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[Book] Implementation of Accelerated Testing and Product Life Prediction (No. 2201)

【Available for preview】★ Lifespan prediction from sparse data and small data! What is the new method to improve accuracy?

Book Title: Implementation of Accelerated Testing and Product Life Prediction Using Models ★ Planning of accelerated testing, setting conditions, and formulating life prediction equations based on material degradation mechanisms! ■ Key Points of This Book ● Planning, implementation, and how to write and read plots for accelerated testing - Calculation methods for coefficients used in life prediction models - How to write and read plots using the Arrhenius model, Eyring model, and Larson-Miller type - How to write and read S-N curves used for applying the Miner rule - Types, characteristics, and usage of accelerated testing equipment ● Life prediction when data collection is challenging, high-precision product life prediction methods - Life estimation using sparse data - Life prediction based on small data - Life prediction through simulation - High-precision product life prediction methods combining analytical instruments and numerical analysis

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Quality relevance and lifespan prediction using data mining.

Recommended technical proposal for customers considering the measurement of the effectiveness of predictive maintenance and equipment management operations, as well as quality improvement! Utilizing large-scale data and machine learning as well!

This document explains, based on our company's implementation results and experience, the necessary considerations for threshold examination that inevitably arise when conducting predictive maintenance, as well as what indicators should be used when considering and implementing predictive maintenance. Additionally, we focus on the analysis of causal relationships with quality-related issues, which we have received many inquiries about in recent years, in conjunction with equipment maintenance. When building IoT and predictive maintenance systems, it is essential to start with a system that has a completion level of around 60 or 70 points, rather than aiming for a perfect 100-point system from the outset, and to gradually improve the system towards the desired state. This document introduces some of the essence of that approach.

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Reliability life prediction using Weibull analysis

Free seminar ongoing! An easy-to-understand introduction to Weibull analysis.

Weibull analysis is a method that uses the number of failures as input to determine the unreliability. Once the unreliability is known, the failure rate and unreliability can also be determined. Our company regularly holds free seminars on Weibull analysis. We provide clear explanations from the basics of reliability data analysis to an overview of Weibull analysis and representative methods. For more details, please check below. https://www.wavefrontsales.com/teikiseminar/weibull/

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