paper is to apply a nested partitioning (NP) method and an optimal computing budget allocation (OCBA) method to reduce the computational load without the loss of the performance of multi-pass scheduling. The experimental design and analysis was performed to validate that NP and OCBA can be successfully applied to multi-pass scheduling in order to enhance the performance of multi-pass scheduling.
Using Autonomous Modular Material Handling Equipment for Manufacturing Flexibility
Björn Johansson (Chalmers University of Technology), Edward J. Williams (Production Modeling Corporation) and Tord Alenljung (Chalmers University of Technology)
This paper describes a modular autonomous material handling equipment solution for flexible automation. Discrete Event Simulation is in this case used as a tool for shortening time spent in many different phases of a manufacturing systems lifecycle. The paper presents the concept of autonomous modular material handling equipment, and how simulation is used as a support tool and lead time reducer in each lifecycle phase. Furthermore, we describe the knowledge levels needed for using the simulation support and conclude with examples of how this methodology are reducing lead times within a company.
A Decision Tool for Assembly Line Breakdown Action
Frank Shin (NC A&T State University)
Assembly lines with closed loop parallel lanes have the potential to continue to be productive when individual stations breakdown. A requirement in such parallel lane systems is that the products must exit the parallel lanes in the same sequence as they entered. Such lines offer the opportunity to run the line partially either by shutting down an affected lane or by bypassing the failed station to continue to run on all lanes. Bypassing a station, however, requires a backup station that can pick up the incomplete work at a later stage in the process. However, when a station breakdown occurs, it is not readily obvious as to whether to bypass the affected lane or just the affected station. This decision will vary depending on which station failed and the length of the repair. This paper presents a discrete-event modeling approach to provide a decision-making tool during breakdowns.
Monday 1:30:00 PM 3:00:00 PM
Supply Chain Analysis
Chair: Hyunbo Cho (POSTECH)
Study to Assess the Efficacy of Linear Control Theory Models for the Coordination
of a Two-Stage Customized Service Supply Chain
Douglas J. Morrice, Edward G. Anderson, and Saurav Bharadwaj (The University of Texas at Austin)
In this paper, we conduct a simulation study to evaluate linear control theory models applied to the management and coordination of a two-stage customized service supply chain. Linear models that were proposed in previous research are compared against more general nonlinear models for three different levels of coordination: centralized, decentralized, and no information sharing. Using simulation and regression analysis, we show that the linear models yield results that are off by an average of six percent or less for parameter values observed in practice.
Analysis of Supply Chains Using System Dynamics, Neural Nets, and Eigenvalues
Luis Rabelo (University Of Central Florida), Magdy Helal (University of Central Florida) and Chalermmon Lertpattarapong (Massachusetts Institute of Technology)
Supply chain management is a critically significant strat-egy that enterprises depend on in meeting the challenges of today’s highly competitive and dynamic business envi-ronments. An important aspect of supply chain manage-ment is how enterprises can detect the supply chain be-havioral changes due to endogenous and/or exogenous influences and to predict such changes and their impacts in the short and long term horizons. A methodology for addressing this problem that combines system dynamics and neural networks analysis is proposed in this paper. We use neural networks’ pattern recognition abilities to capture a system dynamics model and analyze simulation results to predict changes before they take place. We also describe how eigenvalue analysis can be used to enhance the understanding of the problematic behaviors. A case study in the electronics manufacturing industry is used to illustrate the methodology.
Exploring the Impact of RFID on Supply Chain Dynamics
Young M. Lee and Feng Cheng (IBM ) and Ying Tat Leung (IBM )
Radio-frequency identification (RFID) as an emerging technology has generated enormous amount of interest in the supply chain arena. With RFID technology, inventory can be tracked more accurately in real time resulting in reduced processing time and labor. More significantly, the complete visibility of accurate inventory data throughout the entire supply chain, from manufacturer’s shop floor to warehouses to retail stores, brings opportunities for improvement and transformation in various processes of the supply chain. We developed a simulation model to study how RFID can improve supply chain performance by modeling the impact of RFID technology in a manufacturer-retailer supply chain environment. Our study provides a quantitative analysis to demonstrate the potential benefits of RFID in inventory reduction and service level improvement.
