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Data collection and analysis system Product List

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[Example] Compressor Quality and Performance Trial Operation Bench Data Collection and Analysis System

[Example] Compressor Quality and Performance Trial Operation Bench Data Collection and Analysis System

Introduction of a case study on the delivery of a compressor quality and performance trial operation bench data collection and analysis system.

We would like to introduce a case study of a system that collects and analyzes various data such as vibration, pressure, and temperature in real-time, which is essential for maintaining quality during the manufacturing of large compressors used in shale oil, petrochemicals, and energy-related development. In conventional systems, measurement data such as temperature, pressure, and flow rate were collected and analyzed separately from vibration-related data. Our new system allows for efficient processing of this data, significantly improving work efficiency. 【Case Overview】 ■Challenges - Measurement data and vibration-related data were collected and analyzed using separate systems. ■Results - The new system enables efficient processing, leading to a significant improvement in work efficiency. *For more details, please refer to the PDF document or feel free to contact us.

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Achievement Data Collection and Analysis System [DBSTAR light]

Achievement Data Collection and Analysis System [DBSTAR light]

Collect and analyze data on production equipment and processes, and build a quality control and analysis system.

- Overview - The real-time quality data database system for Windows is designed to support the collection and analysis of operational data, utilizing our original proprietary file format in the database. The X-axis of the graph can display product dimensions, allowing for easy identification of any abnormal parts of the product at a glance. - Application - DBSTAR light is a package designed for small-scale operations that runs on Windows OS, supporting the analysis of production conditions in manufacturing sites, early detection of manufacturing anomalies, and improvement of yield.

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Achievement Data Collection and Analysis System 【HIGHWAYSTAR】

Achievement Data Collection and Analysis System 【HIGHWAYSTAR】

Collect and analyze data on production equipment and processes, and establish a quality control and analysis system.

- Overview - This is a system monitoring package that monitors resources such as hardware failures and memory usage, as well as resources under the management of our proprietary middleware, MIDDLESTAR, including processes, tables, and files (including exclusive consistency). It also detects abnormal trends based on thresholds, and in the event of anomaly detection, it can send emails to mobile phones and other devices through integration with an email server. Additionally, the GUI (Graphical User Interface) allows users to easily configure the monitoring environment. - Purpose - It enables remote monitoring of hardware, resources, and MIDDLESTAR-managed processes in a system composed of Ethernet. It is also equipped with an abnormal trend detection function, contributing to improved system uptime.

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Achievement Data Collection and Analysis System【DBSTAR】

Achievement Data Collection and Analysis System【DBSTAR】

Collect and analyze data on production equipment and processes, and establish a quality control and analysis system.

- Overview - This is a real-time quality database system for operational data collection and analysis support. It features collection capabilities and graphic display functions, allowing for program-less system generation with only environmental definitions. It can also accumulate 10 years of data with 16,000 tags. Additionally, it easily facilitates integration with user applications for calculations and statistical processing. Furthermore, by displaying the X-axis of graphs with product lengths, it allows for quick identification of abnormal areas in products at a glance. - Applications - DBSTAR is a package designed for medium to large-scale operations that runs on a stable Linux OS, supporting the analysis of production conditions in manufacturing sites, early detection of manufacturing anomalies, and improvement of yield rates.

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