From veteran intuition to scientific evidence through AI. Reduce maintenance costs! AI scientifically assesses the risk of 146 types of damage and guides suitable maintenance plans.
【Adopted as a Leading Project of Tama Innovation】 Are you struggling with aging equipment and a shortage of skilled technicians? The "AI-RBM" provided by Best Materia Co., Ltd. quantifies risks based on the "Probability of Failure (PoF)" and "Consequences of Failure (CoF)" of equipment, scientifically determining maintenance priorities as a next-generation maintenance solution. We are moving away from traditional maintenance methods that relied on the "intuition and experience" of veterans. AI estimates the optimal damage mechanisms from 147 types, allowing us to concentrate limited maintenance budgets and personnel on "truly high-risk areas," achieving both stable plant operations and significant reductions in maintenance costs. ■ Do you have these concerns? - Equipment is aging, and there is anxiety about the risk of line stoppage due to sudden failures. - Veteran maintenance technicians are nearing retirement, and knowledge transfer is not keeping up. - We continue to conduct uniform periodic inspections (TBM), but excessive maintenance costs are incurred. - There are too many inspection points, and we want objective grounds for prioritizing where to start. - We want to promote smart safety and maintenance DX, but we don't know where to begin.
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■ Features (clearly presented in bullet points) 1. Comprehensive screening by AI Consolidating expertise in materials engineering. AI instantly estimates the most suitable damage mechanisms from over 146 types of metal material damage mechanisms, such as corrosion, fatigue, and creep, for the target equipment, preventing oversight. 2. Elimination of subjectivity and high precision Transforming the tacit knowledge of experts into AI. Providing a consistent, scientifically grounded high-precision risk assessment that is not influenced by the experience of the personnel evaluating it. 3. Optimization of maintenance costs (targeted maintenance) Evaluating risks based on global standards (such as API 581). By providing more attention to high-risk areas and extending inspection intervals for low-risk areas, we reduce unnecessary inspection costs through a targeted approach. 4. Continuous improvement of accuracy through user data By training AI with your actual operational data and past history, it becomes increasingly tailored to your equipment, allowing for continuous improvement in accuracy as it is used. uni-planner *Selected project of the Tama Innovation Ecosystem Promotion Project
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Major automobile manufacturers Major chemical manufacturers Numerous facilities such as oil refining, power generation, and waste treatment plants
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We engage in the sales and implementation consulting of the material information management system GRANTA MI from Granta Design in the UK, as well as the development and operation of the optimal material selection site MatGuide for selecting materials such as steel. Additionally, we contribute to the creation of a safe and secure society by providing appropriate knowledge and technology related to material selection and Risk-Based Maintenance (RBM).
