A popular safety-inventory policy utilized in the apparel industry is time-of-supply. Time-of-supply specifies inventory held to protect against forecast error and supply disruptions in terms of safety-time rather than safety-stock. Determining the proper safety-time is critical to ensure customer service. This case study presents a method for determining safety-time for raw materials in an apparel manufacturing operation. Additionally, the results of a simulation study that validated the time-of-supply inventory policy are presented.
{"title":"Validation of a time-of-supply inventory policy through simulation","authors":"Benjamin Martin, James Francis","doi":"10.5555/1162708.1163233","DOIUrl":"https://doi.org/10.5555/1162708.1163233","url":null,"abstract":"A popular safety-inventory policy utilized in the apparel industry is time-of-supply. Time-of-supply specifies inventory held to protect against forecast error and supply disruptions in terms of safety-time rather than safety-stock. Determining the proper safety-time is critical to ensure customer service. This case study presents a method for determining safety-time for raw materials in an apparel manufacturing operation. Additionally, the results of a simulation study that validated the time-of-supply inventory policy are presented.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126026163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Since 9/11 many telecommunications systems have seen the need to deal with overloading during high traffic conditions. As the use of VoIP increases an important question that needs to be answered is: "Can the voice packets be delivered in a timely fashion when the there has been a significant increase in traffic?" In this paper we considered the problem of modeling VoIP systems in an overloaded condition. We look at the problem from a simulation and analytic point of view. We present analytic models for the packet latency and jitter and loss probability for the three prevelant disciplines being used for VoIP today: First Come First Served, Priority Queue and Weighted Fair Queueing Systems. In addition, we investigate how simulation languages like GPSS/H compare with respect to runtime with simulation models developed using Visual Basic for Applications and if their runtimes are acceptable for practical use.
自 9/11 事件以来，许多电信系统都需要应对高流量条件下的过载问题。随着 VoIP 使用的增加，需要回答的一个重要问题是："当流量大幅增加时，能否及时传送语音数据包？在本文中，我们考虑了在过载情况下的 VoIP 系统建模问题。我们从模拟和分析的角度来研究这个问题。我们提出了目前 VoIP 使用的三种普遍规则的数据包延迟、抖动和丢失概率的分析模型：先到先得、优先队列和加权公平队列系统。此外，我们还研究了 GPSS/H 等仿真语言与使用 Visual Basic for Applications 开发的仿真模型在运行时间方面的比较，以及它们的运行时间在实际使用中是否可以接受。
{"title":"Modeling overloaded VoIP systems","authors":"M. J. Fischer, D. Masi","doi":"10.5555/1162708.1163243","DOIUrl":"https://doi.org/10.5555/1162708.1163243","url":null,"abstract":"Since 9/11 many telecommunications systems have seen the need to deal with overloading during high traffic conditions. As the use of VoIP increases an important question that needs to be answered is: \"Can the voice packets be delivered in a timely fashion when the there has been a significant increase in traffic?\" In this paper we considered the problem of modeling VoIP systems in an overloaded condition. We look at the problem from a simulation and analytic point of view. We present analytic models for the packet latency and jitter and loss probability for the three prevelant disciplines being used for VoIP today: First Come First Served, Priority Queue and Weighted Fair Queueing Systems. In addition, we investigate how simulation languages like GPSS/H compare with respect to runtime with simulation models developed using Visual Basic for Applications and if their runtimes are acceptable for practical use.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127531468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The quality of health care is increasingly receiving more and more emphases in almost all developed countries. Traditional health care Quality Assurance (QA) models have always been implemented in retrospect depending heavily on surveys. The objective of this research is to develop a novel and more reliable approach to the monitoring and improvement of health care quality. This approach is based on a real-time simulation system that monitors a Health Care Quality Index (HCQI). This system will map the HCQI which is a function of process factors (e.g. waiting time), against the patients' expectations and hence give health care managers the 'local' information needed to continuously adjust performance without waiting for an annual survey. Being a real-time system, managers will have the ability to run fast-forward simulation to help predict future demands and make decisions accordingly. This will be a key to Continuous Quality Improvement (CQI) in health care.
