A new approach for the selection of advanced manufacturing technologies: DEA with double frontiers

Selection of advanced manufacturing technologies (AMTs) is an important yet complex decision which requires careful consideration of various performance criteria. This paper proposes the use of data envelopment analysis (DEA) with double frontiers for the selection of AMTs, which considers not only the best (optimistic), but also the worst (pessimistic) relative efficiencies of each AMT. Compared with the traditional DEA, the DEA approach with double frontiers can identify the best AMT correctly and easily without the need to impose any weight restriction or the need to calculate the cross-efficiency matrix, which requires a large number of computations and may also result in inconsistent conclusions by aggressive and benevolent cross-efficiency models. Four numerical examples are examined using the DEA approach with double frontiers to illustrate its simplicity and usefulness in AMT selection and justification.