Predictive Maintenance Product List and Ranking from 7 Manufacturers, Suppliers and Companies

Last Updated： Aggregation Period:Jul 09, 2025～Aug 05, 2025
This ranking is based on the number of page views on our site.

Predictive Maintenance Manufacturer, Suppliers and Company Rankings

Last Updated： Aggregation Period:Jul 09, 2025～Aug 05, 2025
This ranking is based on the number of page views on our site.

  1. 中外炉工業 Osaka//others
  2. シー・エス・シー Tokyo//Building materials, supplies and fixtures manufacturers 本社、大阪支店、福岡出張所
  3. CMエンジニアリング Tokyo//Information and Communications
  4. inQs Tokyo//Electricity, Gas and Water Industry 本社
  5. エル・エス・アイジャパン Tokyo//Information and Communications
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Predictive Maintenance Product ranking

Last Updated： Aggregation Period:Jul 09, 2025～Aug 05, 2025
This ranking is based on the number of page views on our site.

  1. IoT for heat treatment equipment! We propose predictive maintenance through data collection and remote monitoring. 中外炉工業
  2. For predictive maintenance of bearings! 'SKF Quick Collect Sensor' シー・エス・シー 本社、大阪支店、福岡出張所
  3. IoT Textbook Series: Utilization of IoT in Predictive Maintenance of Equipment CMエンジニアリング
  4. Remote predictive maintenance using retrofitted vibration sensors: "Add-on Vibration Sensing" inQs 本社
  5. [IoT Textbook Series] Utilization of IoT in Predictive Maintenance of Equipment CMエンジニアリング

Predictive Maintenance Product List

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For predictive maintenance of bearings! 'SKF Quick Collect Sensor'

For predictive maintenance of bearings! 'SKF Quick Collect Sensor'

Supports IoT integration for machinery! Portable bearing condition monitoring sensor. *Rental service is also available.

The "SKF Quick Collect Sensor" is a device that measures the vibration velocity, acceleration envelope, and temperature of bearings. □ It is a portable sensor that allows administrators to share information by connecting with apps on tablets, smartphones, or smartwatches. □ By monitoring bearings, it enables the creation of maintenance plans for bearings, including preventive diagnostics, eliminating sudden downtime. □ The condition of the bearings is indicated in three colors: green, yellow, and red, making it easy for everyone to understand the status of the bearings. □ The communication method is Bluetooth, and no internet connection is required. (An internet connection is necessary when transferring data from smartphones, tablets, or smartwatches.) 【Features】 ■ Quick startup ■ Easy for everyone to use ■ Pre-identification of issues in rotating machinery ■ Ability to directly consult experts as needed ■ Functionality expansion through the app to develop and complement existing maintenance programs *For more details, please refer to the PDF document or feel free to contact us.

  • Vibration and Sound Level Meter

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IoT for heat treatment equipment! We propose predictive maintenance through data collection and remote monitoring.

IoT for heat treatment equipment! We propose predictive maintenance through data collection and remote monitoring.

"CRism" is an IoT system for heat treatment equipment. It can set reference values and issue alerts for all data being collected.

"CRism" allows customers to set thresholds for all collected data, and notifications can be configured to be sent through general communication apps when these thresholds are exceeded. It visualizes various numerical data such as time-series data and batch data. 【Do you have any of these concerns with your heat treatment equipment?】 - I want to manage the timing of parts replacement to prevent troubles in advance. - I don't know the cause of the furnace shutdown. - I want to check the equipment status from anywhere. 【Features】 ■ Convenient "threshold setting function" ■ Capable of "diverse data analysis" ■ Visualizes various numerical data *For more details, please refer to the PDF materials or feel free to contact us.

  • maintenance
  • IoT
  • Analysis and prediction system

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IoT Textbook Series: Utilization of IoT in Predictive Maintenance of Equipment

IoT Textbook Series: Utilization of IoT in Predictive Maintenance of Equipment

"What is predictive maintenance?" and "Necessary sensors" and "Sensor connection to Tele-Sentient" are included!

Understanding the operational status of factory equipment and detecting signs of potential failures in advance is crucial for addressing stable operations and losses due to downtime. This falls under the field known as predictive maintenance. This document introduces the types of sensors needed when utilizing IoT for predictive maintenance. We encourage you to read it. 【Contents】 ■ What is predictive maintenance? ■ Necessary sensors ■ Sensor connection to Tele-Sentient *Please download the PDF document from the special site, not from "Ipros Monozukuri": https://premium.ipros.jp/cmengineering/product/detail/2000607476/ Ipros Urban Development https://kensetsu.ipros.jp/product/detail/2000607476/

  • IoT

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Remote predictive maintenance using retrofitted vibration sensors: "Add-on Vibration Sensing"

Remote predictive maintenance using retrofitted vibration sensors: "Add-on Vibration Sensing"

Explosion-proof Area Zone 1 compatible products! No need for power or network construction for installation, ready to use immediately.

