Evaluation of environmentally conscious manufacturing programs using multiple attribute decision-making methods

Abstract

Manufacturers are increasingly under pressure from their major stakeholders to integrate environmental issues in the design and management of their products. These stakeholders include customers, regulators, employees, communities, and interest groups who have a common stake in protecting the earth from pollution and in limiting the exploitation of earth's limited natural resources. Manufacturers recognize that being environmentally responsible also offers competitive advantage to the firm. An environmentally responsible or environmentally conscious manufacturing (ECM) program addresses the environmental impact of the interrelated decisions that are made at various stages of product life, from conception to design, raw materials consumption, processing, delivery, use, recycling, and/or disposal. The evaluation of alternative ECM programs for producing a given product is similar to many strategic initiatives and their justification methodologies. This similarity arises from the fact that there are multiple attributes that need to be considered, many of which have long-term and broad implications for an organization. This paper presents three multiple attribute decision-making methods for evaluation of environmentally conscious manufacturing (ECM) programs for producing a given product. These methods are based on the analytic hierarchy process (AHP), the technique for order preference by similarity to an ideal solution (TOPSIS), and the modified TOPSIS method. The proposed ‘ECM program selection index’ helps to evaluate and rank the ECM programs for producing a given product. An example is included to illustrate and compare the methods. It is proposed that the most sensible approach to select a particular alternative ECM program from among the given alternatives is to apply several valid decision-making methods to the same selection problem and then to make the final selection on the basis of aggregation of the results of those decision-making methods that have a very significant positive relationship.

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