Control of a Single Batch Processor With Incompatible Job Families and Future Job Arrivals
We examine the problem of minimizing the mean cycle time of a batch processor with incompatible job families and future job arrivals. Batch processors frequently found in wafer fabrication include oxidation and diffusion ovens. When the problem is deterministic with a fixed number of job arrivals, t...
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Veröffentlicht in: | IEEE transactions on semiconductor manufacturing 2011-05, Vol.24 (2), p.208-222 |
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description | We examine the problem of minimizing the mean cycle time of a batch processor with incompatible job families and future job arrivals. Batch processors frequently found in wafer fabrication include oxidation and diffusion ovens. When the problem is deterministic with a fixed number of job arrivals, the problem is NP-hard; an optimal dynamic program formulation is developed and empirically tested on small problem instances. For larger problem instances with possibly infinite job arrivals, an online heuristic based on model predictive control (MPC) is proposed. The proposed heuristic has two parameters: the number of job families considered f , and the number of future job arrivals L . Statistical analysis of simulation results shows that the MPC-based heuristic has significantly lower mean cycle time than a benchmark look-ahead method under the assumption that the arrival time is deterministic and job families of consecutive job arrivals are uncorrelated. These observations also hold true when the predicted arrival times can be erroneous, indicating that the suggested MPC-based heuristic is as robust as the benchmark with respect to errors in forecasted arrival times. When the job families of future job arrivals are positively correlated, the mean cycle time of jobs passing through the batch processor is significantly reduced, regardless of control policy. We infer that the introduction of correlation generates less improvement for policies that foresee events longer into the future. For this reason, when the correlation is high, the MPC-based heuristic, which considers events that occur farther into the future, may have worse performance than the benchmark. The results suggest two ways to improve the performance of the batch processor. First, we can use a heuristic that has better mean performance, which may entail much larger computational costs. Another option is to continue using a simple look-ahead policy at the batch processor, and focus attention on controlling the upstream processors, such that the batch processor arrival process exhibits correlated job families between consecutive arrivals. This introduction of correlation causes a significant reduction of cycle time regardless of system parameter and batch processor control policy. |
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Batch processors frequently found in wafer fabrication include oxidation and diffusion ovens. When the problem is deterministic with a fixed number of job arrivals, the problem is NP-hard; an optimal dynamic program formulation is developed and empirically tested on small problem instances. For larger problem instances with possibly infinite job arrivals, an online heuristic based on model predictive control (MPC) is proposed. The proposed heuristic has two parameters: the number of job families considered f , and the number of future job arrivals L . Statistical analysis of simulation results shows that the MPC-based heuristic has significantly lower mean cycle time than a benchmark look-ahead method under the assumption that the arrival time is deterministic and job families of consecutive job arrivals are uncorrelated. These observations also hold true when the predicted arrival times can be erroneous, indicating that the suggested MPC-based heuristic is as robust as the benchmark with respect to errors in forecasted arrival times. When the job families of future job arrivals are positively correlated, the mean cycle time of jobs passing through the batch processor is significantly reduced, regardless of control policy. We infer that the introduction of correlation generates less improvement for policies that foresee events longer into the future. For this reason, when the correlation is high, the MPC-based heuristic, which considers events that occur farther into the future, may have worse performance than the benchmark. The results suggest two ways to improve the performance of the batch processor. First, we can use a heuristic that has better mean performance, which may entail much larger computational costs. Another option is to continue using a simple look-ahead policy at the batch processor, and focus attention on controlling the upstream processors, such that the batch processor arrival process exhibits correlated job families between consecutive arrivals. This introduction of correlation causes a significant reduction of cycle time regardless of system parameter and batch processor control policy.