"Add-on Vibration Sensing" is a product designed for remote predictive maintenance using an aftermarket vibration sensor that can accommodate all volatile gases. It is compatible with IIC T6, allowing for the detection of hydrogen, acetylene, and more. It is suitable for older equipment where sensor installation has not progressed, as well as auxiliary equipment in explosion-proof areas. Installation requires no power or network construction, allowing for immediate use. Remote fault monitoring of equipment can be performed from a PC in the management room. 【Features】 ■ Products compatible with explosion-proof area Zone 1 ■ Capable of detecting all volatile gases ■ Compatible with IIC T6, allowing for detection of hydrogen, acetylene, etc. ■ Well-suited for older equipment where sensor installation has not progressed and auxiliary equipment in explosion-proof areas ■ Immediate use with installation requiring no power or network construction *For more details, please refer to the PDF document or feel free to contact us.

  • Security cameras and surveillance systems
  • Monitoring and Control Equipment

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[IoT Textbook Series] Utilization of IoT in Predictive Maintenance of Equipment

[IoT Textbook Series] Utilization of IoT in Predictive Maintenance of Equipment

"What is predictive maintenance?" and "Necessary sensors" and "Sensor connection to Tele-Sentient" are included!

Understanding the operational status of factory equipment and detecting signs of potential failures in advance is crucial for addressing stable operations and losses due to downtime. This falls under the field known as predictive maintenance. This document introduces the types of sensors that are necessary when utilizing IoT for predictive maintenance. We encourage you to read it. [Contents] ■ What is predictive maintenance? ■ Required sensors ■ Sensor connection to Tele-Sentient *For more details, please refer to the PDF document or feel free to contact us.

  • IoT

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Predictive maintenance with "vibration detection sensor system" *Monitor recruitment

Predictive maintenance with "vibration detection sensor system" *Monitor recruitment

We are looking for companies that can help us monitor the development of our "Vibration Detection Sensor System" for commercialization!

The "vibration detection sensor" currently under development detects vibrations using built-in sensors and wirelessly transmits data indicating changes in equipment status to a higher level for acquisition. At LSI Japan Co., Ltd., we aim to simplify the process of understanding the appropriate maintenance timing for equipment by visualizing changes in vibration, and we are looking for companies that can participate as monitors for the commercialization of our sensor system. If you are interested in systems that monitor equipment status using sensors and predictive maintenance, please feel free to contact us. Customers who participate as monitors will receive graphs of the acquired data on clogging trends. 【Patent】 We have obtained a patent for a method of detecting clogging based on the magnitude of vibrations that are proportional to the diversion. Patent No. 5821067 "Clogging Estimation Method, Filter Monitoring System, and Vibration Information Transmission" *For more details, please contact us.

  • others

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Predictive maintenance of rotating equipment such as motors and pumps.

Predictive maintenance of rotating equipment such as motors and pumps.

A deterioration detection solution for rotating equipment that enables early warning detection of low-speed rotating equipment, which could not be captured by vibration sensors.

"MMCloud for AEMonitorPack" is a package service that includes a dedicated AE sensor and IoT platform, available for a fixed monthly fee that includes communication costs. The dedicated AE sensor automatically detects signs of failure and immediately notifies with an alert. This helps prevent unexpected troubles on the manufacturing line and reduces downtime. It is suitable for predictive maintenance of rotating equipment such as motors, pumps, and conveyors. 【Features】 ■ Everything you need is included in one package ■ Available for a fixed monthly fee that includes communication costs ■ Maintenance is conducted without relying on the experience or intuition of workers ■ Enables predictive detection of signs of failure in low-speed rotating equipment that vibration sensors cannot capture ■ Prevents unexpected line stoppages and enables planned maintenance *For more details, please refer to the PDF document or feel free to contact us.

  • IoT
  • pump

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NVIDIA Certified Course: Predictive Maintenance Using AI [Online Training]

NVIDIA Certified Course: Predictive Maintenance Using AI [Online Training]

You will learn methods to identify anomalies and faults from time series data based on AI, as well as how to estimate the remaining useful life of the relevant parts.

■Goals - Using time series data, it is possible to predict outcomes with an XGBoost-based machine learning classification model. - By using an LSTM-based model, it is possible to predict equipment failures. - Utilizing anomaly detection through time series autoencoders, it is possible to predict failures when limited failure case data is available. ■Target Audience System engineers and developers who develop and provide predictive maintenance systems in the industrial sector. ■Prerequisites - Completion of the "Introduction to Python from Scratch - Focusing on Data Analysis" course or equivalent knowledge. - Completion of the "NVIDIA Deep Learning Institute (DLI) Certified Course Fundamentals of Deep Learning" course or equivalent knowledge.

  • IoT

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