{"title":"A real-time knowledge-based decission support system for health care quality improvement using discrete event simulation techniques","authors":"A. Komashie, A. Mousavi, M. Özbayrak","doi":"10.5555/1162708.1163140","DOIUrl":"https://doi.org/10.5555/1162708.1163140","url":null,"abstract":"The quality of health care is increasingly receiving more and more emphases in almost all developed countries. Traditional health care Quality Assurance (QA) models have always been implemented in retrospect depending heavily on surveys. The objective of this research is to develop a novel and more reliable approach to the monitoring and improvement of health care quality. This approach is based on a real-time simulation system that monitors a Health Care Quality Index (HCQI). This system will map the HCQI which is a function of process factors (e.g. waiting time), against the patients' expectations and hence give health care managers the 'local' information needed to continuously adjust performance without waiting for an annual survey. Being a real-time system, managers will have the ability to run fast-forward simulation to help predict future demands and make decisions accordingly. This will be a key to Continuous Quality Improvement (CQI) in health care.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131037736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Simulating large call centers can require weeks or months. Additional time is spent on detailed analysis of input data to drive the models. Once a model is complete, the input data can be obsolete, requiring additional analysis and re-validation. This hinders the ability to provide accurate, timely models. This process is greatly improved by the use of OLAP data cubes to provide input data. Most simulation software packages have the functionality to read data from Excel workbooks. Data cubes provide data in a standard Excel pivot table format that can be easily updated to current data. Using OLAP cubes can significantly reduce the time to bring a simulation model to market, by streamlining the access to input data. Cubes also provide a quick, easy method to update data to the most current information. This ultimately provides a simulation analyst with a means to produce accurate, relevant and timely simulation solutions.
{"title":"Driving large call center simulations using OLAP data cubes","authors":"P. L. Markt","doi":"10.5555/1162708.1163224","DOIUrl":"https://doi.org/10.5555/1162708.1163224","url":null,"abstract":"Simulating large call centers can require weeks or months. Additional time is spent on detailed analysis of input data to drive the models. Once a model is complete, the input data can be obsolete, requiring additional analysis and re-validation. This hinders the ability to provide accurate, timely models. This process is greatly improved by the use of OLAP data cubes to provide input data. Most simulation software packages have the functionality to read data from Excel workbooks. Data cubes provide data in a standard Excel pivot table format that can be easily updated to current data. Using OLAP cubes can significantly reduce the time to bring a simulation model to market, by streamlining the access to input data. Cubes also provide a quick, easy method to update data to the most current information. This ultimately provides a simulation analyst with a means to produce accurate, relevant and timely simulation solutions.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133864404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-12-04DOI: 10.1109/WSC.2005.1574402
C. Grimard, Jon H. Marvel, C. Standridge
Simulation can be used to validate the design or redesign of any complex system before it is implemented. Validation evidence is obtained if the simulation demonstrates that the system operation corresponds to its design. This evidence includes comparing both detailed system behavior and performance measure values to those stated in the design. The application of simulation to validating the redesign of an injector assembly and calibration production area is discussed. Simulation is necessary to validate the initial estimate of cell throughput since a single worker must perform multiple operations at multiple workstations. The feasibility of the pattern of movement by this worker between stations must be demonstrated and alternative patterns assessed. Controls on the amount of work in process inventory in the cell must be validated. Modeling challenges unique to part movement using one-piece flow, work in process inventory control, and the movement of both workers and parts are discussed.
