WSC 2008

WSC 2008 Final Abstracts

Manufacturing Applications Track

Monday 10:30:00 AM 12:00:00 PM
Input Data and Validation

Chair: Guodong Shao (National Institute of Standards and Technology)

A New Procedure Model for Verification and Validation in Production and Logistics Simulation
Markus Rabe (Fraunhofer IPK), Sven Spieckermann (SimPlan AG) and Sigrid Wenzel (Universitaet Kassel)

Verification & Validation of simulation models and results has been strongly investigated in the context of defence applications. Significantly less substantial work can be found for applications for production and logistics, which is surprising when taking into account the massive impact that wrong or inadequate simulation results can have on strategic and investment-related decisions for large production and logistics systems. The authors have, therefore, founded an expert group for this specific topic in the year 2003, which has analysed the existing material and then developed proposals for definitions, overviews on existing V&V techniques, practical hints for the documentation of the procedural steps within a simulation study, and a specific procedure model for V&V in the context of simulation for production and logistics. The results of this working group are available as a textbook, in German. This paper summarises major results.

A Methodology for Input Data Management in Discrete Event Simulation Projects
Anders Skoogh and Björn Johansson (Chalmers University of Technology)

Discrete event simulation (DES) projects rely heavily on high input data quality. Therefore, the input data management process is very important and, thus, consumes an extensive amount of time. To secure quality and increase rapidity in DES projects, there are well structured methodologies to follow, but a detailed guideline for how to perform the crucial process of handling input data, is missing. This paper presents such a structured methodology, including description of 13 activities and their internal connections. Having this kind of methodology available, our hypothesis is that the structured way to work increases rapidity for input data management and, consequently, also for entire DES projects. The improvement is expected to be larger in companies with low or medium experience in DES.

A Discrete Event Simulation Model for Reliability Modeling of a Chemical Plant
Bikram Sharda and Scott Bury (The Dow Chemical Company)

This paper discusses a discrete event simulation model developed to identify and understand the impact of different failures on the overall production capabilities in a chemical plant. The model will be used to understand key equipment components that contribute towards maximum production loss and to analyze the impact of a change policy on production losses. A change policy can be classified in terms of new equipment installation or increasing the stock level for the failure prone components. In this paper, we present the approach used and some preliminary results obtained from available data.

Monday 1:30:00 PM 3:00:00 PM
Balancing and Bottleneck Detection

Chair: Ander Skoogh (Chalmers University of Technology)

A New Method for Bottleneck Detection
Sankar Sengupta (Oakland University), Kanchan Das (East Carolina University) and Robert VanTil (Oakland University)

This paper presents a new method to identify and rank the bottlenecks in a manufacturing system. The proposed method is based on performance related data that are easy to capture, offers low computational burden and less prone to be in error due to its simplicity. The proposed method analyzes inter-departure time from different machines to identify and rank the bottlenecks. In a follow-up paper the authors plan to present a method to allocate loss of production to different machines based on analysis of inter-departure time. This paper also proposes a set of rules that may be used to improve data integrity. The proposed method may be used to analyze both steady state as well as non-steady state data and can be extended easily to analysis of a job shop.

Metodology for Selecting the Best Suitable Bottleneck Detection Method
Eliseu Lima and Leonardo Chwif (Escola de Engenharia Maua) and Marcos Ribeiro Pereira Barretto (Universidade de São Paulo)

Focusing on process constraints (or bottlenecks) is how companies are improving productivity, decreasing response times. However, a bottleneck is not easily detectable, especially when conventional bottleneck methods are used. This work presents a method, based on simulation, to help the selection of the bottleneck detection method to be applied to a given situation. The methodology extends previous works on the subject, mainly those by Roser, Nakano and Tanaka (2002) and Roser, Nakano and Tanaka (2003). The proposed method was successfully applied to a real bottling process.

Mixed Model Assembly Line Balancing Problem with Fuzzy Operation Times and Drifting Operations
Weida Xu and Tianyuan Xiao (National CIMS Engineering Research Center)

Assembly line balancing problem (ALBP) means assigning a series of task elements to uniform sequential stations under certain restrictions. This paper considers a special type of assembly line balancing problem with mixed models, fuzzy operation times and drifting operations, which has the objective of minimizing the total work overload time. According to chance constrained programming, a fuzzy alpha total work overload time minimization model is built. Moreover, fuzzy simulation and genetic algorithm are integrated to design a hybrid intelligent algorithm to solve the above model. Finally, Extensive computational results are reported to demonstrate the efficiency and effectiveness of the algorithm.