</description><identifier>ISSN: 0894-6507</identifier><identifier>EISSN: 1558-2345</identifier><identifier>DOI: 10.1109/TSM.2011.2120850</identifier><identifier>CODEN: ITSMED</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Algorithm design and analysis ; Applied sciences ; Arrivals ; Batch processing ; Batch processor ; Batch production systems ; Complexity theory ; Correlation ; Cycle time ; Design. Technologies. Operation analysis. Testing ; Dynamic programming ; Dynamic scheduling ; Electronics ; Exact sciences and technology ; Heuristic ; Integrated circuits ; Integrated circuits by function (including memories and processors) ; Mathematical models ; Microelectronic fabrication (materials and surfaces technology) ; Microprocessors ; optimal control ; Policies ; Processor scheduling ; Program processors ; Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices ; Semiconductors ; Studies ; wafer fabrication</subject><ispartof>IEEE transactions on semiconductor manufacturing, 2011-05, Vol.24 (2), p.208-222</ispartof><rights>2015 INIST-CNRS</rights><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) May 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c353t-5bb15b56493d0f564f5078fa49bd6f92e1f7d47ab8c35f5488e6720b764dde0b3</citedby><cites>FETCH-LOGICAL-c353t-5bb15b56493d0f564f5078fa49bd6f92e1f7d47ab8c35f5488e6720b764dde0b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5720553$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5720553$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=24162470$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Tajan, J B C</creatorcontrib><creatorcontrib>Sivakumar, A I</creatorcontrib><creatorcontrib>Gershwin, S B</creatorcontrib><title>Control of a Single Batch Processor With Incompatible Job Families and Future Job Arrivals</title><title>IEEE transactions on semiconductor manufacturing</title><addtitle>TSM</addtitle><description>We examine the problem of minimizing the mean cycle time of a batch processor with incompatible job families and future job arrivals. Batch processors frequently found in wafer fabrication include oxidation and diffusion ovens. When the problem is deterministic with a fixed number of job arrivals, the problem is NP-hard; an optimal dynamic program formulation is developed and empirically tested on small problem instances. For larger problem instances with possibly infinite job arrivals, an online heuristic based on model predictive control (MPC) is proposed. The proposed heuristic has two parameters: the number of job families considered f , and the number of future job arrivals L . Statistical analysis of simulation results shows that the MPC-based heuristic has significantly lower mean cycle time than a benchmark look-ahead method under the assumption that the arrival time is deterministic and job families of consecutive job arrivals are uncorrelated. These observations also hold true when the predicted arrival times can be erroneous, indicating that the suggested MPC-based heuristic is as robust as the benchmark with respect to errors in forecasted arrival times. When the job families of future job arrivals are positively correlated, the mean cycle time of jobs passing through the batch processor is significantly reduced, regardless of control policy. We infer that the introduction of correlation generates less improvement for policies that foresee events longer into the future. For this reason, when the correlation is high, the MPC-based heuristic, which considers events that occur farther into the future, may have worse performance than the benchmark. The results suggest two ways to improve the performance of the batch processor. First, we can use a heuristic that has better mean performance, which may entail much larger computational costs. Another option is to continue using a simple look-ahead policy at the batch processor, and focus attention on controlling the upstream processors, such that the batch processor arrival process exhibits correlated job families between consecutive arrivals. This introduction of correlation causes a significant reduction of cycle time regardless of system parameter and batch processor control policy.</description><subject>Algorithm design and analysis</subject><subject>Applied sciences</subject><subject>Arrivals</subject><subject>Batch processing</subject><subject>Batch processor</subject><subject>Batch production systems</subject><subject>Complexity theory</subject><subject>Correlation</subject><subject>Cycle time</subject><subject>Design. Technologies. Operation analysis. Testing</subject><subject>Dynamic programming</subject><subject>Dynamic scheduling</subject><subject>Electronics</subject><subject>Exact sciences and technology</subject><subject>Heuristic</subject><subject>Integrated circuits</subject><subject>Integrated circuits by function (including memories and processors)</subject><subject>Mathematical models</subject><subject>Microelectronic fabrication (materials and surfaces technology)</subject><subject>Microprocessors</subject><subject>optimal control</subject><subject>Policies</subject><subject>Processor scheduling</subject><subject>Program processors</subject><subject>Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices</subject><subject>Semiconductors</subject><subject>Studies</subject><subject>wafer fabrication</subject><issn>0894-6507</issn><issn>1558-2345</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkE1LAzEQhoMoWKt3wUsQBC9b87nZPWqxWqkotCJ4CcluYlO2m5rsCv57U1o8eHph5plh5gHgHKMRxqi8WcyfRwRhPCKYoIKjAzDAnBcZoYwfggEqSpblHIljcBLjCiHMWCkG4GPs2y74BnoLFZy79rMx8E511RK-Bl-ZGH2A765bwmlb-fVGdU4n4slrOFFr1zgToWprOOm7PuzqtyG4b9XEU3BkU5izfQ7B2-R-MX7MZi8P0_HtLKsop13GtcZc85yVtEY2pU1XFlaxUte5LYnBVtRMKF0k3nJWFCYXBGmRs7o2SNMhuN7t3QT_1ZvYybWLlWka1RrfR4lzgSklIi8TevkPXfk-tOk6WSYhgic2QWgHVcHHGIyVm-DWKvxIjOTWtUyu5da13LtOI1f7vSpWqrFBtZWLf3OE4ZwwseUudpwzxvy1eXqHc0p_AZSjhd0</recordid><startdate>20110501</startdate><enddate>20110501</enddate><creator>Tajan, J B C</creator><creator>Sivakumar, A I</creator><creator>Gershwin, S