Dynamic simulation of job shop scheduling for optimal performance
Deals with the dynamic scheduling problems and solutions of job shop comprising six work centres and n components. Concerns the behaviour of the system, with the arrival of urgent orders and normal orders. In a typical manufacturing system, urgent orders are scheduled for processing based on their u...
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| Veröffentlicht in: | International journal of operations & production management 1995-07, Vol.15 (7), p.106-120 |
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| container_end_page | 120 |
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| container_issue | 7 |
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| container_title | International journal of operations & production management |
| container_volume | 15 |
| creator | Selladurai, V. Aravindan, P. Ponnambalam, S.G. Gunasekaran, A. |
| description | Deals with the dynamic scheduling problems and solutions of job
shop comprising six work centres and n components. Concerns the
behaviour of the system, with the arrival of urgent orders and normal
orders. In a typical manufacturing system, urgent orders are scheduled
for processing based on their urgency and given priority over normal
orders. Describes an analysis of urgent order processing on the basis of
non pre-emptive priority and pre-emptive resume priority over normal
orders. Enumerates manufacturing system performances which had been
analysed for the two most popular scheduling rules - first in
first out (FIFO) and shortest processing time (SPT) - through a
system simulation program. Concludes by asserting that the simulation
program can be used to schedule the manufacturing system dynamically by
choosing the appropriate scheduling rule to measure optimal system
performance leading to higher productivity. |
| doi_str_mv | 10.1108/01443579510090444 |
| format | Article |
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shop comprising six work centres and n components. Concerns the
behaviour of the system, with the arrival of urgent orders and normal
orders. In a typical manufacturing system, urgent orders are scheduled
for processing based on their urgency and given priority over normal
orders. Describes an analysis of urgent order processing on the basis of
non pre-emptive priority and pre-emptive resume priority over normal
orders. Enumerates manufacturing system performances which had been
analysed for the two most popular scheduling rules - first in
first out (FIFO) and shortest processing time (SPT) - through a
system simulation program. Concludes by asserting that the simulation
program can be used to schedule the manufacturing system dynamically by
choosing the appropriate scheduling rule to measure optimal system
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shop comprising six work centres and n components. Concerns the
behaviour of the system, with the arrival of urgent orders and normal
orders. In a typical manufacturing system, urgent orders are scheduled
for processing based on their urgency and given priority over normal
orders. Describes an analysis of urgent order processing on the basis of
non pre-emptive priority and pre-emptive resume priority over normal
orders. Enumerates manufacturing system performances which had been
analysed for the two most popular scheduling rules - first in
first out (FIFO) and shortest processing time (SPT) - through a
system simulation program. Concludes by asserting that the simulation
program can be used to schedule the manufacturing system dynamically by
choosing the appropriate scheduling rule to measure optimal system
performance leading to higher productivity.</description><subject>Computer simulation</subject><subject>Computer-generated environments</subject><subject>FIFO</subject><subject>Heuristic</subject><subject>Job shops</subject><subject>Machine shops</subject><subject>Manufacturing</subject><subject>Manufacturing strategy</subject><subject>Methods</subject><subject>Production capacity</subject><subject>Production management</subject><subject>Production scheduling</subject><subject>Productivity</subject><subject>Scheduling</subject><subject>Scheduling (Management)</subject><subject>Workinprogress</subject><issn>0144-3577</issn><issn>1758-6593</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1995</creationdate><recordtype>article</recordtype><sourceid>K30</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp90ltrFDEUAOBBFFyrP8C3QUFfnDb3y-NaqxZaFFEWfAmZTLLNOpOMyQy0_94MKy3YreQhJPlycg45VfUSgmMIgTgBkBBMuaQQAAkIIY-qFeRUNIxK_LhaLedNAfxp9SznHQAAYUhX1frDTdCDN3X2w9zrycdQR1fvYlvnqzjW2VzZbu592NYupjqOkx90X482leWgg7HPqydO99m--DsfVT8-nn0__dxcfPl0frq-aAylaGow4Zpx2EnIW8xZy5CwTjqhRSekZrSVbUdbKDgQhDkOOk2MsaUQCiQUiOKj6u0-7pji79nmSQ0-G9v3Otg4Z8UJhhJggop881-JJIISYVDgq3_gLs4plCoUwggzLAks6PVDCCLJuZRULG--26ut7q3ywcUpabO1wSbdx2CdL9vrpRCGESm8OcDL6Gz5jEMe7r1JMedknRpT-Yh0oyBQSwOoew1w94bPk72-vaDTL8U45lSRDVLf0M-vl-83UG3uSrDDknR3e-NeaDV2rnBwmD-c0R-f1MnG</recordid><startdate>19950701</startdate><enddate>19950701</enddate><creator>Selladurai, V.