The Study and Application of FCE for a Metrology Equipment Selection Case
|School||South China University of Technology|
|Keywords||Metrology Equipment Selection FCE (Fuzzy Comprehensive Evaluation) Evaluation Index System|
It is common sense that metrology management is foundation for process control andquality management in modern industry. The selection of metrology equipment is the key rolein establishing the measurement standard, and closely concern with the level of metrologymanagement. However, the study on the selection of metrology equipment is very scarce formany reasons. And it is not proper for apply normal equipment selection methodsmechanically on metrology equipment which contain some specialty that should not beenignored in model design.The selection of metrology equipment is multi-scheme and multi-objective complicateddecision-making process which concerns the applicability, the reliability, and the cost ofequipment in life cycle, and the selection of standards. Some of those are difficult to bequantified. The mainstream evaluation approach is establish evaluation index system byExpert Investigation (Delphi Method especially) firstly, then reweighting by AHP (AnalyticHierarchy Process). The routine process, however, is facing many problems in practice on theselection of metrology equipment，sort of which theoretical defects. In the study, In the study,the vagueness of the evaluation indexes that is difficult to quantify required employment ofFCE (Fuzzy Comprehensive Evaluation) on the reference degree of information source andconstruct the Judgment Matrix, which based on the sample standard deviation of the values ofthe reference degree, then amend by Optimal Transfer Matrix Method which is lesscalculation and meaningful if Judgment Matrix failed in consistency test. The eigenvector ofthe final matrix are the weight value of the evaluation indexes, multiply the FuzzyComprehensive Evaluation Matrix which derived from the conception of MembershipFunction, results the values of evaluation, to make a conclusion. Both in qualitative researchand quantitative analysis, the approach minimizes the subjective randomness and uncertaintyof mind, based on the make full use of the expert knowledge and through the regular, concise,and less time consuming algorithm. It is easy and simple to handle, could extended inapplications. In the end, the validity of the model is illustrated by a case.