Product improvement, optimization of operating conditions, predictive maintenance system.
Utilizing simulation, statistical analysis, and machine learning techniques, we achieve product improvement, operational condition optimization, and predictive maintenance from field data of equipment!
We combine simulation technology and reliability evaluation with insights into equipment maintenance to support the construction of systems related to data collection and visualization, analysis, product improvement, optimization of operating conditions, and predictive maintenance. The main target equipment includes: - Various plants - Semiconductor manufacturing equipment - Air conditioning systems In this study, we support the construction of systems by using different tools and systems according to the customer's requests and objectives, such as: - 1D simulation software (1D CAE) - 3D simulation software (3D CAE) - Reliability and safety evaluation software - Statistical analysis software - Machine learning/AI software - IoT information collection infrastructure - Equipment maintenance management systems - Tablet systems Additionally, in conducting this study, we recommend starting small by narrowing down the target equipment.
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basic information
The steps for building the system are as follows: 1. Consulting 2. Requirements definition for the system 3. System construction 4. Start of operation / Tool implementation These four steps are carried out, and system construction or tool implementation is recommended as needed. In the consulting phase, depending on the objectives, we examine and construct models to build the online simulation system, compare them with actual machines or experimental values, and perform fitting to reproduce the equipment on the computer. For an overview of the system, please download the catalog or contact us.
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Applications/Examples of results
- Various plants - Semiconductor manufacturing equipment - Air conditioning systems
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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 a system 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 of digital transformation (DX), there is a growing movement to digitize and automate manufacturing processes and research and development sites in factories to improve operational efficiency. In line with this trend, our company provides a solution aimed at enhancing efficiency in research and development environments, which is the Laboratory Information Management System (LIMS). This software includes features such as workflow management, data tracking, data management, data analysis, and integration of electronic lab notebooks.