Heuristic techniques for modelling machine spinning processes

Abstract

AbstractIn spite of many efforts made a complete model of machine spinning processes, due to its complexity, multidimensionality of the decision space and the present state of knowledge, is unachievable. The paper addresses the issues of constructing a local process model to enable the search for a locally optimal course of the process, within a short time and with the cost as low as possible. Comparison was made between the theoretically well-grounded response surface designs method with a few approaches to the model construction based on intuitively understood heuristic bases justified by their successful practical applications. In order to determine a set of Pareto-optimal solutions for a discrete decision space, the durations of process execution were generated through a virtual simulation. In order to outline and justify the adopted solutions a comprehensive example of the practical construction of the machine spinning process model was presented, including its various versions. The results obtained were validated and evaluated. The main utilitarian conclusion is the indication whereby basing on a partial experiment plan it is possible, thanks to simple heuristic methods, to obtain Pareto-optimal solutions which are close to those obtained when the full experiment plan is carried out.