COVID-19

COVID-19’s effect on digitalization in manufacturing

The COVID-19 pandemic has had a marked effect on the speed of digitalization across the industrial and manufacturing sectors.

By Ravi Gopinath October 29, 2021
Image courtesy: Brett Sayles

As the world begins to recalibrate itself following the pandemic, businesses have undergone a radical and irreversible shake up. The crisis, while challenging, has offered radical insights into running and optimizing organizations in unpredictable times. Put simply, it has showed how industrial operations can be upended almost overnight. Workforce routines, supply chains, essential maintenance and parts movement were disrupted, while border closures and an unprecedented drop in demand squeezed already tight economic operations. To thrive in this brave new world, there has been a need to respond with transformative action.

As such, the crisis has fast-forwarded the digital transition of the industrial sector by around five years. Several developing technologies are set to underpin a sustainable, optimized and streamlined future for the energy industry.

Cloud computing

The industrial sector is rapidly digitizing. Companies that were initially hesitant to migrate to the cloud were compelled to make their move amid the pandemic, and now they are seeing transformational benefits. Cloud adoption is rapidly accelerating – industrial data volumes are set to treble in the next four years, topping 159 Zettabytes by 2024, according to IDC data.

By leveraging Cloud, companies can integrate standalone products, linking AI modules together into a broader intelligence for more efficient performance. With integrated systems comes integrated analysis.

Artificial intelligence (AI)

As AI becomes more sophisticated, with wider use cases, it allows organizations to improve productivity and make better decisions. With unified smart analytics that bridge complete data stacks, teams can leverage mathematical thought processes across all their activities. A recent IDC report predicts that in accelerating digitization efforts, worldwide spending on AI systems will reach $98 billion by 2023, more than two and a half times the spend in 2019.

Machine learning (ML)

By leveraging the power of machine learning, it is also possible to transform asset performance. Using a knowledge graph – a data map of the entire asset that uses AI and machine learning to build connections – over time the software comes to understand the critical processes and components needed for optimum asset management. The knowledge graph uses this information to help define the asset’s safe operating envelope, and to automatically notify the owner of key thresholds for safety, performance or other metrics are being met or exceeded.

Connected workforce

The impact of pandemic-driven worker lockdowns has forced industrial organizations across the globe to rapidly accelerate their migration to digital. With the help of technologies like cloud, the industrial internet of things (IIoT), digital twins, and AI, companies are overcoming supply chain, production, and distribution complexity obstacles by linking core processes into a unified remote digital environment.

Multi-experience and data visualization are driving new value for companies. These innovative technologies allow companies to visualize a single operating view in 1D, 2D, 3D, real time, or fully immersive virtual reality environment.

Companies are leveraging technology to optimize everything from flares and construction to operating procedures and decision-making.

As the industry begins to adapt and adopt technology at an unprecedented speed, what people now need above all is trust and partnership. Amid the pandemic, we saw a resurgence around giving the right people the tools to do their job, harvesting data, and predicting when facilities will fail.

There will be growing cross-industry collaboration across horizontal data and the development of standards. Even in times of rapid change, the two most valuable assets for any organization remains its people and its data. By integrating human insight and operational information, the way that we design, build, and run assets can evolve to be more efficient, intelligent, and sustainable.

– This originally appeared on Control Engineering Europe’s website. Edited by Chris Vavra, web content manager, Control Engineering, CFE Media and Technology, cvavra@cfemedia.com.


Ravi Gopinath
Author Bio: Ravi Gopinath is chief cloud officer and chief product officer at AVEVA.