{"title":"Validation of the re-design of a manufacturing work cell using simulation","authors":"C. Grimard, Jon H. Marvel, C. Standridge","doi":"10.1109/WSC.2005.1574402","DOIUrl":"https://doi.org/10.1109/WSC.2005.1574402","url":null,"abstract":"Simulation can be used to validate the design or redesign of any complex system before it is implemented. Validation evidence is obtained if the simulation demonstrates that the system operation corresponds to its design. This evidence includes comparing both detailed system behavior and performance measure values to those stated in the design. The application of simulation to validating the redesign of an injector assembly and calibration production area is discussed. Simulation is necessary to validate the initial estimate of cell throughput since a single worker must perform multiple operations at multiple workstations. The feasibility of the pattern of movement by this worker between stations must be demonstrated and alternative patterns assessed. Controls on the amount of work in process inventory in the cell must be validated. Modeling challenges unique to part movement using one-piece flow, work in process inventory control, and the movement of both workers and parts are discussed.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"237 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122967882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-12-04DOI: 10.1109/WSC.2005.1574252
W. V. Beers
Many simulation experiments require considerable computer time, so interpolation is needed for sensitivity analysis and optimization. The interpolating functions are 'metamodels' (or 'response surfaces') of the underlying simulation models. For sensitivity analysis and optimization, simulationists use different interpolation techniques (e.g. low-order polynomial regression or neural nets). This paper, however, focuses on Kriging interpolation. In the 1950's, D. G. Krige developed this technique for the mining industry. Currently, Kriging interpolation is frequently applied in Computer Aided Engineering. In discrete-event simulation, however, Kriging has just started. This paper discusses Kriging for sensitivity analysis in simulation, including methods to select an experimental design for Kriging interpolation.
{"title":"Kriging metamodeling in discrete-event simulation: an overview","authors":"W. V. Beers","doi":"10.1109/WSC.2005.1574252","DOIUrl":"https://doi.org/10.1109/WSC.2005.1574252","url":null,"abstract":"Many simulation experiments require considerable computer time, so interpolation is needed for sensitivity analysis and optimization. The interpolating functions are 'metamodels' (or 'response surfaces') of the underlying simulation models. For sensitivity analysis and optimization, simulationists use different interpolation techniques (e.g. low-order polynomial regression or neural nets). This paper, however, focuses on Kriging interpolation. In the 1950's, D. G. Krige developed this technique for the mining industry. Currently, Kriging interpolation is frequently applied in Computer Aided Engineering. In discrete-event simulation, however, Kriging has just started. This paper discusses Kriging for sensitivity analysis in simulation, including methods to select an experimental design for Kriging interpolation.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"599 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123429934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-12-04DOI: 10.1109/WSC.2005.1574437
J. Venkateswaran, Y. Son
In this paper, the dynamics of a collaborative supply chain have been analyzed using transform techniques. The general conditions for stability of the supply chains are derived and the effects of inter-player sampling intervals are analyzed. System dynamics simulation models of the different members of the supply chain are developed. Z-transform techniques are employed to derive the general stability conditions (settings of control parameters that produce stable response). The variation in the supply chain's stability in response to the information synchronization frequency is examined by relating the update frequency to the sampling interval of the underlying difference equations. Existence of instability due to improper parameter selection and improper sampling interval selection is thus confirmed, and guidance for the selection of appropriate parameters to guarantee system stability is presented. Simulations are used to confirm our analysis and help demonstrate the stable or unstable behavior of the supply chain.
{"title":"Information synchronization effects on the stability of collaborative supply chain","authors":"J. Venkateswaran, Y. Son","doi":"10.1109/WSC.2005.1574437","DOIUrl":"https://doi.org/10.1109/WSC.2005.1574437","url":null,"abstract":"In this paper, the dynamics of a collaborative supply chain have been analyzed using transform techniques. The general conditions for stability of the supply chains are derived and the effects of inter-player sampling intervals are analyzed. System dynamics simulation models of the different members of the supply chain are developed. Z-transform techniques are employed to derive the general stability conditions (settings of control parameters that produce stable response). The variation in the supply chain's stability in response to the information synchronization frequency is examined by relating the update frequency to the sampling interval of the underlying difference equations. Existence of instability due to improper parameter selection and improper sampling interval selection is thus confirmed, and guidance for the selection of appropriate parameters to guarantee system stability is presented. Simulations are used to confirm our analysis and help demonstrate the stable or unstable behavior of the supply chain.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123593132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-12-05DOI: 10.1109/WSC.2004.1371333
Simon J. E. Taylor, P. Lendermann, R. Paul, S. Reichenthal, S. Strassburger, S. Turner
This panel paper presents the views of six researchers and practitioners of simulation modeling. Collectively we attempt to address a range of key future challenges to modeling methodology. It is hoped that the views of this paper, and the presentations made by the panelists at the 2004 Winter Simulation Conference will raise awareness and stimulate further discussion on the future of modeling methodology in areas such as modeling problems in business applications, human factors and geographically dispersed networks; rapid model development and maintenance; legacy modeling approaches; markup languages; virtual interactive process design and simulation; standards; and Grid computing.
