The Impact of Poor Quality Engineering, Asset and Maintenance Data on Digitalization and Digital Twins

Asset Intensive organizations are increasingly under pressure to become more efficient by digitalizing their engineering, asset and maintenance information and making it readily available to employees who need it. This includes creating digital twins – broadly defined as virtual models of physical objects, systems or processes that mimic their real-world counterparts. Digital Twins for Maintenance have the potential to make it easier and more efficient for users to plan and execute maintenance work. But data quality issues make it very difficult to build and maintain an accurate digital twin.

The Information Management Gap in Maintenance and Reliability

These issues are exacerbated when you’re dealing with an older site or facility. For brownfield sites, drawings and P&IDs may not be up-to-date or may not exist at all. You may only have access to paper or scanned PDFs of drawings and documentation. On-site verifications may be required to confirm the data. But even then name plates on equipment may be missing, worn off or inaccessible. Keeping track of all this information accurately is a challenge.

For companies with thousands of unique pieces of equipment all requiring bills of material (BOMs) – the scope of the data management can become overwhelming. Managing that volume of data during a digitalization or digital twin building project is a challenge in itself. You may also need to keep track of changes and collaborate across a team that can include both internal stakeholders and external resources. Finally, updating thousands of complex data records in your EAM/CMMS and other asset management software and tools efficiently is a challenge when it comes time to update all of your systems.

Once you’ve updated all your asset management systems with accurate information you need to keep them up-to-date as changes occur to your facilities. These can occur due to repair, routine capital investment or process improvement initiatives. Keeping digital twins up-to-date is particularly challenging in the maintenance and operations realm because you are unlikely to have resources available with the skills to use CAD or other complex authoring solutions to update drawings and models. Solutions that can’t deal with missing or incomplete data also pose a problem since the information handover for these sorts of changes is often limited or non-existent.

 

Relying on maintenance and reliability workers to keep information up-to-date poses unique challenges. Information management is not a priority for workers trouble shooting critical issues, trying to keep production going and working within tight turnaround schedules. 

Impact on Maintenance
  • Difficulty planning and scheduling work
  • Difficulty finding and ordering the right parts
  • Misguided predictive maintenance schedules
  • Increased costs
Impact on Operations
  • Increased training costs
  • Lost production
  • Compromised decision making
  • Reduced operator efficiency
Impact on Reliability
  • Difficulty collecting and sharing reliability data for equipment
  • Inaccurate simulations
Impact on Engineering

  • Lack of standardization across the enterprise

  • Difficulty planning process improvements

  • Inaccurate simulations