Monday 3:30:00 PM 5:00:00 PM
Supply Chain Simulation Application
Chair: Luis Rabelo (University of Central Florida)
Impact of Production Run Length on Supply Chain Performance
David J. Parsons, Robin J. Clark, and Kevin L. Payette (Simulation Dynamics)
This paper documents an experiment designed to show the value of simulation in understanding the relationship be-tween production run lengths and overall supply chain per-formance. Current production practices and supply chain policies of an existing company provided the starting point for the experiment. The experiment consisted of two de-ployment scenarios and a range of run length multipliers that vary the company’s actual run length rules. Minimum cost run lengths were determined for twelve combinations of cost assumptions for changeovers and inventories.
Design Specifications of a Generic Supply Chain Simulator
Shigeki Umeda (Musashi University) and Y. Tina Lee (National Institute of Standards and Technology)
This paper describes a design specification for a generic supply chain simulation system. The proposed simulation system is based on schedule-driven and stock-driven control methods to support the supply chain management. The simulation system includes three processing modes: business process flows, material process flows, and information process flows. The paper also discusses interface data requirements for the proposed supply chain simulation system.
Simulation, a Framework for Analysing SME Supply Chains
PJ Byrne and Cathal Heavey (University of Limerick)
The following paper briefly presents the formulation and development of a case study supply chain simulation model as developed for an industrial company. The case study company in question is considered to be a vertically integrated organisation, offering a complete range of its related industries products to a global marketplace. The paper reviews the scale of supply chain system being analysed, the type of data required to populate such a model and the performance outputs from the model. These outputs include the percentage of demand that is both On Time and In Full (OTIF%), the days of inventory held in finished stock and also the finished stock quantities. The paper also reviews the scope of such a model by reviewing some of the experimental work as carried out on this model and highlights the usefulness of such a model as an aid to supply chain decision making in a SME.
Tuesday 8:30:00 AM 10:00:00 AM
Information Modeling for Manufacturing Simulation
Chair: Jayendran Venkateswaran (University of Arizona)
Garment manufacturers usually work with a short vision of the demand to come in the following months. So they want to borrow as little as possible while still making a good profit at the end of the year. This study models a garment manufacturer’s cash flow with the objective of finding sce-narios where the company will be employing a low level of its credit-line and still be making a reasonable profit. To model our problem, we use Silk, an object-oriented simula-tion library in Java. Input data from a small-sized garment manufacturing company is used to build and test the model. A model where the manufacturer can test decisions like investing on opening new job shops, changing the pro-duction scheduling heuristics, or changing the payment agreements with suppliers and an example usage of the simulation are presented.
Modeling Information for Manufacturing-Oriented Supply-Chain Simulations
Guixiu Qiao and Frank Riddick (National Institute of Standards and Technology)
This paper discusses a new approach that facilitates the use of simulation in supply chain applications, especially for manufacturing-related activities. A neutral information rep-resentation methodology, which is based on the eXtensible Markup Language (XML), referred to as the Manufactur-ing Information Model for Simulation (MIMS), is being developed at NIST to address the needs of information in-tegration and exchange along supply chain applications. This information model can be applied to create a data-driven simulation that supports supply chain optimization. An example of a manufacturing-oriented supply-chain simulation is also discussed.
Minimizing Total Setup Cost for a Metal Casting Company
Xue-Ming Yuan (Singapore Institute of Manufacturing Technology), Hsien Hui Khoo (National University of Singapore), Trevor A. Spedding (University of Greenwich), Ian Bainbridge (University of Queensland) and David M. R. Taplin (University of Greenwich)
The optimizing sequence of production for a set of customer orders - in order to minimize machine setup time and costs - is one of the typical problems found in many manufacturing systems. In this paper, we develop a simulation model to capture a practical system of a metal casting company in Queensland, Australia, and optimize the production sequence for a set of customer orders. The method addressed in the paper can be applied to other optimization problems in manufacturing industry.
Modeling a Garment Manufacturer’s Cash Flow Using Object-Oriented Simulation
José A. Sepúlveda (University of Central Florida) and Haluk M. Akin (Tirol Giyim Ltd)
Tuesday 10:30:00 AM 12:00:00 PM
Simulation for e-Commerce
Chair: Steve Buckley (IBM T.J. Watson Research Center)
A Stochastic On-Line Model for Shipment Date Quoting with On-Time Delivery Guarantees
Yunpeng Pan and Leyuan Shi (University of Wisconsin-Madison)
The paper introduces a new model for shipment date quoting with potential applications in E-commerce. First, a customer sends to the vendor a request for an item advertised at a certain price on the company's web site. Upon receiving the request, the vendor immediately quotes the customer a no-later-than shipment date for the requested item, taking into account the amount of time to produce the item and any outstanding order previously placed but not yet fulfilled. If the quoted date is deemed acceptable, the customer subsequently places an order for the item; otherwise, the customer rejects the quote and looks for an alternative vendor (the deal is thus lost). The back-end of the quoting system is a single server production system. We propose heuristics that account for the intricate combinatorics of the server scheduling problem, as well as the uncertainty in customer demand and customer behavior.
