The Talent Gap

Since 2010, an estimated 10,000 babyboomers have reached retirement age every day and will continue to do so until 2030, including many workers in the power generation and oil and gas industries. As the energy industry watches its core workforce prepare for retirement, it’s faced with replacing valuable years of knowledge and acquired talent from a limited pipeline. 

In the last decade, the energy industry has struggled to attract new talent to backfill open positions. Millennials and generation Z, the youngest entrants into the workforce, are opting to pursue non-conventional energy careers in computer science and consumer technology, rather than in plant engineering, operations or management. Some also associate the traditional industrial landscape with large-scale accidents and resulting environmental concerns, making it difficult to encourage them to seek job opportunities that are open. 

Industrial companies have an opportunity to change the mindset of new grads and young adults by focusing on the potential of the industrial Internet and big data. This will help capture and transfer the knowledge of the retiring workforce while offering new and innovative frontiers for job growth that is suited for younger generations.

Years of Knowledge

For many energy organizations, past overreliance on the retiring workforce has resulted in the need to capture years of knowledge by digitizing operations manuals and databases so that less-experienced professionals have a resource to learn and operate from. For example, human machine interfaces (HMIs) interact with turbines, compressors and control systems to share critical data on asset performance and to provide alarms when issues arise. 

Based on their years of experience and understanding of how individual machines behave on the plant floor, veteran engineers can identify in real-time which alarms require immediate action and which ones can be addressed through scheduled maintenance. 

Less-experienced professionals, on the other hand, may need to consult a manual or seek reactive input from the original equipment manufacturer (OEM) to help determine the type of alarm and how to manage the corrective action. This can lead to equipment being taken offline and inspected to ensure safety, which results in costly downtime. 

To ensure the same level of efficiency when addressing alarms – regardless of engineering experience – the digitization of manuals, alarm and data management processes provides operators easy access to computer guides and searches. Establishing digital rules even enables the machine and control network to react to the alarms directly without the interference of an operator. 

The OEM’s insight has been captured from decades of aggregate equipment service experience across multiple applications. This machine knowledge and insight can be made available with state-of-the art digital alarm management software tools embedded in new HMIs and control systems. 

Engineering teams also previously relied on physical drawings and paper diagrams for machine behavior and component information. Digitizing blueprints and drawings, particularly with cloud technology, means engineers can now collaborate across remote locations to edit documents and make notes, improving project dynamics and productivity. This process also improves knowledge transfer by allowing less-experienced engineers and technicians to collaborate directly with more experienced professionals through digital devices and channels.

Beyond digital manuals and operation, virtual models or “twins” that simulate in parallel the physical equipment and its operation, such as turbines and controls, have dramatically transformed industrial operations and asset productivity. These dynamic virtual replicas allow operators to distinguish between how the machine is performing in real-time compared to how it should be performing under optimal conditions and flag any health concerns or failures before they happen. 

In the past, workers relied on measurement readings, understanding of the equipment and experience with maintenance issues to provide insight about operations and equipment health. Industrial oil and gas and power generation operations can benefit from the help of virtual models, remote sensors and data analytics to provide a clear dashboard with a holistic picture of operations and any recommended actions for improvement, helping less-experienced workers efficiently run operations and proactively address maintenance needs.

Paving the Way

While smart machines have greatly improved industrial operations, there have also been concerns about process safety with fewer operating hands on the plant floor, particularly during a disaster. In 2011, the tsunami in Japan caused partial meltdowns of three nuclear reactors at the Fukushima Daiichi plant, requiring emergency evacuations based on health and environmental concerns. 

Today, more advanced digital protocols have made it possible for plants and machines to shut down safely and enable employees to walk away from dangerous events. Further, emerging centralized control centers operated by experts with cyber-secured remote access to multiple sites enable machines to operate safely without operators physically onsite. 

The transition to digital technologies not only reduces the impact of the retiring workforce’s departure, but also helps appeal to the next generation of workers, who are familiar with smart devices and constant connectivity. 

These new technologies transmit so much data that there is information overflow requiring more effective storage and management. As a result, the energy industry is turning toward big data analysis, offering new job opportunities in this field and utilizing that data to create valuable insight, ultimately transforming the way the industry operates and paving the way for a new workforce. 

HOMERO ENDARA is the oil and gas product line leader at GE Measurement & Control. He develops and implements market-driven growth initiatives, leads key market penetration programs, and drives global business strategy with focus on growth and profitability. Endara holds a bachelor of science in chemical engineering and an MBA from the University of Massachusetts, Amherst. 

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