Representative End User Clients
Representative Automation Clients
Representative Software Clients
Client’s Challenge: A global beverage manufacturer having a large bottling facility in the US West Coast, was facing unplanned downtime in its Filling Lines critical assets. The plant has 3 beverage production lines (11 assets) and 1 utility section (3 assets). The manufacturer wanted to transition from preventive to predictive maintenance with 24x7 monitoring of its critical assets as part of its enterprise-wide initiative of a digital factory. L&T Technology Services (LTTS) was chosen to provide a scalable, fit-for-purpose and an end-to-end predictive maintenance solution.
The Solution: LTTS proposed its proprietary condition-based Predictive Maintenance solution to address these problems by monitoring critical asset component health parameters like current and temperature, combined with vibration in real time to generate useful insights and predictions. LTTS followed a systematic and approach for solution implementation, which is detailed below:
Site and Asset Assessment: Identification of critical components of each asset for additional sensor mounting and conducted detailed investigation of line layout, asset assembly, operational and maintenance incident history and its impact on the facility.
Sensors and Edge Gateways: Based on the identified critical asset components, 3 sensor types were installed – Vibration (118 nos. Tri-axial accelerometers), Temperature (41 nos.) and Current (45 nos.). These sensors covered 14 complex assets and were integrated through LTTS’ custom-designed and custom-built 34 Edge Gateways, using STAR topology.
Data Handling and ML Modelling: The analytical model deployed for a specific asset, processes the condition data gathered from sensors to compute asset health and estimated time to failure KPIs of the asset. Events generated for the fault incidents are flagged to the maintenance team for performing the analysis and maintenance on the components to avoid unplanned shutdown.
Key Achievement: The implemented solution system is running at the beverage plant at USA for more than 3 years with the following outcome:
Improved availability and OEE – Helped the plant team avoid 8 potential failure incidents, resulting in improved OEE and production with substantially lower downtime.
- Reduced operations and maintenance costs – Reduced production loss of approximately $314,204 by avoiding unplanned shutdown and minimized MTBF in the first 8 months. Reduced maintenance costs by improving MTTR – decreased holding time and CapEx of spares for impacted asset components.
Ability to deliver accurate failure prediction (~ 90 percent accurate) in near real-time basis, the solution is continuing to help the customer avoid unplanned downtime and improve plant efficiency.