Кейс2025 ж. 15 қаңтар
Cutting Unplanned Downtime from Bearing Failures: A Manufacturing Plant Case Study
A plant was losing up to 15 pieces of equipment a year to sudden bearing failures. Ultrasonic routes built on SDT340 found the defects weeks before failure — a KEG TRK case study in Kazakhstan.
SDT Ultrasound SolutionsӨндірісSDT340 - Продвинутый ультразвуковой детекторUAS3 - Программное обеспечение для анализа данных
Мақала орыс тілінде
Мақаланың толық мәтіні қазіргі уақытта орыс тілінде жарияланған. Аударма дайындалуда — толық мәтін үшін орыс нұсқасына өтіңіз.
Орыс тілінде оқуClient
A large machine-building plant in Kazakhstan that manufactures components for the oil & gas industry.
The problem
- Up to 15 unplanned shutdowns a year due to bearing failures
- High emergency repair costs
- No predictive maintenance program in place
The solution
A comprehensive ultrasonic monitoring program built on SDT340 was deployed:
Equipment
- 3 sets of SDT340 for different shops
- UAS3 software for data management
- Training for a team of 5 specialists
Implementation
- Built an equipment database (500+ measurement points)
- Trained staff in ultrasonic testing methodology
- Launched a regular monitoring program (monthly)
- Configured alarm levels and trending
Results
| Metric | Before | After | Improvement |
|---|---|---|---|
| Unplanned shutdowns | 15/year | 3/year | 80% |
| Maintenance cost | 100% | 65% | 35% |
| Repair time | 100 hours | 25 hours | 75% |
| ROI | — | 6 months | — |
Key findings
Early defect detection
- A turbine bearing defect was detected 3 months before failure
- A lubrication problem was found on 20% of pumps
- Compressed air leaks were located (savings of $15,000/year)
Best-practice rollout
- Standardized the bearing lubrication procedure
- Implemented alarm management
- Built a reference-value knowledge base
Next steps
- Expand the program to electrical equipment
- Deploy LUBExpert to automate lubrication
- Consider stationary Vigilant monitoring for critical assets
Client testimonial
"SDT340 let us move from reactive to predictive maintenance. Payback was under 6 months." — Chief mechanical engineer, the plant