ProceedingsIEEE, 1997 - Artificial intelligence |
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Page 149
... manufacturing field , we need to develop large scale manufacturing information systems especially in the field of Japanese steel manufacturing industry where CIM is the core management technology . But they require large amount of time ...
... manufacturing field , we need to develop large scale manufacturing information systems especially in the field of Japanese steel manufacturing industry where CIM is the core management technology . But they require large amount of time ...
Page 460
... manufacturing times when considering an aggregate level of the hierarchy , i.e. a level where entities are lots ( instead of parts ) and manufacturing subsystems ( instead of machines ) . Parameter Tm , which is the minimal period on ...
... manufacturing times when considering an aggregate level of the hierarchy , i.e. a level where entities are lots ( instead of parts ) and manufacturing subsystems ( instead of machines ) . Parameter Tm , which is the minimal period on ...
Page 527
... Manufacturing Plants , M.T. Research Project , Department of Manufacturing and Industrial Technology , Arizona State University , Aug. 1993 . [ 10 ] Li , S. , Tang , T , and Collins , D.W. , Minimum Inventory Variability Schedule with ...
... Manufacturing Plants , M.T. Research Project , Department of Manufacturing and Industrial Technology , Arizona State University , Aug. 1993 . [ 10 ] Li , S. , Tang , T , and Collins , D.W. , Minimum Inventory Variability Schedule with ...
Contents
Innovations in Design and Integrated | 1 |
Creative and Innovative Manufacturing | 4 |
Y Fan and C Wu Tsinghua Univ | 7 |
Copyright | |
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according activities algorithm allows analysis application approach architecture assembly ATRT Automation called communication complete components considered constraints control system cost customers decision defined described determined dispatching distributed dynamic effective Engineering enterprise environment error estimated example exists Figure fixture flexible flow function given implementation important improvement industrial input integration interaction interface INTRODUCTION knowledge lead learning load locating machine manuals manufacturing means measurements method nets object obtained operation optimal output parameters performance Petri planning plant position possible presented problem proposed prototype real-time reference represents requirements robot rules scheduling selected sequence server shown shows simulation solution specific standard station structure task token tool transition unit University virtual