{"title":"Panel on future challenges in modeling methodology","authors":"Simon J. E. Taylor, P. Lendermann, R. Paul, S. Reichenthal, S. Strassburger, S. Turner","doi":"10.1109/WSC.2004.1371333","DOIUrl":"https://doi.org/10.1109/WSC.2004.1371333","url":null,"abstract":"This panel paper presents the views of six researchers and practitioners of simulation modeling. Collectively we attempt to address a range of key future challenges to modeling methodology. It is hoped that the views of this paper, and the presentations made by the panelists at the 2004 Winter Simulation Conference will raise awareness and stimulate further discussion on the future of modeling methodology in areas such as modeling problems in business applications, human factors and geographically dispersed networks; rapid model development and maintenance; legacy modeling approaches; markup languages; virtual interactive process design and simulation; standards; and Grid computing.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127635382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-12-05DOI: 10.1109/WSC.2004.1371430
J. Nomura, S. Takakuwa
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.
{"title":"Module-based modeling of flow-type multistage manufacturing systems adopting dual-card Kanban system","authors":"J. Nomura, S. Takakuwa","doi":"10.1109/WSC.2004.1371430","DOIUrl":"https://doi.org/10.1109/WSC.2004.1371430","url":null,"abstract":"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.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128835742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-12-05DOI: 10.1109/WSC.2004.1371295
M. Zyda
The MOVES Institute's mission is research, application and education in the grand challenges of modeling, virtual environments and simulation (MOVES). The institute's focus is on 3D visual simulation, networked virtual environments, computer-generated autonomy, human performance engineering, immersive technologies, defense/entertainment collaboration, and combat modeling and analysis. In networked virtual environments, we are architecting the technology that allows us to build large-scale, dynamically extensible virtual environments, virtual environments that are semantically interoperable and always on. In computer-generated autonomy, we are building a scenario engine for determining the space of potential outcomes from a virtual description of an infrastructure, a set of policies, characters and cultural behaviors. In immersive technologies, we have designed a source-less tracker that is micromachinable, and have performed considerable work on the deployment of sound to enhance the feeling of immersion. In defense/entertainment collaboration, we have constructed a PC game, America's Army, that provides the experience of a potential career in the Army. America's Army has become the fastest growing online PC game in history, a game that has been the recipient of several "best game" or "runner up for best game" of the year awards. Since the release of America's Army, the number one question being asked of our institute is will the next generation of training and combat modeling systems have a game-like face? In this talk, we answer that question and discuss the potential that game technology has for the future of modeling and simulation.
{"title":"Does the future of modeling and simulation have a game face?","authors":"M. Zyda","doi":"10.1109/WSC.2004.1371295","DOIUrl":"https://doi.org/10.1109/WSC.2004.1371295","url":null,"abstract":"The MOVES Institute's mission is research, application and education in the grand challenges of modeling, virtual environments and simulation (MOVES). The institute's focus is on 3D visual simulation, networked virtual environments, computer-generated autonomy, human performance engineering, immersive technologies, defense/entertainment collaboration, and combat modeling and analysis. In networked virtual environments, we are architecting the technology that allows us to build large-scale, dynamically extensible virtual environments, virtual environments that are semantically interoperable and always on. In computer-generated autonomy, we are building a scenario engine for determining the space of potential outcomes from a virtual description of an infrastructure, a set of policies, characters and cultural behaviors. In immersive technologies, we have designed a source-less tracker that is micromachinable, and have performed considerable work on the deployment of sound to enhance the feeling of immersion. In defense/entertainment collaboration, we have constructed a PC game, America's Army, that provides the experience of a potential career in the Army. America's Army has become the fastest growing online PC game in history, a game that has been the recipient of several \"best game\" or \"runner up for best game\" of the year awards. Since the release of America's Army, the number one question being asked of our institute is will the next generation of training and combat modeling systems have a game-like face? In this talk, we answer that question and discuss the potential that game technology has for the future of modeling and simulation.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115498543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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