Simulating Availability Outlook for E-Commerce Business of Personal Computer Sales
Young M. Lee (IBM )
For newly designed or transformed business processes, accurately predicting business performances such as costs and customer services before actual deployment is very important. We have successfully developed and used a simulation model for the IBM’s Personal Computer Division by modeling multiple, discrete events such as customer order arrival, replenishment planning and availability data refresh, and uncertainty of demand forecast, order size and customer preference of product feature. Using the model we were able to predict dynamics of availability, ship dates and accuracy of ship date, and identified other opportunities for improvement. We have also studied how different inventory policies, supply planning policies and sourcing policies affect business performance metrics such as inventory and customer services.
Utilizing Simulation to Evaluate Business Decisions in Sense-and-Respond Systems
Paul Huang, Young M. Lee, Lianjun An, Markus Ettl, and Steve Buckley (IBM ) and Karthik Sourirajan (Purdue University)
Simulation can be an effective way to evaluate alternative decisions in Sense-and-Respond systems prior to taking actions to resolve existing or anticipated business situations. In Sense-and-Respond systems, business situations arise within predefined contexts that specify what aspects of the business need to be monitored and what information is needed to make decisions. We have designed a decision support system that dynamically configures simulation models based on business context and interactively presents simulation results to business analysts. In this paper, our decision support system is applied to the IBM Demand Conditioning process, in which mismatches between supply and demand are identified and corrective actions are initiated.
Tuesday 1:30:00 PM 3:00:00 PM
Manufacturing Case Studies
Chair: Guixiu Qiao (NIST)
This paper reports findings of a study of shock absorber assembly line using computer simulation. The shock absorber assembly line feeds shockers to the motorcycle assembly line. The assembly line simulated in this project is located at an OEM for Bajaj Auto Ltd., the largest producers of scooters and motorcycles in India. In this paper, results of simulation are presented from two scenarios. The first is the original layout of the system. The second simulation is the suggested modifications. Data was gathered and evaluated to determine the necessary parameters to be used. The new demand required the OEM to increase its capacity by 200 shock absorbers per day. After implementing the proposed model the daily output increased by 435 shock absorbers. The highlights of our analysis was that this increase in production rate was achieved without any increase in direct labor, contributing to a gross increase in profit by 32%
The Use of Simulation and Design of Experiments for Productivity Improvement in the Sawmill Industry
Felipe F. Baesler, Eduardo Araya, and Francisco Ramis (Universidad del BioBio) and José A. Sepúlveda (University of Central Florida)
This work presents a discrete event simulation model of an important sawmill in Chile. This model was used to per-form a bottleneck analysis of the wood process and to pro-pose, based on these results, alternatives that would yield to an improvement in the process productivity. Different alternatives were simulated and the results obtained were used to perform a full factorial design in order to select the combination of factors that have the most important impact in the process productivity. The implementation of these improvement measures could increase the wood production up to a 25%.
Simulation Modelling for a Bus Manitenance Facility
Manivannan Ramadass, Jay M. Rosenberger, and Brian Huff (The University of Texas at Arlington), Stephanie Gonterman (Greyhound Lines, Inc.) and Rajesh N. Subramanian (Greyhound Lines Inc)
The Greyhound Lines Dallas Maintenance Facility was congested during peak operating periods. A stochastic model of this facility was developed to determine the re-source requirements needed to provide adequate service during periods of peak demand. The structure of the simulation model is described. A representative sensitivity analysis is presented to discuss how this model was used to support facility sizing decisions. Based on our simulation experiments, we concluded that the existing site, with appropriate modifications, could accommodate peak traffic with some room for growth.
Production Capacity Analysis of a Shock Absorber Assembly Line Using Simulation
Nikhil S. Gujarathi, Rohit M. Ogale, and Tarun Gupta (Western Michigan University)