The client was looking for an analytics service provider for the Supply Chain Services Metrics team responsible for improving all key operational KPIs.
The Before state
- A plant producing ~3000 lbs chips an hour has lower Operational Equipment Efficiency (OEE) due to the impact of the packaging segment stops contributing to fryer downtime/throughput reduction.
- Large Equipment in the manufacturing line was operating well below capacity and had a high production waste.
- Packaging Efficiency: Frequent Stops in one packaging line will increase other packaging lines’ load and impact overall packaging efficiency.
- Operator Effectiveness: Every Packaging Stop needs attention from the Operator, preventing them from performing other scheduled operational tasks.
- Scheduling Challenges: Adjustment of Daily production planning to account for lines experiencing frequent faults.
The LtentView Solution
- An early warning system to predict stops in advance (30, 60 & 180 minutes) in packaging & processing was developed.
- We developed a Diagnostic Tool to spot packaging issues.
- Our On-site coordinator visited the pilot plants to understand the operational process, which helped us derive features for modeling.
- Packaging stops data was used for attributing Processing Downtime and Throughput events.
- The time-series data format was converted into a cross-sectional form for modeling purposes.
- Statistical models were applied to predict and target Processing events.
- Operational thresholds were found for key factors driving the event.
- Differentiating aspect of the project
- Identifying key factors to predict downtime/throughput reduction on an hourly basis.
- Building a real-time visualization tool to monitor the key factors and take necessary mitigating actions.
The After state
- Incremental wastage reduction ~4500 lbs/month for POC plant
- Additional output was gained by predicting downtime (13000 lbs/month) for the POC plant.