تحلیل سلسله مراتبی(AHP) به عنوان یک ابزار تصمیم گیری استراتژیک برای توجیه انتخاب ماشین ابزار

Machine tool selection has strategic implications that contribute to the manufacturing strategy of a manufacturing organization. In such a case, it is important to identify and model the links between machine tool alternatives and manufacturing strategy. This study presents such a strategic justification tool for machine tools. With the new strategic justification tool, the evaluation of investment in machine tools can model and quantify strategic considerations. AHP and ANP are applied in calculation of the contributions of machine tool alternatives to the manufacturing strategy of a manufacturing organization. Hierarchical decision structures are formed in the application of the AHP and ANP approaches. Ranking scores which are used to rank the alternatives are obtained as outcomes of the applications. Application of the ANP approach also enabled the incorporation of interdependencies among the components of decision structures. An illustrative example is provided. The company management found the application and results satisfactory and implementable in their machine tool selection decisions.

For manufacturing companies, one of the starting points to achieving high competitiveness in the market is the selection of machine tools. Generally, return on investment (ROI) method is applied in justification of machine tools [10], [11] and [24]. Investments in machine tools are often accepted as stand-alone replacement projects, which do not improve the performance of a company enough to affect its strategic positioning against its competitors in the market [18] and [21]. However, the newest machine tools, namely machining centers, work independent of human operators, combine multiple machining operations performed by several conventional machine tools previously, and handle tool exchange, part exchange, and many activities automatically. They combine cost and time reducing efficiency features of specialized machines with the flexibility of conventional non-dedicated machine tools. The capability of accepting any one of a range of parts in random order provides advantages that have major implications for a firm in the market against its competitors, such that a strategic justification is necessary to incorporate the strategic benefits into the selection process of machine tools. In the literature, there are papers proposing models for machine tool selection problems. For example, Atmani and Lashkari [3], Tabucanon et al. [26], and Wang et al. [28] studied the machine selection problem for flexible manufacturing systems (FMS). However, a thorough study of the strategic implications of the machine tool selection decision is not available in the literature to the best knowledge of the author. This paper is along the lines of justifying stand-alone machine tools, and it focuses on the strategic implications of the machine tool selection decision and develops a model in which the strategic benefits of the machine tool selection decision are identified and quantified. In a strategic approach, it is necessary to build a bridge between manufacturing strategy and individual machine tool options [2]. A multi-level decision hierarchy and intermediate decision levels are required to link machine tool properties with the company’s manufacturing strategy. Furthermore, different types of evaluation criteria will exist in the decision hierarchy. Among the available multi-attribute approaches, only the analytic hierarchy process (AHP) approach has the capabilities to combine different types of criteria in a multi-level decision structure to obtain a single score for each alternative to rank the alternatives. In the literature, Arslan et al. [1], Lin and Yang [14] and Oeltjenbruns et al. [19] proposed AHP for machine selection problem. However, the proposed AHP models are limited in terms of strategic implications of their selection decisions. Another important observation related with the proposed AHP models is that none of them has the ability to handle interdependencies, or interrelationships, among the evaluation criteria. The justification criteria are assumed to be independent of each other, and their weights in the achievement of the company’s goals are calculated ignoring contributions to each other. However, to calculate real weight of a criterion, interdependencies among the criteria must be identified, quantified, and included into the calculation of weight of criteria in the machine tool justification problem. AHP cannot incorporate interdependent relationships among and within the levels of criteria. In such a situation, the general form of AHP, ANP (analytic network process), need to be applied along with AHP (see [4], [16] and [17]).

The ranking scores are the outcomes of the approach, and by definition a ranking score show the contribution of an alternative to the manufacturing strategy of a manufacturing firm. The user can obtain not only a ranking of the alternatives but also the degree of dominance among the alternatives using the scores. As the difference between two scores gets larger, the attractiveness of the higher-scored alternative, and consequently its dominance, increases compared to the lower-scored alternative. The application of the model also provides the weights for the components of the decision hierarchies. The firm can follow through the calculations and see the contributions of any component in the ranking scores. The components whose weights are high (above a certain threshold value determined by the firm) can be considered as critical ones; and the alternatives that score low in the critical components can be directly eliminated from further consideration. Such a two-level approach can especially be useful when the number of alternatives is higher than seven alternatives. In the literature, it is advised that less than seven alternatives should be pairwise compared to keep track of the pairwise comparisons previously made by the user. Although the approach can be used alone as shown in the illustrative example, it can easily be integrated with other approaches. For example, the presented strategic justification approach and economic analysis can be integrated in a two-phase machine selection framework. In such a two-phase process for machine selection, an economic analysis can be performed to reduce the number of potential alternatives to a manageable size in the first phase. Phase 2 may involve performing a detailed strategic analysis using the developed AHP/ANP model to select the most suitable one among the remaining alternatives. In a different possible application, the outcomes of the AHP/ANP approach can be input in a multi-objective mathematical programming application as weighting or a preference vector for machine tool alternatives (coefficients of the objective function). Such a combined model can consider resource limitations in the selection process and guarantees a feasible solution [23]. Badri [5] and [6] Ghodsypour and O’Brien [13], Schniederjans and Garvin [23] and Suresh and Kaparthi [25] illustrate the integration of the AHP approach with multi-objective mathematical programming approaches. To conclude, once properly introduced and implemented in a manufacturing company, the AHP/ANP approach provides a structure to the inclusion of strategic considerations by linking the machine tool alternatives and the manufacturing strategy. Furthermore, inclusion and quantification of the interdependencies that exist among manufacturing benefits using the ANP approach is an important contribution to the machine tool selection literature. Incorporation of interdependencies resulted in increases in the weights of the manufacturing benefits which contribute to other benefits.