Optimizing Maintenance Operations: Tailored Strategy with AI and ML for Peak Performance
Challenge
- The diaper machine’s main conveyor belt is a critical component that needs to be monitored for signs of failure. One of the key parameters that can be monitored is the conveyor belt’s vibration
- Our client needed solutions that can help them optimize their machines to ensure they are functioning optimally and producing high-quality products efficiently.
Our Solutions
- We developed a tailored maintenance strategy by integrating Artificial Intelligence (AI) and Machine Learning (ML) into their maintenance operations to meets their specific needs, ensuring that their machines are always running at peak performance levels
- Vibration sensors have been installed on the machine to collect data, which can be used to train an AI algorithm to identify patterns in the vibration data that indicate when the conveyor belt is beginning to wear out or is experiencing excessive stress.
- We analyzed historical data using AI to understand the machine’s vibration behavior and predict when a failure is likely to occur.
- Additionally, we have optimized maintenance schedules by analyzing data on the conveyor belts wear and tear, allowing ML algorithms to predict when it is time to replace the conveyor belt or perform other maintenance tasks.
Results
- Our ML model helped customer to predict when it is time to replace the conveyor belt or perform other maintenance tasks, thus allowing client to optimize their maintenance schedules and reduce the risk of unexpected downtime due to equipment failure.
- By minimizing unexpected downtime due to equipment failure and optimizing maintenance schedules, it helped our client to increase the productivity of their machines and reduce the overall cost of maintenance tasks.
Client
Disposal Hygiene Machine Manufacturer in US
Industry
Machinery Manufacturer