Acquisition, Sharing and Utilization of Information for Preventing Quality and Safety Problems

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Results are summarized into the following four categories:1. System for Prevention of Quality and Safety Problems and Their Organization and Management FactorsTo prevent quality and reliability problems, a system which consists of seven steps is proposed and the importance of the following organizational and management factors is discussed : (1) Quality FLEA, Customer First Principle, (2) Culture which Can Open Problems, (3) Adaptation for Change, (4) Information Sharing and Communication, (5) Confidence on Each Member, (6) Ethics, Engineering and Education, (7) CSR Consciousness.2. Accumulation of Stress-Failure mechanism-Failure modes and its information sharingIf one cannot predict a risk in future, one cannot prevent it. Therefore, prevention based on prediction is important From this point of view, the method of prediction is discussed focusing on stress-failure mechanism-failure modes.3. Fail-safe and Error Proof for Prevention of ProblemsEven for long-time experienced products i … More n the market such as gas stoves, oil fan heaters, etc., they have to operate safely. In this case, fail safe design which fails safely when it fails must be applied. This method is discussed. Also, it is impossible to eliminate human errors completely. For this, error proof technique is a key. Focusing on information processing of human, systematic error proof methods are proposed.4. Investigation of Condition Monitoring Maintenance with Information TechnologyCondition monitoring maintenance plays an important role in preventing the failures of huge and complex systems. This research investigated an optimal policy for a condition monitoring system which comprises multiple sensors, and derived a necessary and sufficient condition under which an optimal procedure is given by a monotone procedure for both cases of independent and depend observations. This condition is given by the conditional probability matrix, which describes the relationship of sensors' observations and system's true state, having a property of Totally Positive of order 2 (TP_2)/ Weak Multivariate Likelihood Ratio (Weak-MLR) property for the case of independent/dependent observation. Less