Simulation of Semiconductor Manufacturing Supply-Chain Systems With DEVS, MPC, and KIB
The dynamics of high-volume discrete-part semiconductor manufacturing supply-chain systems can be described using a combination of Discrete EVent System Specification (DEVS) and model predictive control (MPC) modeling approaches. To formulate the interactions between the discrete process model and i...
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Veröffentlicht in: | IEEE transactions on semiconductor manufacturing 2009-02, Vol.22 (1), p.164-174 |
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creator | Dongping Huang Sarjoughian, H.S. Wenlin Wang Godding, G. Rivera, D.E. Kempf, K.G. Mittelmann, H. |
description | The dynamics of high-volume discrete-part semiconductor manufacturing supply-chain systems can be described using a combination of Discrete EVent System Specification (DEVS) and model predictive control (MPC) modeling approaches. To formulate the interactions between the discrete process model and its controller, another model called Knowledge Interchange Broker (KIB) is used. A robust and scalable testbed supporting DEVS-based manufacturing process modeling, MPC-based controller design, and the KIB DEVS/MPC interaction model is developed. A suite of experiments have been devised and simulated using this testbed. The flexibility of this approach for modeling, simulating, and evaluating stochastic discrete process models under alternative control schemes is detailed. The testbed illustrates the benefits and challenges associated with developing and using realistic manufacturing process models and process control policies. The simulation environment demonstrates the importance of explicitly defining and exposing the interactions between the manufacturing and control subsystems of complex semiconductor supply-chain systems. |
doi_str_mv | 10.1109/TSM.2008.2011680 |
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(IEEE) 2009</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c385t-db8e990ebc2e385c1d727310ec12a213b687889d4fe5c8691647ec2d50ad883c3</citedby><cites>FETCH-LOGICAL-c385t-db8e990ebc2e385c1d727310ec12a213b687889d4fe5c8691647ec2d50ad883c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4773491$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27903,27904,54736</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4773491$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Dongping Huang</creatorcontrib><creatorcontrib>Sarjoughian, H.S.</creatorcontrib><creatorcontrib>Wenlin Wang</creatorcontrib><creatorcontrib>Godding, G.</creatorcontrib><creatorcontrib>Rivera, D.E.</creatorcontrib><creatorcontrib>Kempf, K.G.</creatorcontrib><creatorcontrib>Mittelmann, H.</creatorcontrib><title>Simulation of Semiconductor Manufacturing Supply-Chain Systems With DEVS, MPC, and KIB</title><title>IEEE transactions on semiconductor manufacturing</title><addtitle>TSM</addtitle><description>The dynamics of high-volume discrete-part semiconductor manufacturing supply-chain systems can be described using a combination of Discrete EVent System Specification (DEVS) and model predictive control (MPC) modeling approaches. To formulate the interactions between the discrete process model and its controller, another model called Knowledge Interchange Broker (KIB) is used. A robust and scalable testbed supporting DEVS-based manufacturing process modeling, MPC-based controller design, and the KIB DEVS/MPC interaction model is developed. A suite of experiments have been devised and simulated using this testbed. The flexibility of this approach for modeling, simulating, and evaluating stochastic discrete process models under alternative control schemes is detailed. The testbed illustrates the benefits and challenges associated with developing and using realistic manufacturing process models and process control policies. The simulation environment demonstrates the importance of explicitly defining and exposing the interactions between the manufacturing and control subsystems of complex semiconductor supply-chain systems.</description><subject>Computer simulation</subject><subject>Development</subject><subject>Discrete event systems</subject><subject>Discrete-event system specification</subject><subject>Dynamical systems</subject><subject>Dynamics</subject><subject>Flexibility</subject><subject>hybrid simulation testbed</subject><subject>Knowledge Interchange Broker (KIB)</subject><subject>Manufacturing processes</subject><subject>Mathematical models</subject><subject>model composability</subject><subject>model predictive control</subject><subject>optimization</subject><subject>Predictive control</subject><subject>Predictive models</subject><subject>Process control</subject><subject>Robust control</subject><subject>Semiconductor device manufacture</subject><subject>semiconductor manufacturing</subject><subject>Semiconductors</subject><subject>Specifications</subject><subject>Stochastic processes</subject><subject>supply-chain management</subject><subject>Testing</subject><subject>Virtual manufacturing</subject><issn>0894-6507</issn><issn>1558-2345</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqFkTtv2zAQgImgBeKm3QNkITK0S-QcH-JjTJyXkRgpIMcZCZqiahp6uKI0-N-HgYMOHdrlDjh8d7i7D6FTAlNCQF8ui8WUAqgUCBEKjtCE5LnKKOP5JzQBpXkmcpDH6EuMWwDCuZYTtCpCM9Z2CF2LuwoXvgmua8vRDV2PF7YdK-uGsQ_tL1yMu129z2YbG1pc7OPgm4hfw7DBN7er4gIvfs4usG1L_Di__oo-V7aO_ttHPkEvd7fL2UP29Hw_n109ZY6pfMjKtfJag1876lPBkVJSyQh4R6ilhK2Fkkrpklc-d0poIrj0jpY52FIp5tgJ-nGYu-u736OPg2lCdL6ubeu7MRoNTDAlgP6XVDI9B3JFEvn9nyTjXPC0ZALP_wK33di36V6jCQUqtVAJggPk-i7G3ldm14fG9ntDwLybM8mceTdnPsyllrNDS_De_8G5lIxrwt4Ae-CRtg</recordid><startdate>20090201</startdate><enddate>20090201</enddate><creator>Dongping Huang</creator><creator>Sarjoughian, H.S.</creator><creator>Wenlin Wang</creator><creator>Godding, G.</creator><creator>Rivera, D.E.</creator><creator>Kempf, K.G.</creator><creator>Mittelmann, H.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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To formulate the interactions between the discrete process model and its controller, another model called Knowledge Interchange Broker (KIB) is used. A robust and scalable testbed supporting DEVS-based manufacturing process modeling, MPC-based controller design, and the KIB DEVS/MPC interaction model is developed. A suite of experiments have been devised and simulated using this testbed. The flexibility of this approach for modeling, simulating, and evaluating stochastic discrete process models under alternative control schemes is detailed. The testbed illustrates the benefits and challenges associated with developing and using realistic manufacturing process models and process control policies. The simulation environment demonstrates the importance of explicitly defining and exposing the interactions between the manufacturing and control subsystems of complex semiconductor supply-chain systems.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TSM.2008.2011680</doi><tpages>11</tpages></addata></record> |
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subjects | Computer simulation Development Discrete event systems Discrete-event system specification Dynamical systems Dynamics Flexibility hybrid simulation testbed Knowledge Interchange Broker (KIB) Manufacturing processes Mathematical models model composability model predictive control optimization Predictive control Predictive models Process control Robust control Semiconductor device manufacture semiconductor manufacturing Semiconductors Specifications Stochastic processes supply-chain management Testing Virtual manufacturing |
title | Simulation of Semiconductor Manufacturing Supply-Chain Systems With DEVS, MPC, and KIB |
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