</creator><creator>Aravindan, P.</creator><creator>Ponnambalam, S.G.</creator><creator>Gunasekaran, A.</creator><general>MCB UP Ltd</general><general>Emerald Group Publishing, Ltd</general><general>MCB</general><general>Emerald Group Publishing Limited</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>K30</scope><scope>PAAUG</scope><scope>PAWHS</scope><scope>PAWZZ</scope><scope>PAXOH</scope><scope>PBHAV</scope><scope>PBQSW</scope><scope>PBYQZ</scope><scope>PCIWU</scope><scope>PCMID</scope><scope>PCZJX</scope><scope>PDGRG</scope><scope>PDWWI</scope><scope>PETMR</scope><scope>PFVGT</scope><scope>PGXDX</scope><scope>PIHIL</scope><scope>PISVA</scope><scope>PJCTQ</scope><scope>PJTMS</scope><scope>PLCHJ</scope><scope>PMHAD</scope><scope>PNQDJ</scope><scope>POUND</scope><scope>PPLAD</scope><scope>PQAPC</scope><scope>PQCAN</scope><scope>PQCMW</scope><scope>PQEME</scope><scope>PQHKH</scope><scope>PQMID</scope><scope>PQNCT</scope><scope>PQNET</scope><scope>PQSCT</scope><scope>PQSET</scope><scope>PSVJG</scope><scope>PVMQY</scope><scope>PZGFC</scope><scope>SAAPM</scope><scope>0U~</scope><scope>1-H</scope><scope>7TB</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FI</scope><scope>ABJCF</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>K6~</scope><scope>K8~</scope><scope>L.-</scope><scope>L.0</scope><scope>L6V</scope><scope>M0C</scope><scope>M0T</scope><scope>M2O</scope><scope>M7S</scope><scope>MBDVC</scope><scope>PQBIZ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope></search><sort><creationdate>19950701</creationdate><title>Dynamic simulation of job shop scheduling for optimal performance</title><author>Selladurai, V. ; Aravindan, P. ; Ponnambalam, S.G. ; Gunasekaran, A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c552t-347a671d917b376b628ef9f8a8d89a65b9bd5b1870846f70da4cce44450918253</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1995</creationdate><topic>Computer simulation</topic><topic>Computer-generated environments</topic><topic>FIFO</topic><topic>Heuristic</topic><topic>Job shops</topic><topic>Machine shops</topic><topic>Manufacturing</topic><topic>Manufacturing strategy</topic><topic>Methods</topic><topic>Production capacity</topic><topic>Production management</topic><topic>Production scheduling</topic><topic>Productivity</topic><topic>Scheduling</topic><topic>Scheduling (Management)</topic><topic>Workinprogress</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Selladurai, V.</creatorcontrib><creatorcontrib>Aravindan, P.</creatorcontrib><creatorcontrib>Ponnambalam, S.G.</creatorcontrib><creatorcontrib>Gunasekaran, A.</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>Periodicals Index Online</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - 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shop comprising six work centres and n components. Concerns the
behaviour of the system, with the arrival of urgent orders and normal
orders. In a typical manufacturing system, urgent orders are scheduled
for processing based on their urgency and given priority over normal
orders. Describes an analysis of urgent order processing on the basis of
non pre-emptive priority and pre-emptive resume priority over normal
orders. Enumerates manufacturing system performances which had been
analysed for the two most popular scheduling rules - first in
first out (FIFO) and shortest processing time (SPT) - through a
system simulation program. Concludes by asserting that the simulation
program can be used to schedule the manufacturing system dynamically by
choosing the appropriate scheduling rule to measure optimal system
performance leading to higher productivity.</abstract><cop>Bradford</cop><pub>MCB UP Ltd</pub><doi>10.1108/01443579510090444</doi><tpages>15</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0144-3577 |
| ispartof | International journal of operations & production management, 1995-07, Vol.15 (7), p.106-120 |
| issn | 0144-3577 1758-6593 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_743190342 |
| source | Periodicals Index Online; Emerald Journals |
| subjects | Computer simulation Computer-generated environments FIFO Heuristic Job shops Machine shops Manufacturing Manufacturing strategy Methods Production capacity Production management Production scheduling Productivity Scheduling Scheduling (Management) Workinprogress |
| title | Dynamic simulation of job shop scheduling for optimal performance |
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