An analytical hierarchical process approach for evaluating configuration performance in reconfigurable manufacturing systems

A Reconfigurable Manufacturing System (RMS) undergoes several structural changes in its lifetime in a bid to match variations in production demands. However, such frequent changes often lead to undesirable sub-optimal performance; hence, assessing the effect of reconfiguration changes on the overall system performance is crucial to the operation, management and control of an RMS. In this work, a multicriteria decision method is used to evaluate the impact of reconfiguration on the performance of a manufacturing system. The analytical formulation is based on the Analytical Hierarchical Process (AHP). The analytical functions are derived from fundamental operational characteristics of an RMS, which are mapped from machine-level to system-level attributes and culminate in an overall manufacturing performance index. Two techniques: point estimates and interval estimates, are used to handle inclusion of preference information in the decision making process. The suitability of the proposed approach is demonstrated through an experimental study that investigates reconfiguration effects in Multi-Product Lines. The results indicate that the interval estimates technique that is based on a reference attribute is more flexible and therefore more suitable for reflecting the effect of a new configuration on the overall manufacturing performance of an RMS.

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