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In process improvement efforts, quality costs tite or cost of quality (sometimes abbreviated CoQ or COQ [1]) is a means to quantify the total cost of quality-related efforts and deficiencies. It was first described by Armand V. Feigenbaum in a 1956 Harvard Business Review article.
Cost of poor quality (COPQ) or poor quality costs (PQC) or cost of nonquality, are costs that would disappear if systems, processes, and products were perfect. COPQ was popularized by IBM quality expert H. James Harrington in his 1987 book Poor-Quality Cost. [1] COPQ is a refinement of the concept of quality costs.
Prevention, in the form of "pledging ourselves to make a constant conscious effort to do our jobs right the first time", is the only way to guarantee zero defects. Beyond that, examining the production process for steps where defects can occur and mistake proofing them contributes to defect-free production.
Failure analysis is the process of collecting and analyzing data to determine the cause of a failure, often with the goal of determining corrective actions or liability. According to Bloch and Geitner, ”machinery failures reveal a reaction chain of cause and effect… usually a deficiency commonly referred to as the symptom…”. [ 1 ]
Definition of quality: Quality is defined as conformance to requirements, with requirements encompassing both product specifications and customer expectations. Quality system: The quality management system should be based on defect prevention, rather than relying on inspection or correction after the fact.
Metallurgical failure analysis is the process to determine the mechanism that has caused a metal component to fail.It can identify the cause of failure, providing insight into the root cause and potential solutions to prevent similar failures in the future, as well as culpability, which is important in legal cases. [1]
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The first piece of information added in an FMEDA is the quantitative failure data (failure rates and the distribution of failure modes) for all components being analyzed. The second piece of information added to an FMEDA is the probability of the system or subsystem to detect internal failures via automatic on-line diagnostics.