Monday 3:30:00 PM 5:00:00 PM
Standards and Model Building

Chair: Salla Lind (VTT, Technical Research Centre of Finland)

Automating the Development of Shipyard Manufacturing Models
Gabriel A. Burnett, Daniel A. Finke, D.J. Medeiros, and Mark T. Traband (The Pennsylvania State University)

Simulation results are often needed within a short time frame, while the development of simulation models can be time consuming. We develop a methodology to facilitate rapid generation of simulation models from an enterprise database. Data is communicated between Product Lifecycle Management (PLM) software and Flexsim using a standard Microsoft Excel format. We have developed a custom Flexsim interface and software-specific model generator that creates a discrete event simulation model from the PLM input data. Preliminary results show that the methodology can reduce the cost of simulation model generation while simultaneously improving the accuracy of generated models. This work highlights the benefits of automatic model generation techniques, describes a shipbuilding implementation of the methodology, and provides direction for future work.

Representing Layout Information in the CMSD Specification
Frank Riddick and Yung-Tsun Tina Lee (National Institute of Standards and Technology)

Developing mechanisms for the efficient exchange of information between simulations and other manufacturing tools is a critical problem. For many areas of manufacturing, neither representations for the information nor mechanisms for exchanging the information have been agreed upon. Manufacturing plant layout is one such area. The Core Manufacturing Simulation Data (CMSD) specification is being developed to address some of these issues, through the definition of neutral representations for the “core” manufacturing entities that need to be exchanged between simulations and other applications, through the creation of a Unified Modeling Language information model that defines the relationships between the core manufacturing entities, and through the definition of eXtensible Modeling Language Schemas based on the information model to facilitate the exchange of information that adheres to the model. This paper describes an effort to extend the CMSD specification to cover the definition and exchange of layout information.

Tuesday 8:30:00 AM 10:00:00 AM

Chair: Matias Urenda Moris (University of Skövde)

Emulation in Manufacturing Engineering Processes
Hironori Hibino (JSPMI)

In our research, the manufacturing system emulation technology is proposed as one of the frontloading methods in the manufacturing system implementation phase. In this paper, the roles of the manufacturing system emulation technology in manufacturing engineering processes are summarized based on our analysis for the typical manufacturing engineering processes. The manufacturing system emulation environment (MSEE) to implement the manufacturing system emulation is proposed and developed. MSEE consists of our developed manufacturing cell emulator, our developed soft-wiring system, and the industrial network middleware which is one of the semi-standard middlewares. The validation of our proposed environment was carried out through a case study.

Architecture for Modeling, Simulation, and Execution of PLC Based Manufacturing System
Devinder Thapa, S.C. Park, Gi-Nam Wang, and C. M. Park (Ajou University) and Hee Han Kwan (Gyeongsang National University)

In this paper, we propose an integrated architecture for modeling, simulation, and execution of PLC (Programmable Logic Controller) based manufacturing system. The main objective is to integrate the high level modeling, simulation, and device level executable code generation. This architecture can improve the fidelity between high level system model and lower level PLC controlled devices. In this paper, we model the shop floor controller system using DEVS (Discrete Event System Specification) formalism, subsequently, simulate the model and generate SOP (sequence of operations). We added two algorithms in conventional DEVS, the first algorithm makes an interface between 3D graphic model and DEVS model, whereas, the second algorithm generates SOP. As a result, the generated SOP can be mapped with PLC I/O (Input/Output) address to generate an executable controller code. For the purpose of further validation and implementation, the generated program can be downloaded to software or hardware PLC.

Offline Commissioning of a PLC-Based Control System Using Arena
Jeffrey S Smith and Younghol Cho (Auburn University)

In this paper, we address a generalized method of mapping a control system simulation model to the PLC emulator being tested using model variables and PLC tags under the offline commissioning environment. For this research we created an example system similar to a high speed packaging system described in a previous WSC paper. Implementation experience using Rockwell Software applications is provided.

