The Data Visibility Challenge in Legacy Manufacturing

In a recent study by the Manufacturing Institute, it was found that over 70% of small to medium-sized enterprises delay modernization efforts due to the high costs associated with upgrading legacy systems.

In a world increasingly driven by data, this statistic highlights a significant challenge: how can manufacturers harness the power of real-time data when their equipment was never designed for it? For companies with older machines and manual processes, the data needed to drive efficiency and optimize operations remains trapped, creating a visibility gap that hinders their ability to compete in the era of Industry 4.0.

Milvian Group COO John Traynor shares his insights from decades of creating solutions for manufacturers in the paper The Challenge of Data Collection and Action in Manufacturing: Navigating Legacy Equipment and Manual Processes.

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The Legacy Conundrum

Legacy equipment—machinery that has been in operation for decades—often lacks the sensors and connectivity that modern machines use for real-time data capture. These machines are robust and reliable, but they operate in isolation, leaving critical data such as cycle times, machine health, and productivity metrics locked within. As the demand for digital transformation grows, manufacturers find themselves struggling to bridge this disconnect. Without the necessary data integration, even the best-run facilities can face inefficiencies and operational blind spots.

Strategies for Improved Data Collection

So, what can manufacturers do to overcome these challenges without a complete overhaul? The key is in incremental modernization. By gradually retrofitting legacy equipment with IoT gateways and sensors, manufacturers can begin to collect valuable data from their older machines. This phased approach allows companies to spread out investments over time while testing the effectiveness of new technologies on a smaller scale before committing to full-scale implementation. For example, companies like Bosch have successfully utilized IoT gateways to connect legacy systems, enabling real-time monitoring and predictive maintenance that directly impact productivity and uptime.

The Human Factor

But it’s not just about upgrading machines; it’s also about addressing the human element. Manual processes, essential to many production lines, introduce variability that can be hard to track in real time. Solutions like semi-automated systems and wearable devices can help monitor these processes more consistently, ensuring that data captured is accurate and actionable. By equipping workers with the right tools and technology, manufacturers can minimize human variability, enhancing the overall accuracy and reliability of their data collection efforts.

A Path Forward

The path to modernizing legacy systems and manual processes isn’t without hurdles, but it is achievable with the right approach. By implementing phased technology upgrades and leveraging the power of data analytics, manufacturers can begin to transform their operations step by step. The ultimate goal? Achieving a level of operational visibility that not only improves efficiency but positions them for growth in an increasingly competitive market.

Want to learn more about how to tackle these challenges and take your manufacturing operations to the next level?

Read the full paper from John Traynor, co-founder and COO of Milvian Group, for in-depth strategies and expert insights tailored to help you navigate the complexities of legacy systems and manual processes.