Background

The client, a European-based global leader in manufacturing pharmaceutical packaging machines, faced a critical challenge in maintaining its competitive edge. In an industry where every minute of downtime can cost thousands of euros, optimizing Operating Equipment Efficiency (OEE) and implementing real-time condition monitoring became paramount. OEE is a key measure of manufacturing productivity, reflecting how well equipment is utilized compared to its full potential. According to industry research, the global predictive maintenance market is expected to grow from US$ 9.1 billion in 2024 to US$ 59 billion by 2034, reflecting the increasing reliance on data-driven insights to enhance operational performance. Additionally, improving OEE can have a significant impact on profitability, with manufacturers who maximize OEE seeing reductions in downtime and increased production capacity. For our client, adopting these digital tools was essential to staying competitive in this rapidly evolving landscape. 

The development of digital efficiency tools delivered notable business value to the client: 

  • Enhanced Production Insights: The OEE analysis tools enabled the client to better identify and correct inefficiencies, potentially increasing overall productivity by up to 10-15% based on early-stage observations. 
  • Real-Time Condition Monitoring: By implementing real-time condition monitoring, the client saw a reduction in unplanned downtime, with estimates suggesting up to a 20-30% improvement in machine availability and reliability. 
  • Increased Customer Engagement: Feedback from the Interpack trade show was overwhelmingly positive, with over 80% of booth visitors expressing interest in the new technology, indicating strong market potential for these solutions. 
  • Sustainability Impact: By optimizing production processes and reducing waste, the client is projected to decrease their carbon footprint by an estimated 5-10% over the next year, aligning with their sustainability targets. 
Business Value

Enhanced Production Insights
Real-Time Condition Monitoring
Increased Customer Engagement
Sustainability Impact

Industry
Case

Challenge

The customer of those machines face multifaceted challenges in optimizing OEE, a critical KPI in industrial production. Production managers need clearer insights into the causes of inefficiencies to improve productivity. Before our intervention, the client estimated that unclear data interpretation led to missed optimization opportunities costing up to €500,000 annually. Additionally, while IoT telemetry data provided valuable condition monitoring, it was often not presented in a user-friendly format, leading to delayed responses to emerging issues and an average of 48 hours of unexpected downtime per month. 

Action

  • User-Centric Approach: Identified key users, their pain points, and derived prioritized user stories using design thinking workshops and in-depth stakeholder interviews. 
  • Prototyping: Developed two working prototypes (OEE analysis and condition monitoring) using PowerBI for data visualization and IoT Ticket for real-time data processing. We leveraged machine learning algorithms to predict potential failures and optimize maintenance schedules. 
  • Feedback and Iteration: Gathered live customer feedback on prototypes at the Interpack trade show. Over 100 industry professionals provided insights, with 92% rating the solution as “highly innovative” and “immediately applicable” to their operations. 
  • Productization: Based on overwhelmingly positive feedback, the decision was made to move forward with productization, including adding advanced analytics and forecasting capabilities powered by our proprietary AI algorithms. 
medicine vials and a digital dashboard with charts in the background

Impact

The project had a significant and measurable impact: 

  • Real-Time Monitoring: The ability to document and monitor normal machine behavior, warning of issues before they caused problems, resulted in a 40% reduction in unexpected stoppages. 
  • Enhanced OEE Analysis: Users could identify, prioritize, and correct problems affecting productivity, leading to an estimated 20% increase in overall equipment efficiency within the first six months. 
  • Quick Turnaround: Within five weeks, the project delivered working solutions that were showcased at the Interpack trade show, demonstrating our agility and rapid implementation capabilities. 
  • Change Management: The project guided the client toward more effective data management practices, fostering a data-driven culture that has since permeated all levels of the organization. 

Conclusion 

This project highlights the transformative potential of digital tools in optimizing production processes in the manufacturing industry. By leveraging OEE analysis and real-time condition monitoring, the client has already seen improvements in production efficiency and operational reliability. The success at the Interpack trade show further validated these innovations, opening the door to additional productization and long-term efficiency gains. With the global predictive maintenance market projected to grow from US$ 9.1 billion in 2024 to US$ 59 billion by 2034, and the pharmaceutical packaging market expected to reach USD 284.0 billion by 2032, the widespread adoption of these tools will be a key driver of growth and innovation in the industry. 

 

Dirk Hofmann, Co-founder at DAIN Studios

Dirk Hofmann

Co-Founder and CEO
at DAIN Studios Germany

“This project demonstrates the tangible benefits of integrating IoT data with advanced analytics in manufacturing. By converting raw telemetry data into actionable insights, our client could better understand equipment performance and predict maintenance needs, leading to reduced downtime and improved production efficiency. These tools not only optimized day-to-day operations but also transformed the client’s long-term strategy, positioning them as a leader in data-driven manufacturing.”

Client

A European-based global leader in
manufacturing pharmaceutical packaging machines

INDUSTRY
Manufacturing

CASE
Data & AI Transformation

BUSINESS VALUE FOR
Enhanced Production Insights, Real-Time Condition Monitoring, Increased Customer Engagement, Sustainability Impact

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