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 support the construction of systems related to data collection and visualization, analysis, product improvement, optimization of operating conditions, and predictive maintenance by combining simulation technology, reliability evaluation, and equipment maintenance expertise. The main target equipment includes: - Various plants - Semiconductor manufacturing equipment - Air conditioning systems In this study, we will support the construction of systems by utilizing 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. Requirement definition of the system 3. System construction 4. Start of operation / Tool implementation These four steps are carried out, and we recommend system construction or tool implementation as needed. In the consulting phase, we examine and build models to create an online simulation system according to the objectives, compare it with actual machines or experimental values, and perform fitting to reproduce the equipment on a 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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Company information
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 one 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 towards digital transformation (DX), there is a growing movement to digitize and automate manufacturing processes and research and development sites in factories to enhance operational efficiency. In line with this trend, our company provides a solution aimed at improving efficiency in research and development environments, known as the Laboratory Information Management System (LIMS), which includes features such as workflow management, data tracking, data management, data analysis, and integration of electronic lab notebooks.
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