Process selection with multiple objective and subjective attributes

In the manufacturing sector, process selection is an important strategic consideration for improving competitiveness. We propose two simple and effective methods for process selection. After providing a detailed description of the general process selection problem with particular emphasis on attribute types, objective attribute values, subjective ratings and importance weights, we review an existing Multiple-Attribute Decision Making (MADM) method called TOPSIS, a Technique for Order Preference by Similarity to Ideal Solution (alternative) and describe briefly an operational performance measurement procedure called Operational Competitiveness RAting (OCRA). We show that these two methods are both distance based and strongly interrelated, and that they can be used for process selection decisions as well as operational performance measurement. Focusing on process selection, we demonstrate in detail the two methods' application and interrelationship through two examples. The selection decision in the examples is made on the basis of objective values of the attributes and their subjective ratings.