A short note on an intelligent system for selection of materials for progressive die components

Decision Support System for Designing with Polymer Materials – Current Challenges and Future Expectations

“…As presented in Subsection 6.1, the decision support system for selection of material for progressive die components was developed alternatively to manual material selection with material and die handbooks, heuristics and designer's knowledge and experiences (Kumar & Singh, 2007). The adequate material choice is one of major activities in die components design leading to increased die life and consequential costs reduction of sheet material and costs of production.…”

“…Most material selection methods are specific at some points and offer a vast amount of opportunities to build diverse decision support systems. Some are limited to only one group of materials (Edwards & Dang, 2007;Ullah & Harib, 2008) and some are focused on special group of engineering materials (Kumar & Singh, 2007). Decision support systems, which effectively support the designers at decision making process, are concentrated in knowledge base, specifically in human knowledge and experiences.…”

“…Material selection query occurs at designing various products. Kumar and Singh represented intelligent system for selection of materials for progressive die components, where two knowledge base modules are comprised (Kumar & Singh, 2007). One is designated as selection of materials for active and inactive components of progressive dies.…”

“…Alternatively to experts' acquired domain knowledge, we decided to develop an intelligent decision support system (Đurić & Devedžić, 2002;Edwards & Deng, 2007;Kumar & Singh, 2007;Novak & Dolšak, 2008;Turban et al, 2004;Vitanov & Voutchkov, 2005;Zhu et al, 2008) in order to overcome the bottle neck -plastics material selection (Ullah & Harib, 2008). In the input data are a significant factor for intelligent module performance, the results of which depend on knowledge base content.…”

Shape, sizing optimization and material selection based on mixed variables and genetic algorithm

“…In the latest literature, no work has introduced the idea of simultaneous optimization including the material selection under thermomechanical loading. This is due to the fact that gradient-based algorithms are mainly limited to continuous variables (Guisbiers and Wautelet 2007;Smith 2002, 2006;Fredricson 2005;Bendsoe et al 1994;Walker et al 1997;Rakshit and Ananthasuresh 2008;Kumar and Singh 2007;Ghoreishi et al 2007) and graph theory is limited only for discrete variables (Rao 2006). Rakshit (2008) considered the simultaneous optimization of geometry and material selection of statically determinate trusses as a continuous problem.…”