A Generalized Optimization Tool For
Manufacturing Processes
Author(s)
J. A. J. El-Sayed
Abstract
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
Keywords
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