Client: A US-based multinational company in industrial manufacturing.
Problem: The client is one of the largest suppliers of industrial and environmental machinery to multiple other industries. One of their major products are pumps that are utilized in power, oil, gas, chemical and other industries. They require a way to help their customers manage the performance of their pumps. We can think of this issue having three parts:
- Transforming the nature of maintenance at the client’s customer’s factories, moving from a reactive approach of maintenance to a proactive approach.
- Increasing the visibility of real-time processes and therefore allowing active monitoring and predictive monitoring.
- Creating analytical systems that utilize past trends and historical events to predict maintenance requirements before they become an issue.
VT’s Solution: We combined our IoT (Internet of Things) solution and implemented it with analytical systems. In doing so, we set up and deployed the cloud services to form the backbone of the project. Installed sensors to monitor the pumps, and built analytical models and systems personalized for the maintenance prediction of the client’s pumps. Integrated the solution with the OSI PI system.
We utilized Enhanced Condition Data Point Monitoring (eCDPM) which combines 24/7 equipment monitoring (via sensors) with traditional route based condition data point monitoring. Full spectrum vibration analysis reports provided maintenance and reliability teams with improvement recommendations that increase mean time between failure (MTBF) & process efficiency while reducing total cost of ownership.
This helps give a clear understanding of your equipment’s remaining life, most likely failure modes and recommended actions so you can respond to adverse equipment conditions before they impact your organization.
- Achieved client’s business requirements by introducing technologies that monitor their assets and predict maintenance before major issues arise.
- Built an end-to-end implementation to monitor the processes as per client’s needs, deploying cloud connected IoT sensors for assets, building the cloud framework to support it gaining real-time visibility for the assets, and created analytical models to provide predictive maintenance capabilities.