Case Study :Advance Data Analytics
Predictive Asset Maintenance
Client was facing due to the high production losses due to the high number of issues & stoppages in the machine. Also, to remain competitive, it needed to improve its manufacturing facilities to reduce cost, increase capacity and innovation to remain competitive. Primarily they required a process for proactive monitoring to address the business needs.
2 min Read | Metal Manufacturing
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Challenge
Plant was losing on the production opportunities and the market share to strong competitors and suffering from growth in primary channels. The objective of this project was to increase the throughput by improving the OEE. OEE was at 65% at the starting of the project wherein the performance was the major concern due to stoppages.
Solution
Advance Data Analytics
Praxis Value proposed to develop an optimized algorithm by identifying the critical factors contributing to the situation. Wherein two key equipment’s were in the scope.
- Predict/ detect equipment abuse events (classification model) based on historic data abnormalities.
- Regression based prediction of asset performance with respect to the product grades.
- Conducting Design of Experiments to identify the best optimization algorithm.
Prioritise Key Initiatives
Predictive intelligence by creating algorithm for anomaly detection by understanding core areas 25 Critical factors & 39 other factors. Praxis Value identified 12 initiatives and prioritized them according to improvements to plant capacity and overall equipment effectiveness. These critical initiatives were directly handhold by Praxis Value team in all the phases of the project.
Process Simulation
Insights into operational intelligence through implementation of repair time estimation mechanisms and failure prediction for the equipment (MTBF & MTTR). In parallel to the development of the algorithm new actionable insights for improved business operations to evaluate the effectiveness of the processes and refine them, and develop entirely new methods, it enabled the plant process analysis that gave the information and insight to implement with confidence.
Outcome
With Praxis Value support, plant implemented the recommended initiatives, Production target were achieved and for some grades it went beyond. Lean implementation helped lower operating costs by replacing planned maintenance and reactive maintenance with predictive maintenance. (Points identified by Survival Analysis & Regression based remaining useful life prediction of asset components). Further an algorithm for a new product developed on the similar equipment which saved company from further Capex.
The company also worked with Praxis Value to put knowledge transfer programs in place so that the improvements would spread to additional plants in the system. Once the business transformation program is complete clients expects to save millions per year in terms manufacturing efficiency and headcount reduction.
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Cost Reduction
Cost Reduction and increasing savings without impairing any business operations or productivity.
Business Transformation
Building automation, raising productivity, cutting costs and accelerating growth—enabling more efficient production.
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