Failure mode and effects analysis using a group-based evidential reasoning approach

Introduction

FMEA refers to a methodology used in evaluation of a given system, its design, and process or service to find out possible failures, their impact and the various causes of the failures. It’s normally a group decision making process whose team whose members demonstrate varying knowledge and opinions and hence coming up with different kinds of assessment data. This paper describes an FMEA by use of Evidential Reasoning(ER) approach which is a methodology that has been newly developed and which helps in the analysis of multiple attribute decision.  The illustration of this FMEA is done using a fishing vessel application.  The paper uses a descriptive method to relay the information, where ER approach is used to develop a risk priority model which can incorporate risk factors relative significance and at the same time form a model on uncertainty and diversity of FMEA assessment information. The results from the study is that regardless of assessment is done by team members, the approach of the proposed FMEA is applicable. The paper concludes with proposing the adoption of this FMEA that uses ER- approach that is group based and which can tap the diverse opinions of team members for prioritizing failure modes when under various kinds of uncertainties (CHRYSOSTOM & DWIVEDI, 2013).  

Contributions

 The FMEA methodology addresses the need to understand scientific ways of carrying out potential failure research and analysis of effects of the failures and the advantages of group based opinions in comparison to individual opinions on analysis. In the evidence reasoning approach each member of the FMEA team provides their assessments of the possible failures and the individual opinions are rated and the degree of failure is then assessed using some given intervals (CHRYSOSTOM & DWIVEDI, 2013). The paper provides an important method which allows team members to have an understanding on overall risk of every failure mode, and these modes are assessed to high intervals or ratings with the highest degree of rating representing more risk as compared to those with low intervals or rating. This FMEA methodology approach also portrays the importance of assumptions used in dealing with information assessment , and how different assumptions influence on individual analysis outcomes .The failure risk assessment for each team  member can be integrated  group structures that can be used to rate the expected risk by use of risk scores (CHRYSOSTOM & DWIVEDI, 2013). The method also provide various ways that team members can do their evaluations either as a group or individuals , and the tabulation and synthesizing of results is done separately while applying their importance weights. The evaluations can be carried out together in a room while leaving the team members to choose how to carry out their evaluations. The importance of reaching a consensus on every valuation made is highlighted since such a consensus will not require the assignment of any weight to the team members’ results.

The FMEA method allows the development of a risk priority model by use of ER approach that is group based and this includes evaluation of risk factors by turning individual opinions into group opinions and finding an aggregate of the group opinion which are turn into some overall opinions. The overall opinions are converted to anticipated risk score and the risk scores are ranked by use of MRA.  Through this the method considers the risk factors weights that are quite deterministic. It is also possible to reflect on the uncertainty and diversity of the assessment performed by team members whose opinions can have better outcomes in spotting failures (CHRYSOSTOM & DWIVEDI, 2013).  The method also allows the inclusion of multiple risk factors and there is no need for building rule basis that can be very subjective.

Evaluation

The use of this method of prioritizing risk and failures has various importances one of which is the advantage of changing the results in accordance with uncertain factors effects. What this means is that more accurate results can be obtained which can help in boosting the system or process to handle the uncertainty (CHRYSOSTOM & DWIVEDI, 2013). The conclusion of the article properly states that prioritizing of failures according to opinions from different individuals assist in eliminating any biases associated with working as a group. Evidence based reasoning help to analyze the relationship among risk facing different system components and hence allowing for corrective actions to be taken in a system or process. This relationship defines the available alternatives which when prioritized, the ones with more influence are chosen over those with low priority. Given the above stated reasons this approach is fairly good for risk and effects analysis in process or system evaluation.

Suggestions

For the method to be more effective, I would recommend further research on how various risk factors and priority levels’ functions can be assigned to every team members. Another future research area is how to make the process less tedious since no single rule is applied but many rules are used. In addition, a research should focus on the appropriate software for risk factors and failure prioritizing.

Reference

CHRYSOSTOM, S., DWIVEDI, R., (2013).A review on the methodologies used in failure modes and effects analysis (FMEA). International Journal of Mechanical and Production Engineering. Vol-1., 6,. 13-14

Chin, K. S., Wang, Y. M., Poon, G. K. K., & Yang, J. B. (2009). Failure mode and effects analysis using a group-based evidential reasoning approach. Computers & Operations Research, 36(6), 1768-1779.