Selection of a manufacturing process with multiple attributes: A case study

Decision makers in the manufacturing sector frequently face the problem of assessing alternative processes and selecting one based on a set of attributes. Process attributes with direct cost implication are not always explicitly identified and their indirect cost and benefits are generally not well quantified. This is a case study of the selection of a manufacturing process in a company that produces semiconductors. Regression analysis was used to identify the attributes with significant direct cost implication and rank the alternatives. A distance-based multiple attribute decision making method was adopted to determine the preference ranking with respect to operational benefits. Then, the two results were combined in a manner to reflect the subjective views of the decision makers involved to make the final selection. Managers and technical staff who would be affected by the choice of process understood the models used and were dedicated participants in the analysis.