Taghavifard, T., Pooti, P. (2013). Design and Development of Decision Support System for Ranking Rapid Prototyping Techniques and Selecting the Best Technique in Automobile Industry. Journal of Information Technology Management, 5(2), 1-22. doi: 10.22059/jitm.2013.36525
Taghavifard Taghavifard; Pooti Pooti. "Design and Development of Decision Support System for Ranking Rapid Prototyping Techniques and Selecting the Best Technique in Automobile Industry". Journal of Information Technology Management, 5, 2, 2013, 1-22. doi: 10.22059/jitm.2013.36525
Taghavifard, T., Pooti, P. (2013). 'Design and Development of Decision Support System for Ranking Rapid Prototyping Techniques and Selecting the Best Technique in Automobile Industry', Journal of Information Technology Management, 5(2), pp. 1-22. doi: 10.22059/jitm.2013.36525
Taghavifard, T., Pooti, P. Design and Development of Decision Support System for Ranking Rapid Prototyping Techniques and Selecting the Best Technique in Automobile Industry. Journal of Information Technology Management, 2013; 5(2): 1-22. doi: 10.22059/jitm.2013.36525
1Assistant Prof. of AllameTabatabaei´ University, Industrial Engineering, Tehran, Iran
2M.Sc. in Information Technology Management, AllameTabatabaei´ University, Tehran, Iran
Abstract
The development of a number of different rapid prototyping (RP) technologies with wide-ranging capabilities, features and applications has created the problem of selecting an appropriate RP system for engineering educational institutions as well as manufacturing organizations intending to adopt this new technology. This paper presents an RP Decision Support System (RP DSS) for ranking and selecting a rapid prototyping technique. Three phases of the research, identification-design and development-implementation and test, were deployed RP DSS subsystems: data management, model management and user interface. Data management subsystem contains data for 51 different RP systems. Model management subsystem contains the scoring model approach MADM chosen as the analytic model in model base. TOPSIS is modified to treat decision data extended to fuzzy numbers. RP DSS was implemented in automobile industry. The part considered to test is Front Bumper Grille, one part of automobile with important duty of exchanging heat with environment, because of functional test. Based on data entry to RP DSS with expert user, EOSINT P700 was determined as best RP technique in this application.
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