WSC 2002

WSC 2002 Final Abstracts

Applications in Logistics, Transportation, and Distribution Track

Monday 1:30:00 PM 3:00:00 PM
Manufacturing Supply Chain Applications

Chair: Enver Yücesan (INSEAD)

Modeling Computer Assembly Operations for Supply Chain Integration
Sanjay Jain and Ngai Fong Choong (Virginia Tech) and William Lee (Singapore Institute of Manufacturing Technology)

Factory operations have been modeled for years to understand the relationship between the different design and policy factors and the performance measures of interest. The increasing awareness of the need to manage factories as a link in the supply chain places a corresponding requirement for an enhanced approach for factory modeling. This paper describes the modeling of a computer assembly factory for supply chain integration by including aspects of inbound and outbound logistics and relevant business processes. Lessons are drawn based on the experience.

AI-Based Optimization for Fleet Management in Maritime Logistics
Agostino Bruzzone, Alessandra Orsoni, Roberto Mosca, and Roberto Revetria (University of Genoa)

This paper outlines the features of an automated Decision Support System (DSS) developed to optimize the logistics of maritime transportation for a large chemical company. The paper focuses on the design and implementation of an optimization module to complement a DSS architecture including dynamic databases, decision heuristics, and dynamic process simulation, for the systematic generation of cost-effective fleet configurations capable of meeting the company's production requirements.

Investigation of Influence of Modeling Fidelities on Supply Chain Dynamics
Jayendran Venkateswaran and Young-Jun Son (The University of Arizona) and Boonserm Kulvatunyou (NIST)

In this paper, a three-echelon supply chain model is analyzed to determine strategies to reduce the supply chain system dynamics. Uniqueness of this research stems from the use of multiple models with varying degrees of detail representing the same supply chain. The significance of a detailed supply chain model on the quality of result is made clear. Factors employed to build an abstract to a detailed model include: transportation and production delay, demand at the retailer, and production and transportation capacity. It is shown that the system dynamics itself varies with increasing detail in the model. In addition, it is examined to see if a strategy found effective in improving the system dynamics with an abstract model is effective with a detailed model. It is established that the strategy found to be the most effective on an abstract model is not always the best strategy for the real supply chain.

Monday 3:30:00 PM 5:00:00 PM
Transportation Applications of Simulation

Chair: Sirish Joshi (Perseco)

Simulation Reduces Airline Misconnections: A Case Study
Suna Hafizogullari, Prathi Chinnusamy, and Cenk Tunasar (TransSolutions)

With most major airlines operating a hub-and-spoke system and partnering with other airlines to offer code share flights, more and more passengers are required to make at least one connection before reaching their final destination. These trends in the airline industry have increased the percentage of transfer passengers. In order to minimize the number of missed connections and offer customers a seamless journey, airlines must maintain time limits in which domestic and international transfer passengers can reach their connecting gates at the airports. This paper focuses on how simulation is used to evaluate an airline’s minimum connect time criteria with respect to the design and operational policies at its hub airports. We consider a case study of Delta Air Lines’ new planned state-of-the-art facility at John F. Kennedy International Airport to illustrate the significant role simulation played in the planning stages of an airport design.

Simulation Building Blocks for Airport Terminal Modeling
Alexander Verbraeck and Edwin Valentin (Delft University of Technology)

Airports are an ideal application area for simulation. The processes are in a continuous state of change, are complex and stochastic, involve many moving objects, and require a good performance that can be measured in several different performance indicators. Within airports, but also between airports, the same kind of questions are answered over and over again. Often, however, new simulation models are built for each question, if possible copying some parts of previous models. Structured reuse of simulation components is rarely seen. This paper shows an approach for airport terminal modeling that departs from the assumption that reusable simulation building blocks can form the core of a powerful airport modeling tool, which is able to answer different questions at airports better and faster than traditional models. The building blocks have been implemented in the commercially available simulation language eM-Plant. Several studies carried out with this library were very successful.

