Initial Situation:
Competitive pressure has increased significantly in recent years. Raw material prices are rising, energy costs have skyrocketed, personnel costs are not getting cheaper either, and at the same time regulatory requirements are becoming increasingly complex. The goal was to uncover and realise potential for increasing efficiency and effectiveness.
The problem: there was a lack of transparency regarding actual resource usage and losses incurred, while at the same time there was a high manual documentation burden. The effectiveness and efficiency of production could not be compared between sites, as neither losses were systematically recorded nor uniform KPIs were used. In addition, data was not collected centrally and comprehensively, making root cause analysis extremely time-consuming or impossible altogether.
Objectives:
- Create transparency about resource usage, production processes and losses
- Introduce an energy management system
- Introduce a uniform OEE standard across all sites for systematic analysis of the biggest losses in production, including automatic data collection for downtimes, production output and scrap
- Introduce continuous improvement measures based on insights into the biggest losses
- Build a shared data foundation with all process-relevant data for efficient root cause analyses
- Implement shopfloor dashboards and digital worker guidance to implement improvement measures on the shopfloor
Results:
OEE increase of 14 percentage points at pilot site
- Systematic reduction of unnecessary downtimes
- Increase in average production output through ideal, reproducible setting parameters
Features used: OEE tracking, automatic downtime recording, product-based output recording, dashboarding & reporting, digital setting data sheets (worker assistance system) for feeding back optimal process parameters
Electricity cost reduction of over €60,000 per year
- Optimisation of peak loads
Features used: Hosted Grafana for flexible real-time monitoring via dashboards and alerts, peak load management through combination of production, energy and power data
Reduction of scrap by eliminating recurring production errors
- Detecting and eliminating faulty process control through digital worker assistance system
Features used: Process analysis tools, search function for order and product information, digital setting data sheets combined with digital worker assistance system
Further improvements not directly measurable:
- Meetings significantly more targeted and fact-based
- Fewer gut-feeling discussions
- Higher motivation among production staff through transparency and reduced burden of data collection
Text taken from the original – ENLYZE