TY - GEN digital ID - 131561552 TI - Advanced Multiresponse Process Optimisation : An Intelligent and Integrated Approach AU - Šibalija, Tatjana V. AU - Majstorović, Vidosav D. PY - 2016 SN - 9783319192550 PB - Cham Springer International Publishing DB - UniCat KW - Operational research. Game theory KW - Mathematical statistics KW - Applied physical engineering KW - Planning (firm) KW - Plant and equipment KW - Production management KW - Artificial intelligence. Robotics. Simulation. Graphics KW - Computer. Automation KW - neuronale netwerken KW - fuzzy logic KW - werktuigen KW - fabrieken KW - cybernetica KW - automatisering KW - besluitvorming KW - mathematische modellen KW - productie KW - econometrie KW - KI (kunstmatige intelligentie) KW - operationeel onderzoek KW - machines KW - ingenieurswetenschappen KW - robots UR - https://www.unicat.be/uniCat?func=search&query=sysid:131561552 AB - This book presents an intelligent, integrated, problem-independent method for multiresponse process optimization. In contrast to traditional approaches, the idea of this method is to provide a unique model for the optimization of various processes, without imposition of assumptions relating to the type of process, the type and number of process parameters and responses, or interdependences among them. The presented method for experimental design of processes with multiple correlated responses is composed of three modules: an expert system that selects the experimental plan based on the orthogonal arrays; the factor effects approach, which performs processing of experimental data based on Taguchi’s quality loss function and multivariate statistical methods; and process modeling and optimization based on artificial neural networks and metaheuristic optimization algorithms. The implementation is demonstrated using four case studies relating to high-tech industries and advanced, non-conventional processes. ER -