The Application of Distributed Simulation in TOMAS: Redesigning a Complex Transportation Model
Mark B. Duinkerken, Jaap A. Ottjes, and Gabriel Lodewijks (Delft University of Technology)

This paper describes the application of distributed discrete event simulation in the study of an automated container terminal. The new model was developed to continue the study of large and complex logistic systems. In a previous study, a stand-alone model of the terminal was used that included all the characteristics of container handling between the ships and the container stack. A new distributed simulation model was developed by decomposing the original model into a distributed structure of communicating, small sub models. It is shown that with relative little effort and hardly any programming overhead, a complex stand-alone model can be decomposed into small, easy to understand sub models. The new distributed structure improves the transparency and maintainability of the simulation model, while guaranteeing the original benefits of the stand-alone model and the required reproducibility of the experiments.

Traffic Simulation Application to Plan Real-Time Distribution Routes
Oscar Franzese (Oak Ridge National Laboratory) and Shirish Joshi (Perseco)

This paper studies the effect of real-time information on optimal routes employed by distribution vehicles that supply goods from distribution centers to the stores in any retail environment. This methodology uses simulation models to mimic actual traffic conditions as functions of times of the day along the distribution routes to suggest meta-optimal routes over the ones provided by the routing algorithms. This yields optimized routes based on the times of the day in addition to aiding the planner in sequencing the routes to increase driver productivity and decrease operat-ing costs.

Tuesday 8:30:00 AM 10:00:00 AM
Advanced Aviation Concepts via Simulation

Chair: Lisa Ann Schaefer (The MITRE Corporation)

Techniques to Enhance Performance of an Existing Aviation Simulation
David Carnes and Frederick Wieland (The MITRE Corporation)

Facing a need to run large aviation models more quickly than the one to two days currently required, the MITRE Corporation undertook an effort to reduce the execution time of one such simulation. Only solutions requiring minimal changes to the code base were considered. This paper describes the approaches taken to increase the speed of the original sequential simulation by employing more efficient algorithms and parallel processing technology. Specifically, an implementation of a new technique for parallel proximity detection provided an 80% reduction in the time spent checking for conflicts. In addition, implementation of a thread pool that enables the movement of multiple aircraft in parallel resulted in a 10%-15% reduction in the overall execution time of the simulation.

Research Flight Simulation of Future Autonomous Aircraft Operations
Mario S.V. Valenti Clari, Rob C.J. Ruigrok, Bart W.M Heesbeen, and Jaap Groeneweg (National Aerospace Laboratory NLR)

A key element in the development and innovation of future aviation concepts and systems is research flight simulation. Research flight simulation is applied when the performance and perception of human pilots is a key measure of the overall assessment. This paper will give an overview of the research simulation set-up of the National Aerospace Laboratory (NLR), Amsterdam, the Netherlands, which is used for the human-in-the-loop evaluation of future operational concepts. Special attention is given to the research topic of Airborne Separation Assurance; often referred to as Free Flight. The presented set-up has proven to be a flexible evaluation tool for assessing human-in-the-loop performance when operating in a simulated future autonomous aircraft environment.

A Simulation Study to Investigate Runway Capacity Using TAAM
Massoud Bazargan, Kenneth Fleming, and Prakash Subramanian (Embry - Riddle Aeronautical Uinversity)

This study outlines a method to evaluate runway layouts using simulation, to aid in the airport planning and decision making process. As a sample study, the maximum throughput capacities of proposed expansion alternatives at Philadelphia International Airport (PHL), constrained at varying levels, are identified. The objective is to compare these ultimate airport capacities achievable for each of the different layouts to estimate their respective efficiencies in terms of runway system utilization. TAAM (Total Airspace and Airport Modeller) is used to simulate each proposed alternative given its capabilities for modeling at a very high level of detail and closely representing reality in terms of applicable separation standards and air traffic control procedures.

Decision Support for Advanced Aviation Concepts
Lisa A. Schaefer, Leonard A. Wojcik, Thomas P. Berry, and Craig R. Wanke (The MITRE Corporation)

This paper describes The MITRE Corporation Center for Advanced Aviation System Development (CAASD) research towards simulation of advanced aviation concepts. Research activities are aimed toward improving tactical and strategic decision making methods in the near and long term. We describe how CAASD simulation capabilities assist in determining how to achieve our goals for improving tactical and strategic decision making. For the long term, our simulation capabilities are becoming more agent-based.

