Fuzzy Logic based decision support systems in variant production

Autor: Nandkumar Gilke, A.U. Karmarkar
Rok vydání: 2018
Předmět:
Zdroj: Materials Today: Proceedings. 5:3842-3850
ISSN: 2214-7853
DOI: 10.1016/j.matpr.2017.11.638
Popis: In automobile industry, the product has many facets like engine, brakes, steering system, electronic instrumentation etc. The complex nature of modern automobile industry results in challenging environment for the manufacturer to satisfy customer requirements. Automobile manufacturers today develop products with certain variants for satisfying needs of a bigger group of customer. The customer then selects the option as per individual requirements from the choices available. In this paper a decision support framework is designed for family carsusing the fuzzy logic to assist the customer in selecting most suitable product from predefined product variants. The effectiveness and feasibility of the decision support framework are imperially validated by a case study wherein steering system and braking system are considered as decisive features. To get the most appropriate product as per the customer requirement, combinations of different membership functions such as Triangular, Trapezoidal& Gaussian are used for input as well as output variables. The system is then analyzed for product selection. The developed system is tested using MATLAB and also validated by center of sum and centroid methods. It is observed that input membership function as Gaussian function and output as trapezoidal membership function is mapped very well for decision making. The results are well endorsed by MATLAB for decision support.
Databáze: OpenAIRE