Soft Computing Technique for Product Design Suggestion in Smart Manufacturing Industry - Khatri, Jitesh Kumar; Kumar, Jyoti (Asian Review of Mechanical Engineering, 2015)
With the phenomenal growth in consumer durables industry, and more than ever before change and dynamism in the variety of design needs within the constraints of very limited time and investment, the urgent need of design automation is being recognized all over the world. To be able to capture the market through proactive launching of customer desirable products, the whole development cycle needs to be shrunk without any compromise of product features. This work suggests a fuzzy logic and ANN based noble design suggestion system which would assist the designers with a range of 3D design suggestions to choose from and take forward based on variable inputs from the market. This would facilitate faster designs through automation, reducing the overall design cycle time. The inputs for the design suggestions are based on anthropometry study and emotional behavior. Fuzzy logic is an efficient tool to choose the impact factor of a suggestion from a particular methodology based on the associated membership function and ANN has good learning capability and combination of both forms an efficient system for design suggestion.