Tuesday 10:30:00 AM 12:00:00 PM
Simulation Applications in the Automotive Industry

Chair: Shang-Tae Yee (General Motors R&D)

Simulation Anywhere Any Time: Web-Based Simulation Implementation for Evaluating Order-to-Delivery Systems and Processes
Soundar R.T. Kumara, Yong-Han Lee, Kaizhi Tang, and Chad Dodd (The Pennsylvania State University) and Jeffrey Tew and Shang-Tae Yee (GM R&D Center, Enterprise Systems Lab.)

GM Enterprise Systems Laboratory (GMESL) has developed a stand-alone single user simulation program for evaluating and predicting Order-to-Delivery (OTD) systems and processes. In order for more people to be able to access this simulator, to share the simulation results, and to analyze simulation collaboratively, we have designed, developed and implemented an Internet-based three-tiered client/server framework, which consists of the three tiers: database, execution and user interface. The corresponding components are: database server, execution server, and web based user interface. The relational database server enables users to interact with the persistent data sets for simulation study and maintains data integrity. The multi-agent based execution server guarantees stable user responsiveness by virtue of multi-agent’s flexible architecture, accordingly achieving a high level of processing scalability. Finally the web-based graphical user interface helps users to easily conduct the simulation study from anywhere at any time, and the visual simulation analysis tool helps users to make decisions effectively.

Establishment of Product Offering and Production Leveling Principles via Supply Chain Simulation under Order-to-Delivery Environment
Shang-Tae Yee (General Motors R&D)

In support of the order-to-delivery (OTD) business initiative, a simulation framework has been developed at GM R&D. The OTD simulation program is aimed at simulating the behavior of the OTD supply chain using detailed inputs associated with demand, supply, and production processes. Early capture of customer demand fluctuation enables GM to effectively reduce aggregate mismatch between production and sales and appropriate time series models have been suggested to capture demand patterns based on actual data. The vehicle model and option mix with a given demand variation influences the performance of the OTD supply chain and provides a means to establish certain principles determining the extent of product offering and the scope of production leveling. Analyzing the impact of the model and option mix on primary supply chain performance measures, such as customer wait time, condition mismatch, and parts usage, capacitates reduction of the mismatch between demand and production and stabilizes supply chain operations.

Sequencing Production on an Assembly Line Using Goal Chasing and User-Defined Algorithm
Arvind Mane, Saeid Nahavandi, and Jingxin Zhang (Deakin University)

An Australian automotive component company plans to assemble and deliver seats to customer on just-in-time basis. It plans to assemble various seat types on one assembly line. Mixed-Model sequencing is very important if a company has to assemble seats in just-in-time environment. Toyota Motor Company’s goal chasing algorithm I and a user-defined algorithm are used sequence seats on assembly line. Discrete event simulation software is used to model the assembly operations of seat plant. Both algorithms are programmed to generate a sequence for the seat plant. Model results show both algorithms can sequence seats on the assembly line and each algorithm has its advantages and disadvantages.

Tuesday 1:30:00 PM 3:00:00 PM
Warehousing and Inventory Management

Chair: Luis Rene Contreras (University of Texas at El Paso)

A Simulation Tool to Determine Warehouse Efficiencies and Storage Allocations
Joseph G. Macro and Reino E. Salmi (Macro Solutions, Inc.)

Using ProModel simulation language, a universal warehouse storage simulation model has been developed. Applications of the model have been executed with success to analyze the storage capacity and rack efficiency of a medium volume, low stock-keeping unit (SKU) warehouse and a medium volume, large SKU warehouse. The model is scaleable and can be modified to simulate any warehouse configuration, including selective racks, bulk floor storage, push-back, flow-through, drive-in and drive-through racks.

A Simulation Model to Validate and Evaluate the Adequacy of an Analytical Expression for Proper Safety Stock Sizing
Eduardo Saggioro Garcia and Caio Fiuza Silva (Department of Industrial Engineering / UFRJ) and Eduardo Saliby (COPPEAD / UFRJ)

The purpose of this paper is to validate and test the adequacy of an analytical expression to calculate proper safety stock levels using simulation techniques. The model refers to a periodic review system and a lot-4-lot replenishment policy, with randomness in forecast errors and in order fulfillment. The simulation model is formulated in a spreadsheet environment using MS Excel® and @Risk®. The percentage of periods without stockout is computed and compared to the theoretical value expected by the assumptions inherent to the analytical expression.

