DocumentCode :
2967590
Title :
Cost estimation of automotive sheet metal components using knowledge-based engineering and case-based reasoning
Author :
Karadgi, S. ; Müller, U. ; Metz, D. ; Schafer, Wilhelm ; Grauer, M.
Author_Institution :
Inf. Syst. Inst., Univ. of Siegen, Siegen, Germany
fYear :
2009
fDate :
8-11 Dec. 2009
Firstpage :
1518
Lastpage :
1522
Abstract :
Responding quickly to a customer´s request with a sufficiently precise offer is one of the challenges faced by almost every manufacturing enterprise. Currently, necessary information is passed from department to department and in many cases this information is waiting to be processed. Further, number of offers that are converted into orders is small making the process of preparing an offer relatively costly. Research has been carried out to automatically determine process plans and estimate cost of simple sheet metal components. Unfortunately, this research has not been extended to simultaneously determine process plan and cost of complex deep drawn components. To overcome these drawbacks and to substantially improve the efficiency and precision of the time consuming process of offer preparation, a new methodology is presented which utilizes knowledge-based engineering and case-based reasoning. Inputs obtained to create an offer can be used to generate basic tool structure for the downstream processes.
Keywords :
automotive components; case-based reasoning; costing; automotive sheet metal components; case-based reasoning; cost estimation; knowledge-based engineering; manufacturing enterprise; Assembly; Automotive engineering; Costs; Design engineering; Information systems; Knowledge engineering; Lean production; Manufacturing processes; Marketing and sales; Personnel; Case-based reasoning; cost estimation; deep drawn sheet metal component; knowledge-based engineering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-4869-2
Electronic_ISBN :
978-1-4244-4870-8
Type :
conf
DOI :
10.1109/IEEM.2009.5373084
Filename :
5373084
Link To Document :
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