Tuesday 10:30:00 AM 12:00:00 PM

Chair: Sanjay Jain (The George Washington University)

Optimized Maintenance Design for Manufacturing Performance Improvement Using Simulation
Ahad Ali (Lawrence Technological University), Xiaohui Chen (Chongqing University), Ziming Yang (University of Michigan – Ann Arbor), Jay Lee (University of Cincinnati) and Jun Ni (University of Michigan – Ann Arbor)

This research presents optimized maintenance design using simulation to analyze the capability of auto part manufacturing production system. The integration of simulation and optimization is used to identify critical stations, an optimal system design and maintenance scheduling schemes and evaluates their effects on the overall system performance. Most emphasis is focused on the impact on system by individual station reliability and the fluctuation of maintenance availability. The proposed simulation and optimization for maintenance design is validated through real-life application. This simulation modeling and optimization could help for manufacturing performance improvement.

Simulation and Mathematical Programming for a Multi-Objective Configuration Problem in a Hybrid Flow Shop
Pierpaolo Caricato, Antonio Grieco, and Francesco Nucci (University of Lecce, Dep. of Innovation Engineering)

This paper introduces an application of simulation-based multi-objective optimization to solve a system configuration problem in a hybrid flow shop system. The test case is provided by a firm that manufactures mechanical parts for the automotive sector. We present an architecture that uses both discrete-event simulation and mathematical programming tools in order to solve the problem. The multiple-objective nature of the problem is preserved throughout the proposed approach, using Pareto-dominance concepts both to eliminate inefficient solutions within the proposed solution algorithm and to provide the user with efficient solutions. Mathematical programming is used to cull the required number of simulation runs. Computational results obtained using a real-world case study are reported. The proposed approach is benchmarked against a general purpose simulation-optimization engine in order to prove its effectiveness.

A Comparative Study of Genetic Algorithm Components in Simulation-Based Optimisation
Birkan Can (Enterprise Research Centre, University of Limerick), Andreas Beham (Upper Austria University of Applied Sciences) and Cathal Heavey (Enterprise Research Centre, University of Limerick)

In this paper, we present a comparative study of different stochastic components of genetic algorithms for simulation-based optimisation of the buffer allocation problem. We explore the effects of elements such as operators, fitness assignment strategies and elitism. Three different recombination operators, incorporated with constraint handling mechanisms such as repair and penalty functions, are examined. Under the shed of the experiments, we incorporate problem specific knowledge to further enhance the practicality of GA in decision making for buffer allocation problem.

Tuesday 1:30:00 PM 3:00:00 PM

Chair: Ed Williams (Production Modeling Corporation)

Applying a Simulation-Based Tool to Productivity Management in an Automotive-Parts Industry
Adrián Aguirre (Industrial Engineering Department (FIQ-UNL)), Enrique Müller and Sebastián Seffino (Industrial Engineering Department (FIQ-UNL)) and Carlos Alberto Méndez (INTEC (UNL-CONICET))

This work presents the development and application of an advanced modeling, simulation and optimization-based framework focused on the production process of a basic element of a internal combustion engine which is supplied by a leading factory in the Latin-American market. Lying on the concepts of the process-interaction approach, the principal components available in the discrete event simulation environment “SIMUL8” were used to achieve the best representation of this complex manufacturing system. Furthermore, advanced SIMUL8’s Visual Logic tools were utilized for modeling specific design and operation features arising in the process under study. The developed tool provides a support system for making operative, tactical and strategic decisions, allowing the evaluation of possible scenarios ranging from different operation schemes to potential alternatives of investment. The principal aim of this work is to provide a systematic methodology to improve the productive capacity management, enhancing the process profitability and the degree of customer satisfaction.

Emergence of Simulations for Manufacturing Line Designs in Japanese Automobile Manufacturing Plants
Minh Dang Nguyen and Soemon Takakuwa (Nagoya University)

The aim of this research is to introduce the reader to a new perspective on the framework for designing a manufacturing line project in Japanese automobile manufacturing plants. All manufacturing aspects, manual, automated and hybrid manufacturing lines are considered; however, which line should be used for the factory is always under investigation within the factory. Simulation studies that include resource utilization, line productivity and manufacturing costs help to identify the most suitable manufacturing line type within a factory. By utilizing simulation studies, designers can make reliable decisions upon suitable manufacturing lines faster than conventional methods based upon engineering experience. In order to understand the framework of manufacturing line design, a project to design a new automobile component manufacturing line was investigated in this study, and the chosen manufacturing line was also checked by the manufacturing activities in the factory.

