How a Traditional Industrial Plant Turned into a Smart Factory
Denmark
Challenge
For decades, a large industrial manufacturing plant operated with aging machinery, paper-based processes and fragmented systems. Production managers relied on intuition rather than data, and every unplanned stop meant long investigations and guesswork. The plant had more than 70 documented pain points, from manual data entry to inconsistent downtime codes.
Data existed in many places but was not integrated or trusted. Legacy PLCs, SCADA and ERP systems operated in silos without meaningful connectivity. Operators had limited visibility beyond local HMI screens, and maintenance was purely reactive. The leadership team knew that competitors were moving toward connected, data-driven operations, but internal attempts to modernize had stalled.
Solution
Radner's team designed and executed a comprehensive digital transformation roadmap focused on industrial automation and advanced analytics.
The transformation included:
- Detailed discovery phase with interviews across all shifts and comprehensive system audits
- Strategy workshops to define objectives: increase OEE, reduce unplanned downtime, improve schedule adherence
- Design of layered architecture connecting existing PLCs via industrial gateways
- Implementation of manufacturing data platform for high-frequency signal collection and contextualization
- Deployment of industrial IoT gateways with standardized communication protocols
- Development of standardized equipment model and harmonized downtime taxonomy
- Installation of visual management tools including live dashboards and performance screens
- Implementation of machine learning models for predictive maintenance and early warning systems
- Integration of production data with ERP scheduling module for realistic capacity planning
- Comprehensive change management program with operator training and cultural transformation
Results
The smart factory transformation delivered measurable improvements within 18 months:
- Overall Equipment Effectiveness on pilot lines increased by more than 15 percentage points
- Unplanned downtime dropped by nearly 30% through better root cause analysis and predictive maintenance
- Schedule adherence improved significantly, reducing last-minute rescheduling
- Overtime costs decreased due to better planning and reliability
- Scrap rates reduced through early detection of process drifts
- Maintenance strategy shifted from reactive to predictive, reducing emergency interventions
- Spare parts planning improved through condition-based work orders
- Cross-functional collaboration enhanced with shared data-based language
- Plant reputation within corporate group improved, positioning it as a model site
- Foundation established for future innovations including energy optimization and digital twins
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