Current Situation:
Competitive pressure has significantly increased in recent years. Raw material prices are rising, energy costs have skyrocketed, and our personnel costs are not getting cheaper, while regulatory requirements are becoming increasingly complex. The goal was to uncover and realize potential for increasing efficiency and effectiveness.
The problem: There was a lack of transparency regarding actual resource use and incurred losses, while simultaneously a high manual documentation effort existed. The effectiveness and efficiency of production could not be compared between locations, as neither losses were systematically recorded nor uniform metrics used. Additionally, data was not collected centrally and comprehensively, making root cause analysis extremely cumbersome or completely prevented.
Objectives:
Create transparency about resource use, manufacturing processes, and losses
Implement an energy management system
Introduce a unified OEE standard across all locations for systematic analysis of the largest losses in production, including automatic data collection for downtimes, production performance, and scrap
Implement continuous improvement measures based on insights about the largest losses
Establish a common database with all process-relevant data for efficient root cause analyses
Implement shop floor dashboards and digital worker guidance to implement improvement measures on the shop floor
Results:
OEE increase of 14 percentage points at the pilot location
Systematic reduction of unnecessary downtimes
Increase in average production performance through ideal, reproducible setting parameters
Features Used:
OEE tracking
Automatic downtime recording
Product-based performance recording
Dashboarding & Reporting
Digital setting data sheets (worker assistance system) for feedback of optimal process parameters
Reduction of electricity costs by over €60,000 per year
- Optimization of peak loads
Features Used:
- Hosted Grafana for flexible real-time monitoring through dashboards and alerts
- Peak load management through the combination of production, energy, and performance data
Reduction of scrap by addressing recurrent production errors
- Identifying and addressing faulty process management through digital worker assistance system
Features Used:
- Process analysis tools
- Search function for order and product information
- Digital setting data sheets in combination with digital worker assistance system
Other, not directly measurable improvements:
- Meetings significantly more focused and fact-based
- Fewer discussions based on gut feeling
- Higher motivation of production staff through transparency and relief in data collection
Text taken over from the original – ENLYZE