Simulation Based Evaluation of the Workload Control Concept for a Company of the Automobile Industry
Patrick Kirchhof, Nicolas G. Meseth, and Thomas Witte (University of Osnabrueck)

This paper describes a simulation study conducted for a company of the German automobile supply industry facing the need to improve delivery reliability. The intention of the study was to evaluate whether Workload Control (WLC) is applicable as production control policy for this company and whether improvement can be expected. Therefore the regarded shop floor was modeled being organized as a WLC production system. Both, the structural and quantitative model components of the developed simulation model are explained in depth. Furthermore it is shown how inherent parameters of the WLC concept can be set using the simulation model in a practical environment. As due date compliance is the primary concern of the company, the performance of four simple priority dispatching rules is analyzed with regard to delivery reliability. As a result it is shown that WLC is applicable in the given situation and that performance enhancements can be expected.

Tuesday 3:30:00 PM 5:00:00 PM
System Design 1

Chair: Deogratias Kibira (National Institute of Standards and Technology)

A Proposal for Coordinator Control Recipe in a Batch Process
Jose Francisco Briones de la Torre (Universidad Politecnica de Aguascalientes) and Antonio Espuña Camarasa and Luis Puigjaner Corbella (Universidad Politecnica de Cataluña)

In this work, we propose a coordinator control recipe in the context of a batch process with the use of elements of petri nets and some techniques associated with non linear control (e.g. the relative degree) focused to explain the implications of use a hybrid dynamical models in terms of problem control and its relation with on-line experimental measures and the norm ISA S88.02

Clarifying Conwip Versus Push System Behavior Using Simulation
Silvanus T. Enns and Paul Rogers (University of Calgary)

This research examines the performance of CONWIP versus “push” workload control in a simple, balanced manufacturing flowline. Analytical models and simulation experiments are used to evaluate the tradeoffs between throughput and inventory performance. Tradeoff curves based on inflating the inventory level for the CONWIP system and the arrival rate for the “push” system are generated. As well, the variability of interarrival and processing times are considered as experimental factors. Results show that, contrary to what some previous studies have indicated, CONWIP efficiency is not inherently superior to “push” system efficiency. Instead, the release mechanism used for the “push” system has a significant impact on which system will perform better. Utilization levels and processing time variability also affect the relative performances.

Tradeoffs in Building a Generic Supply Chain Simulation Capability
Sanjay Jain (The George Washington University)

Building a simulation model for any large complex system requires high expertise and effort. These requirements can be reduced through building generic simulation capability that includes artifacts for facilitating the development of the simulation model. The artifacts can have a range of capabilities depending on the design goals for the simulation. This paper focuses on issues to be considered in building a generic simulation capability for supply chains. A number of approaches used in recent years for building generic supply chain simulation capability are discussed. Such approaches include data-driven simulators, interactive simulators, and sub-models for supply chain components. Tradeoffs are identified that should be considered in selecting an approach for building a generic supply chain simulation capability.

Wednesday 8:30:00 AM 10:00:00 AM
System Design 2

Chair: Mark Aufenange (University of Paderborn)

A Simulation Based System for Analysis and Design of Production Control Systems
Corinne MacDonald and Eldon Gunn (Dalhousie University)

We present aspects of a simulated based system for analyzing and designing production control systems. The core of the system is a simulation of a manufacturing system operating with the Production Authorization Card system. The simulation model is fast and flexible, making it attractive for generating large datasets for use in developing simulation metamodels of expected performance for a wide variety of production configurations. Details of the simulation system are provided, along with a discussion of the issues to be considered when using it to design production control systems.

