Failure Mode And Effects Analysis

Abstract

Every machine and process in manufacturing industry has its own modes of failure. In manufacturing industries, production machine failures can create many inconveniences. It may be responsible for machine downtime, unavailability, customer dissatisfaction, increased maintenance time and production costs, lower product quality, and delivery time delay. In chemical or nuclear plants, failures might be very expensive (catastrophic effects) in terms of money and safety. Failure Mode and Effects Analysis (FMEA) is a risk assessment tool that reduces potential failures in systems, processes, designs or services and has been used in a wide range of industries. When it is used in criticality analysis, it is also referred to as failure mode,

In 1960s aerospace industry first developed a formal design methodology for FMEA (Bowles &Pelaez, 1995) which was useful and proved to be a powerful tool in analysing potential failures and preventing such problems from occurring (Sankar&Prabhu, 2001). To identify and evaluate potential failure modes, causes and their effects on different component failure modes and finding a way to eliminate or reduce the chance of failure are the main objectives of FMEA. To improve the performance of a system during the stages of design and production, the results of the analysis can help analysts to identify and correct the failure modes that have a negative effect on the system.

There are several advantages offered by FMEA in improving quality and safety for different organizations. Just like in any other quality tools and techniques, it needs involvement of people from different expertise areas of an organisation, which thereby provides an opportunity to improve different functions of the organization to communicate and co-operate better (Kostina,Karaulova, Sahno, &Maleki,

This means the RPN scale is not continuous.

• S, O and D are qualitative factors, so to obtain precise and direct numerical judgements is difficult or even impossible.

• The judgements have a specific value of uncertainty and subjectivity which is difficult to handle.

Several alternative approaches have been suggested in the literature to overcome one or more of the mentioned limitations of the traditional FMEA methods. Artificial intelligence – fuzzy rule based approaches was found to be one of the most frequently studied class of approaches considering uncertainty according to the review conducted by Liu, Liu and Liu (2013). The reasons for these approaches being widely used are, first, consistent or precise numerical data and vague or imprecisely defined subjective information, second, flexible and realistic combining of probability of occurrence, severity and detectability of failure modes (Sharma et al., 2005), and finally, customized risk assessment function according to the particular product, system or process under consideration (Liu et al., 2013). The society accepts the LNG regasification facilities based on safety standards such as low risk for population and environment. The risks connected to new technologies used in these facilities should be analysed in depth for this purpose (Bernatik et al., 2011; Pitblado and Woodward, 2011;