(38a) Can Digital Twins Solve the Workforce (people) Challenges of the Process Industry?

The process industry has been blessed with an abundance of software and technology solutions that have transformed the way assets are managed and maintained, using data to enable predictive maintenance and other operational benefits. This has been very successful. However, the industry requires 'people' to operate and maintain these assets, and no matter how reliable or even automated these assets are, people need to perform frequent procedures and tasks on these assets to ensure effective and efficient production. The industry faces challenges of attracting and retaining skilled workers, dealing with the loss of equipment and procedure knowledge from experts retiring (great crew change) or general employee turnover, and upskilling workers quickly and effectively.

Digital twins have been part of this successful asset intensive focus, yet most chemical and refining companies are failing to utilize digital twins for building workforce competency more efficiently and effectively. Most Digital twins are based on CAD (Computer-Aided Design) technology, which has hindered applications for training and learning & development purposes. While visualization (of the plant assets) is key to improving training, learning and development and knowledge transfer, there are four aspects of CAD-based technology that have been a disadvantage for helping the human-asset interaction: realism, cost, usability and ease of updating. Digital twins based on Enhanced Reality (ER) technology, however, have been successfully adopted in the industry by some of the biggest chemical and refining companies in the world to solve the workforce challenges described above. Impact includes speeding up time to operator competency (up to 70% faster than traditional methods), cutting resources needed to train operators (reduction of trainer or SME time by 50% on average), capturing tribal knowledge related to specific equipment and procedures so it does not leave the plant, and reducing incidents related to human-asset interaction (zero incidents related to procedures that have been simulated in ER digital twins).

This paper will briefly analyze the four advantages of ER technology: realism, cost, user-friendliness and ease of updating. But the main focus will be on real examples and impact of ER’s digital twin and procedure simulators within the chemical and refining sectors, with particular focus on cutting the time to upskill the plant workforce, the ability to self-train/learn and cut training resources, and the reduction of incidents related to human-asset interactions. We will present (anonymous) data from major chemical and refining companies that collected data on ER digital twin simulation versus traditional training methods (time and resources), incident data related to specific procedures/equipment over time and increase in operator knowledge/procedure competency (real test scores). This paper concludes that digital twins, based on the right technology, can solve the challenges of the workforce in the process industry.

Some References:

ER digital twin (Voovio) was referenced in 14 Gartner Hype Cycles: https://www.gartner.com/en/documents/4003818-hype-cycle-for-life-science-manufacturing-quality-and-supply-chain-2021

Gartner Webinar: Build a Strategic Enterprise Roadmap With IoT for Composable Business, Al Velosa, Jun 16 2021 | 62 mins | Voovio starts at 19 min 19 sec - https://www.gartner.com/en/webinars/4001507/build-a-strategic-enterprise-roadmap-with-iot-for-composable-bus

The technology that ER is built upon, as described in the following patent, has been cited 63 times by Google, Apple, Samsung, Microsoft, Uber, Facebook, Adobe, Honeywell, Boeing and many more, making ER state-of-the-art. The patent also led to the creation of a new patent category for visualization Patent References: https://patents.google.com/patent/US20120099804A1/en

Data collected from over 10 customers using ER digital twin and procedure simulators from 2017-2021: 3 or 4 case studies on real life operations challenges that have been solved.

BASF public domain reference on ER: https://www.manufacturingleadershipcouncil.com/inside-basfs-customized-d...