Product Mix Analysis using Soft Computing

Advanced Manufacturing Technology, deals with high flexibility, high speed, least waste and computer based soft-computing techniques and application of hybridized artificial intelligence. Organizations continually strive to achieve their goal, but the contention in any manageable system is limited in achieving more of its goal by very small number of constraints. Theory of Constraints represented as linear programming mathematical model provide an explicit solution. The constraints in the Product-Mix problem are further explored and exploited, which contain fuzzy, imprecise, vague and uncertain parameters of the system, are optimized using fuzzy numbers, rough sets and evolutionary algorithms. Data model using the artificial neural networks, the fusion of neural networks and fuzzy adapt to the imprecise and fuzzy parameters is demonstrated. Flexible Manufacturing System has been tested and verified for the product mix problem, and the ease of implementation show the usefulness to obtain an optimal solution and decision making in real world problems. The paradigm shift in the aspect of manufacturing, soft computing is a road to model the Factory of the Future.

Autorentext

Dr. Pravin Nikumbh is Professor of Computer Engineering, in Mumbai University. He has done his Master s in Systems and Information from BITS, Pilani, Rajasthan, India in the year 1991. He did his PhD from Jadavpur University, Kolkata, India in the year 2011. His areas of interest are Soft Computing, Intelligent Systems and Heuristic Search.