Integrating Simulation Modeling and Equipment Condition Diagnostics for Predictive Maintenance Strategies – A Case Study
Luis Rene Contreras, Chirag Modi, and Arunkumar Pennathur (University of Texas at El Paso)

This paper presents results from a case study in predictive maintenance at a distribution warehouse. A simulation model was built with ARENA 5.0 for integrating predictive maintenance strategies with production planning strategies, for a conveyor system. Equipment health was monitored using condition-based parameters such as temperature and vibration for mechanical and electrical components such as rollers, electrical motors, and gearboxes. This diagnostic information was then integrated with a simulation model to simulate various equipment breakdown and failure conditions. Integration of condition-based monitoring of conveying equipment with a simulation model of the distribution system has provided a useful analytical tool for management to reduce production downtime due to unplanned maintenance activities. In this instance, downtime was reduced by more than 50% and work in process inventory was reduced by more than 65%.

Tuesday 3:30:00 PM 5:00:00 PM
Maufacturing Supply Chain Applications 1

Chair: Jeffrey A. Joines (North Carolina State University)

Decision Support Tool – Supply Chain
Christian Wartha and Momtchil Peev (ARC Seibersdorf Research) and Andrei Borshchev and Alexei Filippov (XJ Technologies)

We present a recently developed Decision Support Tool - Supply Chain (DST-SC). This is a specialized domain oriented tool, which is an extension of the general purpose, UML-RT Hybrid Simulation kernel of AnyLogic by XJ Technologies. DST-SC allows high degree of flexibility with respect to the supply chain functionality being modeled, has the ability to handle large complex problems, and offers highly reusable model components, offering at the same time ease of use by non-experts in simulation. Typical features of DST-SC are interoperability with third-party software (DB, GIS, PPS), platform-independence as well as potential for concurrent use by a geographically distributed group.

Capacity and Backlog Management in Queuing-Based Supply Chains
Edward G. Anderson and Douglas J. Morrice (The University of Texas at Austin)

In this paper, we model and analyze a type of two-stage serial supply chain often found in service sector and make-to-order manufacturing industries. The chain holds no finished goods inventory at either stage. Rather, processing occurs only after an order is received and backlogs are managed solely by adjusting capacity. We model this supply chain using a tandem queuing model. Our analysis considers the impact of changes in first stage lead-time and capacity adjustment time on backlog, waiting time, and capacity variances at both stages. The results can be used to support the argument for better coordination across stages in these types of supply chains.

Supply Chain Multi-Objective Simulation Optimization
Jeffrey A. Joines, Deepak Gupta, Mahmut Ali Gokce, Russell E. King, and Michael G. Kay (North Carolina State University)

A critical decision companies are faced with on a regular basis is the ordering of products and/or raw materials. Poor decisions can lead to excess inventories that are costly or to insufficient inventory that cannot meet its customer demands. These decisions may be as simple as "How much to order" or "How often to order" to more complex decision forecasting models. This paper addresses optimizing these sourcing decisions within a supply chain to determine robust solutions. Utilizing an existing supply chain simulator, an optimization methodology that employs genetic algorithms is developed to optimize system parameters. The performance measure that is optimized plays a very important role in the quality of the results. The deficiencies in using traditionally used performance measures in optimization are discussed and a new multi-objective GA methodology is developed to overcome these limitations.

Wednesday 8:30:00 AM 10:00:00 AM
Manufacturing Supply Chain Applications 2

Chair: Brett Marc Duarte (Arizona State University)

Logistic Simulator for Steel Producing Factories
Steven C. Hamoen and Dirk-Jan Moens (Incontrol Enterprise Dynamics)

The logistic processes in most steel producing plants are very complex. To assist the decision makers in steel producing plants, Incontrol Enterprise Dynamics have developed for and in cooperation with SMS Demag in Germany, a simulator that can be used to rapidly model any steel plant. The Steel Plant Simulator has been built using the software package Enterprise Dynamics® and allows for rapid insight into the influences of layout changes, process and speed parameters, length of production runs, changes in planning and type of products that are being produced. The Simulator incorporates a dynamic scheduler to create a realistic production planning. Results include production Gantt charts, time-path diagrams, utilization figures and production statistics.

