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Life expectancy prediction Product List and Ranking from 6 Manufacturers, Suppliers and Companies

Last Updated： Aggregation Period:Sep 17, 2025～Oct 14, 2025
This ranking is based on the number of page views on our site.

Life expectancy prediction Manufacturer, Suppliers and Company Rankings

Last Updated： Aggregation Period:Sep 17, 2025～Oct 14, 2025
This ranking is based on the number of page views on our site.

  1. ウェーブフロント 本社 Kanagawa//software
  2. スイスビットジャパン Tokyo//Electronic Components and Semiconductors
  3. TECHNICAL INFOMATION INSTITUTE CO.,LTD Tokyo//Service Industry
  4. 4 マグナ・インターナショナル・ジャパン マグナパワートレイン・ECS（Engieering Center Steyr） Tokyo//Automobiles and Transportation Equipment
  5. 4 日本テクノセンター Tokyo//others
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Life expectancy prediction Product ranking

Last Updated： Aggregation Period:Sep 17, 2025～Oct 14, 2025
This ranking is based on the number of page views on our site.

  1. Reliability life prediction using Weibull analysis ウェーブフロント 本社
  2. Flash Product Lifespan Predictions You Should Know (2) スイスビットジャパン
  3. [Book] Deterioration, Destruction Evaluation and Lifetime Prediction (No. 2294) TECHNICAL INFOMATION INSTITUTE CO.,LTD
  4. FEMFAT weld extension module: Fatigue life prediction of welded joints マグナ・インターナショナル・ジャパン マグナパワートレイン・ECS（Engieering Center Steyr）
  5. 4 Practical Guide: Failure Analysis and Lifetime Prediction of Rubber and Resin Products 日本テクノセンター

Life expectancy prediction Product List

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Practical Guide: Failure Analysis and Lifetime Prediction of Rubber and Resin Products

Practical Guide: Failure Analysis and Lifetime Prediction of Rubber and Resin Products

Practical Guide: Failure Analysis and Lifetime Prediction of Rubber and Resin Products

A practical book written by 20 frontline professionals from 15 companies across various levels of materials, components, and systems, based on their extensive experience, data, and numerous case studies. 【Features】 ○ Chapter 1: Demand Trends and History of Rubber and Resin ○ Chapter 2: Reliability Assurance Activities and Approaches to Failure Analysis ○ Chapter 3: Composition ○ Chapter 4: Failure Mechanisms ○ Chapter 5: Analytical Methods ○ Chapter 6: Lifetime Prediction Methods ○ Chapter 7: Reliability Testing ○ Chapter 8: Case Studies on Rubber Materials, Components, and Products ○ Chapter 9: Case Studies on Resin Materials, Components, and Products ○ Chapter 10: Case Studies on Rubber and Resin Products ○ B5 Size, Hardcover, 383 Pages ○ Published in April 2002 ● For other functions and details, please contact us.

  • others

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Flash Product Lifespan Predictions You Should Know (3)

Flash Product Lifespan Predictions You Should Know (3)

Easily check the remaining lifespan and replacement timing of SSDs and memory cards, as well as signs of errors, on the operating system. This helps avoid unexpected system shutdowns and data loss.

= Lifespan Diagnosis and Lifespan Prediction = To maintain high performance and data retention capabilities, as well as stable operation during long periods of continuous use, we recommend products optimized for the application, installation environment, and write/read/erase cycles of the system by combining appropriate functions and advanced technologies. Lifespan measures for NAND flash-based storage involve various technologies and functions aimed at maximizing storage lifespan optimization, such as reducing WAF through page-based FTL technology, decreasing the number of block erasures by implementing cache DRAM and garbage collection, and using over-provisioning techniques to increase durability and performance by expanding spare areas. However, accurately understanding the lifespan of storage in practice is very difficult, for example, estimating lifespan or predicting lifespan-related changes from the software access profile on the system (host) side. At Swissbit, the "firmware" and "lifespan diagnosis tool" enable easy visualization of WAF and realistic lifespan predictions, allowing for timely and reliable decisions based on the remaining lifespan of the installed storage and signs of errors, thus preventing unexpected operational downtime and data loss.

  • Storage
  • SSD
  • Memory

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[Book] Deterioration, Destruction Evaluation and Lifetime Prediction (No. 2294)

[Book] Deterioration, Destruction Evaluation and Lifetime Prediction (No. 2294)

[Available for preview] - Polymers / Composite Materials / Coatings / Adhesives / Ceramics / Metals / Concrete -

Book Title: AI, Deterioration and Destruction Evaluation and Lifetime Prediction Using Simulation －－－－－－－－－－－－－－－－－－－－－ ★ An objective lifetime prediction method that replaces the experience of skilled analysts and advanced expertise through machine learning! ★ Rapid strength evaluation combining equipment analysis and computational science, detecting slight deterioration, deformation, and defects! －－－－－－－－－－－－－－－－－－－－－ ■ Key Points of This Book ● Preparation of data for evaluation and prediction, key points for prediction formulas and model building ● Evaluation and prediction examples using machine learning and simulation

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  • Technical and Reference Books

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Flash Product Lifespan Predictions You Should Know (1)

Flash Product Lifespan Predictions You Should Know (1)

Low cost with high reliability and amazing rewrite lifespan! Reduced WAF to the limit, achieving high performance and long lifespan with SLC-level random write performance!

