Abstract:
Manufacturing process planning is the system of selecting and sequencing manufacturing processes such that they achieve one or more organizational goals and fulfill a set domain constraints. It is mainly a link between design and manufacturing and has vital role in the manufacturing systems. In this paper the under research industry is automotive manufacturing industry in Pakistan.
First of all a fundamental process plan is developed for a certain part manufacturing including all the user and design requirements and then it is modeled mathematically using progressive closed loop approach. Mathematically modeled process plan is then optimized in order to find optimal or sub optimal solutions. Research then explores the capabilities of optimization techniques in handling optimization of manufacturing process plan. Commonly used optimization techniques like Secant (simplex), Gradient Search methods, linear and DSM e.t.c., are employed on the case study to provide the best approximate process planning solution. Then complete optimization of the current Process Plan using Stochastic search techniques and incorporated non linear method and closed loop convex quality controls.
The linear as well DSM, stochastic search optimization using non linear method is performed is order to reach the optimal point where all the time activities are optimum. Finally a comparison will show the most optimum value/global optimum over which an optimized facility layout converges as well. The research examines the convergence of optimization techniques to an optimal solution for a reconfigurable manufacturing framework.
