Software Prototype for Optimization and Control of Manufacturing Processes

Modeling of manufacturing processes aimed at better understanding, optimization and process control is very important in manufacturing practice. This is usually achieved by integrating empirical models with classical mathematical and meta-heuristic algorithms. In this paper, software prototype “Function Analyzer” for optimization and control of manufacturing processes is presented. It is based on the mathematical iterative search of entire space of possible input values. This way, the developed software is able to determine global extreme points of the process model and corresponding input values (process optimization). Furthermore, it is able to determine the optimal input values that satisfy the specified requirements for output value and accuracy (process control). The developed software is characterized by extendible architecture, flexible user interface and efficient operation. The abilities of software prototype “Function Analyzer” were demonstrated on two case studies. The first one considers the regression based modelling of dry turning of cold rolled alloy steel. The second case study considers the artificial neural network based modelling of dry turning of unreinforced polyamide.