Introducing failure analysis using Weibull analysis!
This document introduces Weibull analysis. In Weibull analysis, the number of failures is used as input to determine the unreliability. Once the unreliability is known, the failure rate and reliability can also be determined. (Refer to the relationship between failure rate and reliability) To express the bias in the occurrence of failures, Weibull distribution is used in failure analysis. By using Weibull distribution, it has become possible to express the bias in the occurrence of failures, including the probability density of failure occurrences.
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【Contents】 ■ Explanation of Weibull analysis ■ Figures 1 to 6 ■ Reliability in probability paper format (Cumulative failure probability density) *For more details, please refer to the PDF document or feel free to contact us.
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Our company develops and sells a "Maintenance Management System" for managing and operating various plants, factories, and other facilities and assets. Currently, this system is undergoing significant evolution into one that incorporates IoT technologies, such as sensor information and input from tablet devices, as well as AI technologies like machine learning, featuring functions for failure prediction and automatic scheduling. Additionally, as part of the recent trend towards digital transformation (DX), there is a growing movement to digitize and automate manufacturing processes and research and development sites in factories to enhance operational efficiency. In line with this trend, our company provides a solution aimed at improving efficiency in research and development environments, known as the Laboratory Information Management System (LIMS), which includes features such as workflow management, data tracking, data management, data analysis, and integration of electronic lab notebooks.