This paper describes how the effects of possible component failures on an electrical system can be predicted through simulation of the correct behavior of the system, and repeated simulation of versions of the system containing faulty components. The results of such simulation are useful both for failure mode and effects analysis (FMEA), and for diagnosis. Such results have been used commercial...

For proper management of life cycle of machines and manufacturing facilities, it is important to perform appropriate maintenance operations, and to keep machine status for better reuse and recycling opportunity. For this purpose, a virtual maintenance system is very effective, where facility life cycle model is constructed in computer, and reliability and availability of machines are predicted ...

In this paper we propose a computer-aided solution with Genetic Algorithms in order to reduce the drafting of reports: FMEA analysis and Control Plan required in the manufacture of the product launch and improved knowledge development teams for future projects. The solution allows to the design team to introduce data entry required to FMEA. The actual analysis is performed using Genetic Algorit...

FMEA has been used for several years and proved its efficiency for system’s risk analysis due to failures. Risk priority number found in FMEA is used to rank failure modes that may occur in a system. There are some guidelines in the literature to assign the values of FMEA components known as Severity, Occurrence and Detection. This paper propose a method to assign the value for occurrence in mo...

Failure mode and effect analysis (FMEA) is a widely used reliability analysis and risk assessment tool in various industries. It is one of the most established project management techniques to identify and eliminate failures before actual manufacturing starts. In traditional FMEA, Risk Priority Number (RPN) ranking system is used to evaluate; the risk level of failures, to rank failures, and to...

Several reliability engineering approaches have been proposed to identify and recover from failures. A well-known and mature approach is the Failure Mode and Effect Analysis (FMEA) method that is usually utilized together with Fault Tree Analysis (FTA) to analyze and diagnose the causes of failures. Unfortunately, both approaches seem to have primarily focused on failures of hardware components...

Failure Modes and Effect analysis (FMEA) is a widely used technique for inductive safety analysis. FMEA provides engineers with valuable information about failure modes of system components as well as procedures for error detection and recovery. In this paper we propose an approach that facilitates representation of FMEA results in formal Event-B specifications of control systems. We define a n...

This article discusses the risk assessment of a health information system. A case study was conducted at the South Western Sydney Area Health Service to examine the potential risks of the Maternal and Infant Network (MINET) health information system using Failure Mode Effect Analysis (FMEA). FMEA was conducted by utilising safety attributes identified by the authors. Potential failure modes of ...

Despite of the popularity of the fuzzy Failure Mode and Effects Analysis (FMEA) methodology, there are several limitations in combining the Fuzzy Inference System (FIS) and the Risk Priority Number (RPN) model. Two main limitations are: (1) it is difficult and impractical to form a complete fuzzy rule base when the number of required rules is large; and (2) fulfillment of the monotonicity prope...

Failure mode and effect analysis (FMEA) is a useful tool to define, identify, and eliminate potential failures or errors so as to improve the reliability of systems, designs, and products. Risk evaluation is an important issue in FMEA to determine the risk priorities of failure modes. There are some shortcomings in the traditional risk priority number (RPN) approach for risk evaluation in FMEA,...