The Use of Simulation for Process Improvement in Metal Industry - Case Ht-lasertekniikka
Toni Petteri Ruohonen (University of Jyväskylä)

Companies in the metal industry want to find solutions for increasing the quality of service and productivity of the operation, but it is not an easy task to do, especially if the company is large (has several different production units) and in addition uses many different metal types as material. This paper examines the centralization of special metal production into a single unit instead of several units. The research method is simulation and the main concentration is on finding out the effects and the possible benefits of the centralization scenario. Two different simulation models are constructed for the study. The results of the simulation runs showed that the centralization would increase the utilization of a selected unit only 3,12 % which means that it could be easily carried out. The results also indicated that the centralization scheme could improve the operation significantly (elimination of operational and logistics phases).

Iterative Use of Simulation and Scheduling Methodologies to Improve Productivity
Karthik Krishna Vasudevan, Edward John Williams, Ravi Lote, and Onur M. Ulgen (PMC)

Experienced and wise industrial engineering educators and practitioners have long understood that industrial engineering is a coherent discipline encompassing techniques that work best synergistically, not a motley collection of specialized techniques each isolated in a separate chimney. As an example of the synergies which industrial engineering can bring to process improvement in a production environment, this case study presents the integrated use of process simulation, production scheduling, and detailed analysis of material-handling methods and their improvement. The study undertook the identification and improvement of production and scheduling policies to the benefit of a manufacturing process whose original throughput capacity fell significantly short of high and increasing demand.

Wednesday 10:30:00 AM 12:00:00 PM
System Design 3

Chair: Toni Ruohonen (University of Jyväskylä)

Using Simulation with Design for Six Sigma in a Server Manufacturing Environment
Sreekanth Ramakrishnan (Binghamton University, State University of New York), Christiana M Drayer (IBM Corporation) and Pei-Fang Tsai and Krishnaswami Srihari (Binghamton University, State University of New York)

This research presents an integrated simulation modeling-Design For Six Sigma (DFSS) framework to study the design and process issues in a server manufacturing environment. The server assembly process is characterized by long cycle times, high fall-out rates and extremely complex assembly operations. To ensure on-time customer delivery, these enterprises adopt a make-to-plan and build-to-order philosophy. However, this model is extremely complex, resulting in wastes and inefficiencies in the associated processes. Lean and six sigma approaches have been successful in improving performance by eliminating waste in the design and operational processes. In this study, an integrated simulation modeling - DFSS framework is proposed to (i) address effects of variation, (ii) assess interactions effects between various sub-systems, and (iii) study proposed process (or design) changes, while performing “what-if” analysis. This framework was then used to identify opportunities for improving the operational and design issues in a server manufacturing environment.

Simplification and Aggregation Strategies Applied for Factory Analysis in Conceptual Phase Using Simulation
Matías Urenda Moris, Amos H.C. Ng, and Jacob Svensson (University of Skövde)

Despite that simulation possesses an establish background and offers tremendous promise for designing and analyzing complex production systems, manufacturing industry has been less successful in using it as a decision support tool, especially in the conceptual phase of factory design. This paper presents how simplification and aggregation strategies are incorporated in a modeling, simulation and analysis tool, with the aim of supporting decision making in conceptual phase. Conceptual modeling is guided by a framework using an object library with generic drag and drop system components and system control objects. Data inputs are simplified by the use of Effective Process Time distributions and a novel aggregation method for product mix cycle time differences. The out coming specification is through a Web Service interface handle by modeling system architecture, automatically generating a simulation model and analysis. Case studies confirm a breakthrough in project time reduction without appreciable effects on the model’s fidelity.

Simulation-Based Sustainable Manufacturing System Design
Juhani Heilala, Saija Vatanen, Jari Montonen, and Hannele Tonteri (VTT Technical Research Centre of Finland), Björn Johansson and Johan Stahre (Chalmers University of Technology) and Salla Lind (VTT Technical Research Centre of Finland)

Manufacturing simulation and digital engineering tools and procedures have had a positive impact on the manufacturing industry. However, to design a sustainable manufacturing system, a multitude of system dimensions must be jointly optimized. This paper proposes an integrated simulation tool helping to maximize production efficiency and balance environmental constraints already in the system design phase. Lean manufacturing, identification and elimination of waste and production losses, and environmental considerations are all needed during development of a sustainable manufacturing system. Engineers designing the manufacturing system need decision support, otherwise sub-optimization is more likely to occur. We present methods for calculating energy efficiency, CO2 emissions and other environmental impacts integrated into factory simulation software.