We will introduce examples of services that utilize accumulated data to provide high-precision anomaly detection and prediction!
Introducing the use cases of the AI-based predictive maintenance service "LUiNa." By "streamlining the maintenance of equipment across the country," it is possible to prevent equipment malfunctions and failures, as well as reduce labor hours. Additionally, through periodicity and change point detection algorithms, it can detect early signs of issues, enabling "early detection of signs before network equipment failures." [Use Cases] ■ Streamlining maintenance of equipment across the country ■ Early detection of signs before network equipment failures *For more details, please refer to the PDF document or feel free to contact us.
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【Case Details】 <Improving Maintenance Efficiency of Equipment Nationwide> ■Challenges ・Threshold monitoring detects even non-problematic equipment uniformly, leading to being overwhelmed by alerts. ・When issues are discovered through customer reports, the need for on-site responses increases labor costs and decreases customer satisfaction. ■Implementation Effects ・By detecting "not always," we can identify equipment in a silent failure state. ・By conducting planned maintenance, we can prevent equipment malfunctions and failures, reducing labor costs. ・Customer satisfaction also increases. *For more details, please refer to the PDF document or feel free to contact us.
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For more details, please refer to the PDF document or feel free to contact us.
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Our company has been engaged in IT system performance management for many years. With our extensive achievements and know-how cultivated during this time, we provide products and consultations that ensure a system that does not cause problems, or if issues do arise, they can be handled with peace of mind, thereby promoting efficient IT utilization for our customers. Please feel free to consult us if you have any requests.