Research On FMEA Improvement And Application Within Complex And Uncertain Environment

Nowadays failure mode and effect analysis(FMEA)has evolved as a received risk management technique which is broadly utilized in various industries to recognize,evaluate and remove potential failure modes of products,systems,service,and/or process.The traditional FMEA adopts risk priority number(RPN)method to rank the identified failure modes,which has suffered from much criticism for its intrinsic deficiencies.With the development of science and technology,customer demands for products and service become increasingly diversified,while the traditional FMEA is no longer suitable to be applied in the complex and uncertain environment because of its inherent limitations.Therefore,this paper put forward three novel FMEA models under different conditions to surmount the drawbacks of the conventional FMEA method and enhance its performance in reality.The main work of this dissertation can be summarized as below:(1)Lots of theories and approaches have been published to effectively address the known shortages in the traditional FMEA,but few contributions are devoted to summarizing the research achievements in this field.Thereby,based on 269 peer-reviewed journal articles which published between 1998 and 2018,a bibliometric review on FMEA improvement is undertaken with the aid of Cite Space to reveal the development and research foci in this field.(2)A new approach for FMEA based on linguistic distribution assessments and TODIM(an acronym in Portuguese of interactive and multicriteria decision making)method is proposed.Particularly,linguistic distribution assessments are applied to represent FMEA team members' risk evaluation information and an improved TODIM method is employed to determine the risk priority of failure modes.Furthermore,both subjective weights and objective weights of risk factors are taken into account while conducting the risk analysis process.Finally,an empirical case concerning the risk evaluation of a grinding wheel system in numerical control machine is presented to validate the practicality and effectiveness of the new FMEA model.(3)An innovative FMEA model combining linguistic Z-numbers and an extended projection method is developed to represent experts' risk evaluations and rank failure modes.Specifically,FMEA team members adopt linguistic Z-numbers to express their risk assessments and the reliability of the evaluation results simultaneously.The normal projection method is extended to determine the risk priority ranking of failure modes.Moreover,the ordered weights are calculated by the minimal variance weighting method when aggregating the individual evaluation information.Meanwhile,the relative weights of risk factors are derived objectively based on TOPSIS(the idea of technique for order preference by similarity to ideal solution)method.Finally,a practical case about risk evaluation of aircraft landing system is performed and a comparison study is also undertaken to demonstrate the rationality and applicability of the proposed FMEA framework.(4)A new FMEA approach using proportional hesitant fuzzy linguistic term sets(PHFLTSs)and prospect theory is devised to evaluate the orderings of risk for failure modes.The PHFLTSs are utilized to cope with the risk assessment information elicited from FMEA team members,whilst an extended prospect theory is employed to determine the priority ranking of the recognized failure modes.Further,the relative weights of risk factors are derived based on the best-worst method(BWM).Finally,an illustrative example regarding hospital service diagnosis is implemented and some comparative methods are discussed to substantiate the availability and superiority of the proposed FMEA.Based on the proofs provided by the real-life cases and the comparison studies,it is authenticated that the proposed three new models can efficiently remedy the defects rooted in the classical FMEA within different complex and uncertain contexts and enhance the performance of the traditional FMEA in practice.