Cost estimation for sheet metal parts using multiple regression and artificial neural networks: A case study
Autor: | Dirk Cattrysse, Joost Duflou, Bart Verlinden, Philippe Collin |
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Rok vydání: | 2008 |
Předmět: |
Economics and Econometrics
Artificial neural network Cost estimate Computer science Process (computing) Regression analysis Management Science and Operations Research computer.software_genre General Business Management and Accounting Industrial and Manufacturing Engineering visual_art Linear regression visual_art.visual_art_medium Data mining Sheet metal computer |
Zdroj: | International Journal of Production Economics. 111:484-492 |
ISSN: | 0925-5273 |
Popis: | Increasing competition in sheet metal operations has urged those companies to search for tools that generate accurate cost estimates within a short time period. The requirement for on-line generation implies that the underlying cost estimate needs to be generated without extensive process planning first. Analysis has been conducted on developing a less-detailed method, based on a brief analysis of the CAD-file. Cost formulas are composed by applying regression techniques and neural networks. A case study is used to compare both methods. The results obtained indicate that neural networks give better results but are still mainly considered black boxes. |
Databáze: | OpenAIRE |
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