FMECA Case Study 4.1 Traditional Feca

If the expectancy of the attributes or criteria is larger the better;

= (2)

If the expectancy of the attributes or criteria is smaller the better;

= (3)

where; and are the maximum and minimum value of each alternative respectively.
Normalized decision matrix is as follows;

= (4)

(4) Calculate preference variation value for all criteria as per following equations;

= ] (5) where; = (6)

(5) Calculate deviation in preference value for all criteria as per following equations;

= (7)

(6) Calculate overall preference value for all criteria as per following equations;

= (8) (7) Calculate the maintainability criticality index of each alternative as follow;

= (9)

The criticality ranks (priorities) of
Case Study

4.1 Traditional FMECA

FMECA is based on systematic brainstorming session to recognize the failures which may occur in system or process and it is devoted to determine the design reliability by considering the potential causes of failures and their effects on system under study. It provides an organized way of identifying criticalities based on its risks and considered as the final point in failure investigation.
The score for each individual failure mode for every process input of critical components are decided on; (i) historical failure data; which gives comprehensive behavioral study of failure pattern of critical components and (ii) questionnaires; to floor operators, managers, maintenance personnel. The scores for detectability (D), probability of occurrence (P) and severity of effect (S) is ranked as per Table 1, Table 2 and Table 3 respectively.
Appropriate score has been assigned to each failure mode and Rank Priority Number (RPN) is calculated. Based on achieved RPN and analysis of existing maintenance strategies; revised and effective maintenance methodology has been suggested.

Table 1 Scores for detection of failure (D)
Chances of detection Likelihood