Journal of The Japanese Society for Quality Control

Failure Mode and Effects Analysis (FMEA) is known as a useful method to analyze possible troubles which may ocour in a product or process during the design/development stage. The FMEA has not been widely applied in practice, however, due to some difficulties. Particularly, one of the main difficulties is the probability of omission of failure modes in failure mode prediction. This paper investigates problems on failure mode prediction, and proposes method to predict failure modes effectively. For this purpose, we analyzed causes of the omission of failure modes through investigation of actual prediction processes. As a result, some causes of the omission have been identified. Here we propose three approaches as follows to predict effectively failure modes with less omission. 1) Failure mode prediction based on "Association" 2) Preparation of Failure Mode Mechanism (FMM) diagram 3) Failure mode prediction based on "Hierarchy" We also verified effectiveness of the proposal through implementation of FMEA in a design group that developed a component of a car.

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The greater and more complex the system becomes, the more important its reliability and maintainability. Especially, condition monitoring maintenance becomes important for implementing rational maintenance activities timely which keep the system in good condition using monitoring equipments. The results of Karlin & Rubin^<[2]>p on statistical decision problems can be applied for the optimum maintenance activities on a single unit. They developed "monotone policy"; taking action "replace" if the monitored value θ is greater than θ*, and taking action "keep " if θis less than θ*, where θ* is a prespecified threshold value. They derived a sufficient condition that the optimal policy is restricted to "monotone policy". This paper deals with multiple units which are monitored simultaneously by multiple numbers of monitors. The true state of each unit cannot be observed directly, and the maintenance activities are implemented on each unit. A sufficient condition is derived that "monotone policy in wide sense" becomes optimal in view of a minimum expected risk.

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There are many discussion about the effects of product's quality/price on customer's buying will. They, however, have not been investigated empirically, with the previous researches using field customer reports failing to discriminate the effects of quality, price and others such as brand. This paper describes two applications of the experimental design methods, which have already been proved to be effective for putting product concepts into shape, to the identification problem of product's quality/ price and customer's buying will relationships, and clarifies the effectiveness and the matters to be attended to of such approach.

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Recently, production equipment plays the more important role in manufacturing. Therefore, production equipment management is essential to success in the management of production processes. In fact. Approaches for production equipment management such as TPM (Total Productive Maintenance) are being developed and widely applied. However, as it is not clear how much those approaches contribute to improvement of a financial constitution of a company, thee effects of the activities are ambiguous. This paper examines direct and related effects of production equipment management and identifies relations between the effects, decision-making items and financial indices. A structural model of the relations is established using the association diagram and the Interpretive Structural Modeling (ISM) method. Based on this model, in addition, the paper studies variation of financial indices and improvement effects of production equipment management qualitatively. The proposed model makes it possible to understand financial effects of the production equipment management and to evaluate the effectiveness of its management from the view points of a financial constitution. The paper gives a guideline to a systematic planning of production equipment management.

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