DocumentCode
2847670
Title
Business process analysis to obtain empirical lot sizing rule in printing process
Author
Matsumoto, Shimpei ; Ueno, Nobuyuki ; Okuhara, Koji ; Ishii, Ishii
Author_Institution
Dept. of Comput. & Control Eng., Oita Nat. Coll. of Technol., Oita
fYear
2008
fDate
23-26 Aug. 2008
Firstpage
591
Lastpage
596
Abstract
We have addressed the improvement of production efficiency in an automobile parts supplier, and have revised the business processes to develop the knowledge-based production scheduling software as final goal. This paper focuses on the printing process from the whole of production processes, and describes the result of business process analysis to obtain the workerpsilas implicit knowledge. Until now the whole of business processes in the parts supplier have been examined by our previous researches, and we have mainly discussed the operation in printing process as a lot sizing scheduling problem only by theoretical aspect. However the previous approaches cannot flexibly respond to the change of production conditions such as the dispersion of order, the interrupt of urgent task, and the change of inventory quantity in spite of the actual field can handle these. Therefore this paper regards that the expertpsilas technical know-how of tacit knowledge in the actual printing field is mostly important factor in response to the change of production conditions, and the realities of lot sizing is grasped by the production performance records.
Keywords
automotive components; lot sizing; printing industry; business process analysis; empirical lot sizing rule; knowledge-based production scheduling software; printing process; production performance record; tacit knowledge; Automation; Automotive components; Automotive engineering; Frequency; Job shop scheduling; Lot sizing; Manufacturing processes; Printing; Production; Software prototyping;
fLanguage
English
Publisher
ieee
Conference_Titel
Automation Science and Engineering, 2008. CASE 2008. IEEE International Conference on
Conference_Location
Arlington, VA
Print_ISBN
978-1-4244-2022-3
Electronic_ISBN
978-1-4244-2023-0
Type
conf
DOI
10.1109/COASE.2008.4626463
Filename
4626463
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