WIT Press

A Generalized Optimization Tool For Manufacturing Processes


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Paper DOI



WIT Press


J. A. J. El-Sayed


With the recent advances in many areas of manufacturing process simulation, numerical optimization techniques can be used in every day decision making for different products. Decisions in an industrial setting are usually made to meet the desired objectives within a priority structure starting from the higher to the lower goals. In addition, most manufacturing process simulation techniques require a high level of nonlinear mathematical modeling. To address the high level of non-linearity and achieve an optimized setting for different manufacturing processes within the preset priority structure, Nonlinear Goal Programming multi-objective optimization models are the natural choice. This paper presents a nonlinear multi-objective optimization model that can be used in any industrial setting to optimize different manufacturing processes. The resulting nonlinear optimization problem is solved using zero order unconstrained optimization techniques. This reduces the effort required to model the metal forming process problem since linearization and gradients are not required. The optimum solution can also be achieved from any starting point, since feasibility conditions are not needed. The application and efficiency of the developed model is demonstrated for different manufacturing processes such as fixturing, metal forming, and metal cutting test cases. 1 Introduction The major difficulty in formulating optimization problems is to define the problem in a mathematical programming form in order to find a solution. This is due to the fact that most linear and non-linear optimization techniques deal with a single objective. Most common industrial and engineering optimization problems, however, have multiple and often conflicting objectives. These