Development of Distributed Simulation Model for the Transporter Entity in a Supply Chain Process
Richard J. Linn, Chin-Sheng Chen, and Jorge A. Lozan (Florida International University)

Transporter is a critical part of Supply Chain integration. An international transporter process involves multiple ground pickup and delivery operations, package sorting and palletizing, airport operations and air transport. This paper describes a successful two-machine implementation of a distributed simulation model for an international transportation system in a supply chain network operation using Run Time Infrastructure of High Level Architecture software developed by the Defense Modeling and Simulation Office, the Distributed Manufacturing Simulation Adapter developed by the National Institute of Standards and Technology, and ARENA simulation tool. By incorporating the capabilities provided by these tools, it was successful to establish the information flow exchange between the machines where one machine houses transporter while the other has suppliers, customers, and distribution centers located in different parts of world. This research tool attempts to facilitate the development of distributed simulations so they can be used to analyze and solve manufacturing related problems.

Parameterization of Fast and Accurate Simulations for Complex Supply Networks
Brett Marc Duarte, John W. Fowler, Kraig Knutson, Esma Gel, and Dan Shunk (Arizona State University)

More efficient and effective control of supply networks is conservatively worth billions of dollars to the world economy. Adopting an approach by which the basic disciplines of Industrial Engineering, Control Engineering, System Simulation and Business Re-Engineering are integrated into one comprehensive system has been known to produce impressive results. This paper discusses a modular approach to develop a discrete event simulation model that has the appropriate level of abstraction to capture the inherent complexities that exist in a supply chain and is yet simple, fast and produces results of high fidelity. It discusses a method to parameterize each module by finetuning a few parameters to make it represent an entire factory, a warehouse or a transportation link.

Wednesday 10:30:00 AM 12:00:00 PM
Manufacturing Supply Chain Applications 3

Chair: Gloria J. Giacaman (Universidad Católica del Norte)

Multi-Agent Simulation of Purchasing Activities in Organizations
Mark J.R. Ebben, Luitzen de Boer, and Corina E. Pop Sitar (University of Twente)

In this paper we present a Multi-Agent simulation model to investigate purchasing activities in an organizational environment. The starting point is the observation that the majority of purchasing activities in organizations is usually performed without any involvement of the organization’s purchasing department. The purpose of the experiments is to investigate if and how certain factors determine the degree to which Purchasing professionals become involved in the purchasing of Non-Product Related (NPR) items and services. Among the factors investigated are: corporate purchasing policies, available information, and the nature of the various purchasing activities. Preliminary results show that the behavior of the multi-agent simulation model is an acceptable representation of reality. Furthermore, the results show the limits of a Purchasing department’s added value and the important role of organizational learning in that respect. The paper provides directions for further research.

Efficient Simulations of Supply Chains
Dieter Armbruster, Daniel Marthaler, and Christian Ringhofer (Arizona State University)

High volume production flows are modeled by nonlinear hyperbolic partial differential equations representing conservation laws. These models have Little's law explicitly built into the formulation. Borrowing from concepts in gas dynamics and vehicular traffic models we derive several prototypical equations representing linear as well as re-entrant factories. Multiple products, dispatch policies and control actions can be modeled. Standard hydrodynamic codes provide very fast simulations of these models allowing us to link them together to form efficient supply chain simulations.

Simulation of the Material Transporting and Loading Process in Pedro de Valdivia Mine
Gloria J. Giacaman, Rodrigo P. Medel, and Jorge A. Tabilo (Universidad Católica del Norte)

This paper describes the application of simulation techniques in the forecast behavior of a material handling system, which takes place in Pedro de Valdivia Nitrate Mine in Chile. The main goal of the study was to determine the way a change in the size of loading and carrying fleets would affect the total production of the system which is measured in term of the quantity of material that is monthly carried from quarries to stock piles.

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