=durabit(TM) - The better MLC = This is a storage product with high rewrite endurance due to WAF reduction measures. The block rewrite lifespan of NAND Flash memory is 100,000 times for SLC type, 20,000 times for pseudo-SLC, and 3,000 times for MLC. However, when used in NAND storage, the lifespan values differ from those of NAND alone due to data management by the controller and firmware. To address the lifespan issues of MLC NAND-equipped storage, we consider the ratio coefficient of the amount of write data from host to storage to NAND (WAF number: ideal value is 1) and incorporate high-performance page-based FTL firmware technology, which minimizes the increasing WAF value to the extreme, achieving rewrite lifespans comparable to SLC even with MLC. WAF, known as write amplification rate, is influenced by hundreds of conditions, including the specifications of NAND flash, firmware technology, and data management structure, causing its value to fluctuate. Additionally, it is affected by the IOPS rate; for instance, if the WAF value is 10, the number of erasures within the storage becomes ten times that of the external data amount, leading to a lifespan that is reached ten times faster than predicted for NAND alone.

  • Embedded Board Computers
  • SSD
  • Storage

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Flash Product Lifespan Predictions You Should Know (2)

Flash Product Lifespan Predictions You Should Know (2)

High-performance page-based FTL technology enables long lifespan with high rewrite endurance even in storage equipped with MLC-type NAND flash!

The lifespan of storage equipped with flash memory is primarily determined by the maximum number of write/erase cycles of the installed NAND flash memory. The block erase cycles (lifespan) of NAND flash are generally 100,000 for SLC type, 20,000 for pseudo-SLC, and 3,000 for MLC. However, when used as storage, the actual lifespan in operation differs from that of the NAND alone due to data management by the controller and firmware. During data writing, the controller may erase and write to multiple blocks of NAND flash within the storage, even if the data size transferred from the host is minimal, following internal management steps. Swissbit's durabit(TM) MLC storage significantly improves durability performance by using advanced page-based FTL mapping to eliminate the effects of read disturb, along with error handling through read refresh and ECC, and read retry processing to improve uncorrectable pages depending on temperature conditions. It is a high-performance model of MLC NAND-equipped storage that combines over-provisioning features, cache DRAM, and PBM (page-based mapping).

  • Storage
  • SSD
  • Other embedded systems (software and hardware)

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Book: "Degradation and Lifetime Prediction of Polymer Materials"

Book: "Degradation and Lifetime Prediction of Polymer Materials"

Understand the key points necessary to obtain practical lifespan predictions, and learn the mechanisms and concepts of lifespan from actual prediction cases of polymer materials for different applications.

○Publication Date: November 24, 2009 ○Format: B5 size hardcover, 451 pages ○Price: 66,000 yen (excluding tax) → STbook member price: 62,667 yen (excluding tax) ○Supervised by: Yoshito Otake, Japan Chemical Evaluation and Research Institute ○Authors: Yoshito Otake (Japan Chemical Evaluation and Research Institute) / Kazumi Nakayama (Japan Chemical Evaluation and Research Institute) / Masayuki Ito, Waseda University / Minoru Shinbo, Kanazawa Institute of Technology / Jun Kato, Nissan Arc Co., Ltd. / Noriaki Wada, Bandō Chemical Co., Ltd. / Kazuo Nishimoto, Nichias Corporation (former investigator at the High Pressure Gas Safety Institute, Liquefied Petroleum Gas Research Institute) / Kiyoo Kato, Asahi Kasei Chemicals Corporation / Tomohiro Fukuhara, Omron Corporation / Makihito Morii, Omron Corporation / Naruyuki Mitaji, Tokyo University of Technology / Yoshihisa Kano, Furukawa Electric Co., Ltd. / Akira Motoyama, Panasonic Electric Works Analysis Center Co., Ltd. / Takafumi Iida, Nagase ChemteX Corporation / Eiichi Sugimoto, Dengi Ken Co., Ltd. / Toshihiko Aihara, Nissan Motor Co., Ltd. / Yoshihisa Tajima, Polyplastics Co., Ltd. / Mikihiro Ito, Railway Technical Research Institute / and 5 others.

  • Company：S&T出版
  • Price：10,000 yen-100,000 yen
  • Technical and Reference Books

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FEMFAT weld extension module: Fatigue life prediction of welded joints

FEMFAT weld extension module: Fatigue life prediction of welded joints

Practical element division (shell elements) & evaluation method of SolidWELD

In the development of components that include welded structures, accurately predicting the fatigue life of weld joints has become essential. By utilizing FEMFAT weld, precise fatigue life predictions for weld joints can be achieved. FEMFAT weld offers various functions, including sensitivity analysis to identify critical welding shape parameters and evaluation options compliant with standards such as BS7608 and Eurocode 3. When calculating the fatigue life and safety factors of welded structures, the highly flexible analytical methods implemented in FEMFAT weld allow for simultaneous analysis of shell element models and solid element models. For the evaluation of weld root areas and weld termination points, detailed modeling of the fillet shape of the evaluation area can be performed, eliminating the need for extensive manual work. *For more details, please download the PDF or contact us.*

  • weld 1.png
  • weld 2.png
  • weld 3.png
  • Structural Analysis

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Quality relevance and lifespan prediction utilizing data mining

Quality relevance and lifespan prediction utilizing data mining

Recommended technical proposal for customers considering the measurement of effects and quality improvement in predictive maintenance and equipment management! 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, which is always a concern 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 to 70 points, rather than aiming for a perfect score of 100 from the beginning, and to gradually improve the system towards the desired state. This document introduces some of the essence of that approach.

  • Business Intelligence and Data Analysis
  • Workflow System
  • Other operation management software

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Reliability life prediction using Weibull analysis

Reliability life prediction using Weibull analysis

Free seminar ongoing! A clear 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/

  • Other electronic parts
  • Other Auto Parts

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