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Digitalisation: the pandemic effect

10 January 2022

Ravi Gopinath discusses the effects that the past 18 months have had on the speed of digitalisation across the manufacturing sector. 



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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 optimising organisations in unpredictable times. Put simply, it has showed how 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 there has been a need to respond with transformative action. 

As such, the crisis has fast-forwarded the digital transition by around five years. Several developing technologies are set to underpin a sustainable, optimised and streamlined future.

Cloud computing
The industrial sector is rapidly digitising. Companies that were 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 organisations 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 digitisation efforts, worldwide spending on AI systems will reach $98 billion by 2023. 

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 that key thresholds for safety, performance or other metrics are being met or exceeded. 

Connected workforce
The impact of pandemic-driven worker lockdowns has forced organisations 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. 

These innovative technologies allow companies to visualise a single operating view in 1D, 2D, 3D, real time, or fully immersive virtual reality environment. 

As we begin 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. 

I predict 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 organisation 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.

Ravi Gopinath is chief cloud officer and chief product officer at AVEVA.


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