A new approach to failure mode and effect analysis under linguistic Z-number: A case study of CNC tool holders

Failure Mode and Effects Analysis (FMEA), as the most important component of risk management, has been widely used in the engineering field. Although the method is widely used, the traditional FMEA approach does not take into account the issue of decision maker's mental preference, which seriously affects the accuracy of risk ranking results. To improve these shortcomings, we fuse the language set and Z-number to propose the language Z-number to express the decision information. Meanwhile, we propose a new linguistic Z-number weight Muirhead mean (LZNWMM) operator and use it to aggregate the information. Finally, we propose a new FMEA framework, which uses the proposed operator to aggregate information and calculate attribute weights using the fuzzy best-worst method. Using this method applied to a computer numerical control (CNC) tool holder manufacturer, its usability and validity are verified by comparing it with the traditional FMEA method, LZNWA method and LZNBM method.