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Abstract

In this article, design of failure mode and effect analysis (DFMEA) is a structured qualities analysis of the system, subsystem and components/functions that highlights impending failures modes of which their cause and effects of a failure on system operation. Few years ago, many industries are forced to use design of failure modes and effect analysis (DFMEA) technique to physically powerful their product design and manufacturing process due to the global competitive market. DFMEA is agreed out systematically by brainstorming. The aim of this paper is to in attendance a new approach for evaluation of RPN and failure modes to augment the utility of the traditional DFMEA technique. At the closing stages, the statistical method of the factor analysis was used to confirm the effectiveness.

Keywords: DFMEA; Failure modes and Factor Analysis; Risk Priority Number (RPN)

Introduction

This method is widely used during the process of design analyze of engineering system from their reliability aspect. It was described as an effective approach to analyzed of each potential mode in the system to examine the failure mode effects on the system. D FMEA also can be applied to various conducting engineering systems safety analysis. The history of DFMEA may be traced flipside to the early years of the 1950s with the development of flight control systems, when U.S Navy’s Bureau of Aeronautics, in order to widen a procedure for reliability control over the detailed design effort to developed a requirement known as Failures Analysis. There are so many factors that must be explored earlier than the implementation of DFMEA. Some of this factor which includes
(i) Examination of each and every conceivable failure mode by the involved professionals.
(ii) Measuring FMEA cost benefits.
(iii). Obtaining engineer’s approval and support.
(iv). Making decisions based on the risk priority number (RPN).

Design Failure Modes and Effect Analysis was an analytical technique old to design phase of a product development. It was a pro active technique worn to identify the weak points of a product design in early stage. Design Failure Modes and Effect Analysis was a specific tool used during product design phase to develop robust and more reliable product. Its aim to recognize and alleviate or eradicate the product failures earlier than releasing the production drawing for the manufacture.

RPN technique was commonly used in the automation industry, based on the risk priority number for an item failure mode based on three factors-
(i). probability of occurrence,
(ii). the severity of the failures effect, and
(iii). probability of failure detection.

The probability of occurrence is the like hood of failure, or relative number of failures, expected during the item’s useful life.

RPN= Occurrence× Severity× Detection

Failure modes with a high RPN are more critical and given a higher priority than ones with a lower RPN.

When the scales used range from 1 to 10, the value of an RPN will be between 1 and 1000. The scales and categories used.

Novel loom for Evaluation of RPN

Case Study-DFMEA for Buffering Machine (Tire Retarding plant).

The proposed methodology for evaluation of RPN was able to deals with the situation when:
(i). The FMEA team has a divergence in the rating scale S, O and D indexes, the RPN means are indistinguishable for more than one failure mode and the three failure indexes S, O and D are equally important.
(ii). The potential failure modes of a Buffering Machine are listed in Table-2. It shows that there is a incongruity in rating scale for S, O and D indexes. We calculated RPNs and their mean for all possible combinations of severity, occurrence and detection ratings. Various combination of S. O and D values are producing an identical value of RPN means 225. First priority should be given to the failure mode which has similar RPN range.

Statically Psychiatry and Argument

In this paper statistically tools have been used to assess the proposed RPN prioritization methodology. The results shown of each analysis provides sufficient evidence for the usefulness of the proposed method.

Descriptive Statistics

Buffering Machine shows that the means of the RPNs are indistinguishable. Standard deviation of the modes of failure are 65.273, 140.347, 226.779, 173.090 and 208.723. It shows that the most critical failure modes need to be addressed first. Similarly, it is one of the vital roles to be adapted the rank of the failure modes of a Buffering Machine.

Correlation Matrix

From the Table 3 it reveals that the correlation coefficient between a single variable and every other variable in the investigation.

Conclusion

In this paper, we had projected a new methodology for the evaluation of RPNs and the failure modes. Results of statistical analysis are hold up the utility of the proposed methodology. Thus, we conclude that the proposed methodology can be used successfully for the prioritization of failure modes in design failure modes and effect analysis (DFMEA), when:
? The DFMEA team has a disc
? agreement in to the rating scale for S, O and D indexes.
? The RPN means are identical for more than one failure mode.
? Three failure indexes S, O and D are equally important.

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