B</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7U5</scope><scope>8FD</scope><scope>L7M</scope><scope>F28</scope><scope>FR3</scope></search><sort><creationdate>20110501</creationdate><title>Control of a Single Batch Processor With Incompatible Job Families and Future Job Arrivals</title><author>Tajan, J B C ; Sivakumar, A I ; Gershwin, S B</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c353t-5bb15b56493d0f564f5078fa49bd6f92e1f7d47ab8c35f5488e6720b764dde0b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Algorithm design and analysis</topic><topic>Applied sciences</topic><topic>Arrivals</topic><topic>Batch processing</topic><topic>Batch processor</topic><topic>Batch production systems</topic><topic>Complexity theory</topic><topic>Correlation</topic><topic>Cycle time</topic><topic>Design. Technologies. Operation analysis. Testing</topic><topic>Dynamic programming</topic><topic>Dynamic scheduling</topic><topic>Electronics</topic><topic>Exact sciences and technology</topic><topic>Heuristic</topic><topic>Integrated circuits</topic><topic>Integrated circuits by function (including memories and processors)</topic><topic>Mathematical models</topic><topic>Microelectronic fabrication (materials and surfaces technology)</topic><topic>Microprocessors</topic><topic>optimal control</topic><topic>Policies</topic><topic>Processor scheduling</topic><topic>Program processors</topic><topic>Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices</topic><topic>Semiconductors</topic><topic>Studies</topic><topic>wafer fabrication</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tajan, J B C</creatorcontrib><creatorcontrib>Sivakumar, A I</creatorcontrib><creatorcontrib>Gershwin, S B</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE transactions on semiconductor manufacturing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Tajan, J B C</au><au>Sivakumar, A I</au><au>Gershwin, S B</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Control of a Single Batch Processor With Incompatible Job Families and Future Job Arrivals</atitle><jtitle>IEEE transactions on semiconductor manufacturing</jtitle><stitle>TSM</stitle><date>2011-05-01</date><risdate>2011</risdate><volume>24</volume><issue>2</issue><spage>208</spage><epage>222</epage><pages>208-222</pages><issn>0894-6507</issn><eissn>1558-2345</eissn><coden>ITSMED</coden><abstract>We examine the problem of minimizing the mean cycle time of a batch processor with incompatible job families and future job arrivals. Batch processors frequently found in wafer fabrication include oxidation and diffusion ovens. When the problem is deterministic with a fixed number of job arrivals, the problem is NP-hard; an optimal dynamic program formulation is developed and empirically tested on small problem instances. For larger problem instances with possibly infinite job arrivals, an online heuristic based on model predictive control (MPC) is proposed. The proposed heuristic has two parameters: the number of job families considered f , and the number of future job arrivals L . Statistical analysis of simulation results shows that the MPC-based heuristic has significantly lower mean cycle time than a benchmark look-ahead method under the assumption that the arrival time is deterministic and job families of consecutive job arrivals are uncorrelated. These observations also hold true when the predicted arrival times can be erroneous, indicating that the suggested MPC-based heuristic is as robust as the benchmark with respect to errors in forecasted arrival times. When the job families of future job arrivals are positively correlated, the mean cycle time of jobs passing through the batch processor is significantly reduced, regardless of control policy. We infer that the introduction of correlation generates less improvement for policies that foresee events longer into the future. For this reason, when the correlation is high, the MPC-based heuristic, which considers events that occur farther into the future, may have worse performance than the benchmark. The results suggest two ways to improve the performance of the batch processor. First, we can use a heuristic that has better mean performance, which may entail much larger computational costs. Another option is to continue using a simple look-ahead policy at the batch processor, and focus attention on controlling the upstream processors, such that the batch processor arrival process exhibits correlated job families between consecutive arrivals. This introduction of correlation causes a significant reduction of cycle time regardless of system parameter and batch processor control policy.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/TSM.2011.2120850</doi><tpages>15</tpages></addata></record> |
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subjects | Algorithm design and analysis Applied sciences Arrivals Batch processing Batch processor Batch production systems Complexity theory Correlation Cycle time Design. Technologies. Operation analysis. Testing Dynamic programming Dynamic scheduling Electronics Exact sciences and technology Heuristic Integrated circuits Integrated circuits by function (including memories and processors) Mathematical models Microelectronic fabrication (materials and surfaces technology) Microprocessors optimal control Policies Processor scheduling Program processors Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices Semiconductors Studies wafer fabrication |
title | Control of a Single Batch Processor With Incompatible Job Families and Future Job Arrivals |
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