Modelling the relationship between product quality and process characteristics in process industry: an application

Abstract

Process industries have a relatively sophisticated and high capital density structure in manufacturing industries. Process industries are one of the leading industries having competitive advantage due to specialisation, huge amount of standard production and scale economies. In this paper, the goal programming (GP) technique is applied for quality improvement in beer manufacturing as an example of process industry. The main purpose of the constructed model is to determine the new and current standards of the manufacturing process variables, which affect the characteristics of product quality. The model is, basically, formed in three phases. The first is concerned with multiple-regression equations. In this phase, product characteristics are defined as dependent variables while the manufacturing process variables are defined as independent variables. In the second phase, the GP technique is applied to these equations and to other objective functions. In the last phase, the solution values obtained are used to redefine tolerances of variables called process control variables.