Reproducing subjective judgments in complex equipment maintenance into structured data with reproducibility (for high-temperature processes / incineration, exhaust gas, and heat recovery equipment).
AI-FTA is a solution that supports the narrowing down of failure causes and the structuring of judgment in manufacturing and plant environments. It integrates on-site data such as work standards, failure reports, and inspection histories, transforming complex causal relationships into easily understandable structural information. It addresses challenges faced by equipment manufacturers, maintenance departments, and plant operators, such as "dependency on veterans" and "time-consuming cause identification," and supports the standardization of reproducible judgment processes.
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basic information
■ Features Integration of on-site data → Structured decision-making Utilization of past failure cases and causal relationships Acceleration of primary cause estimation Reduction of reliance on veterans and support for horizontal deployment Utilization of existing equipment and existing data (no modifications required) * Data linkage with OT / MES / CMMS, etc., is also possible ■ Expected Implementation Effects Improvements such as the following are anticipated: Reduction in time for narrowing down failure causes Elimination of individual dependency in abnormal response and sharing of know-how Standardization of maintenance criteria and horizontal deployment across sites Reduction of equipment downtime risk Assetization of trouble response history (Contributes to the optimization of maintenance for industrial and plant equipment) ■ Applicable Targets (Examples of Equipment) The following types of equipment can be addressed: High-temperature continuous processing equipment Incineration equipment (combustion, ash processing, exhaust gas systems) Heat recovery / boiler systems Exhaust, denitrification, and catalytic reaction towers Conveying and pre-treatment equipment Multi-system linked equipment (manufacturing and general plant) * Effective in equipment maintenance sites with complex causal relationships.
Price range
P6
Delivery Time
※2-6 months
Applications/Examples of results
■ Performance and Verification Examples Verification conducted in a domestic plant operating company (*Customer and facility names are confidential) Verification focused on continuous processing equipment operating for over 10 years Integration of failure reports, work standards, and inspection history Structuring of over 1,200 records Implementation of multiple system classification and cause candidate suggestion functions Confirmation of potential for horizontal deployment across locations *The verification examples are used as a "valid judgment structure model on-site." ■ Common Concerns (FAQ Style) Q: What is needed before implementation? A: You can start simply by organizing and providing your current maintenance and failure reports. Q: How much effort is required for implementation? A: It varies depending on the data preparation status of the target systems, but you can start with a Proof of Concept (PoC). Q: In what kind of environments is it effective? A: It is effective in equipment maintenance environments where the causal structure is complex and relies on veteran judgment.
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Company information
Our company is a specialty store focused on LED lighting and custom solutions. We can accommodate OEM products for LED lighting in small lots. Additionally, regarding plant cultivation, we offer proposals tailored to current needs, including mobile container farms, compact growth systems, and custom growth shelves. We also have lighting options that comply with JIS8006 for marine applications, in addition to standard lighting. Furthermore, we provide lighting fixtures that can be used in ultra-low temperature environments, as well as types with emergency light functions. For inquiries about LED lighting and plant cultivation, please feel free to consult with us.
