Artist's representation of the IIoT

What Comes Next? Industrial Manufacturers Seek Better Pathways

Dec. 14, 2021
COVID-19 accelerated technology adoption, but not everyone knows what they adopted. What’s next in a post-pandemic world?

On any given workday we see the world through the lens of our industries. But the added burdens of the pandemic—compounded by ongoing supply chain issues, unemployment and grim societal stressors—have exposed fragilities and highlighted challenges now etched into organizational consciousness.

Over the past year, companies grappling with such global trends as climate change, decarbonizing, cybersecurity, flexible working, and diversity and inclusion have expanded efforts to manage risk and build resilience. As vaccination campaigns rage on and amidst new variant threats, decision-makers continue to make sense of it all.

A recurring theme has been the dramatic uptick in the use of technologies to both bolster contactless interaction and to insulate from further supply chain disruption. Far from being meticulously planned, scalable transformations, the use of digital infrastructure and technologies have offered respite in the course of disruption.

Effective transformations are essentially about the people and involves changes to organizational dynamics and how work gets done, argue the authors of The Technology Fallacy. A good measure of insights from the past, an agile mindset and digital savvy are all requisite for digital maturity, they said.

These very sentiments were echoed when Machine Design recently asked a range of thought leaders to consider this question: COVID-19 accelerated technology adoption, but not everyone knows what they adopted. What’s next in a post-COVID world?

These important views have been examined and rolled out in several recent Machine Design articles. (See the related links at the end of this article.) Some provide fresh insights on trends that gained momentum through the pandemic, while others reflect on how the pandemic shifted their view and how they will act on what they see.

As for the thought leaders we contacted, what follows are the responses submitted by several of them.

Successful adoption of lights-out manufacturing depends on digital maturity.

Deborah Holton, president of Metrix Connect LLC, an ASME Company

The combination of skilled worker shortages, COVID-induced remote operations, and increasing capabilities of robotics and automation has accelerated the adoption of “lights out” and automated factories. Although lights out manufacturing—using automation, machine monitoring technology, sensors, robotics and software to run equipment in a third shift with little or no human intervention—is not a new concept, the pandemic has accelerated the need to maximize productivity with fewer workers and to run factories remotely.

Through digital technologies like Edge computing, IIoT, cloud data, machine learning and robotics, companies can utilize machine data to replicate and automate processes, improving quality and creating a safer workplace. Software, systems, robotics and machines work together to increase productivity. It’s not quite a set-it-and-forget-it situation, as maintenance increases and some processes are better suited than others to full automation. But if the robots can run the factory while we’re away, that could mean a new level of productivity for manufacturers looking to maximize their potential.

Pivoting toward a circular economy model gives consumers more control.

Cindy Jaudon, regional president, Americas, IFS

During the COVID-19 lockdown I saw firsthand how some of our manufacturing customers were quick to adapt, were able to take on the challenge of adopting new technologies and understood the need to manage change.

Having made the pivot, these are the companies who are now ready to undergo an even greater transformative shift away from the traditional break/fix model and towards a more circular economy model that focuses on product lifecycle extension and ecological methods of operating.

This will require new servitization offerings, selling product outcomes and support rather than a one-off sale, to reduce, re-use and recycle in the manufacturing process. This is where advancements in disruptive technologies such as artificial intelligence (AI), digital platforms and cloud-based enterprise solutions can help. These technologies will help enhance product flow, increase resource traceability and incorporate new processes such as reverse logistics to lengthen product lifecycles and improve waste management control.

Transformation is driven not just by technology, but also by consumers, as well as legislative actions such as the historic “Right to Repair” Presidential executive order. This makes it clear that we’re all in this together and long-term sustainability must be a new goal for manufacturers.

Consumers will start to have more control over how they purchase products and services. We’ve all seen today’s consumers demanding greater sustainability practices from the businesses they purchase from—with more than half willing to pay more for sustainable brands.

This will change manufacturing processes forever and enable the industry to recover strongly—and contribute to a better society.

Tracking critical components through e-commerce tools can foster new supply channels.

John Lamb, automation & fluid power specialist, Motion

The concept of building a “smart” factory to improve reliability through data analytics has accelerated. It is being accepted as a viable replacement for knowledgeable, skilled long-term employees who are now retiring. Many industrial companies are increasingly looking for third-party support and new technology to keep their operations running smoothly and reduce costly downtime. This trend was accelerated by COVID-19 and will be long-lasting. This will encourage innovation as a new mindset will disrupt traditional ways of doing business and supply channels.

Many intelligent platforms can monitor machinery 24/7/365. A simple temperature/vibration sensor can help identify machinery that isn’t running to specification and can sound an alarm to check on the equipment before a complete failure occurs. This will change the workforce within the industrial sector as new technologies will be reviewed, implemented and maintained, requiring new skills and knowledge.

Tracking critical components through e-commerce tools and an increasing need for value-added services will redefine B2B relationships. Outsourcing for expertise and support on specific technologies is a trend that will only increase in a post-COVID world.

Adoption of AI solutions can provide insights for future digital capabilities.

Artem Kroupenev, vice president of strategy, Augury

In the past two years, some of our manufacturing customers invested as much as 10 times the amount in AI-driven technologies as they have in the five years prior to the pandemic. With the increase in investment, we’ve seen that companies have become more thoughtful about what capabilities they acquire versus attempting to build in-house.

As a result, there has been an increase in adoption of full-stack solutions driven by AI, rather than more generic AI tools that have to be engineered by the end-users to solve a problem. Another consideration among manufacturing leaders during the pandemic was to focus on adopting AI solutions not just for their future benefits, but for their ability to quickly and effectively solve an immediate problem.

As a result, there has been a shift in mindset to pursuing scalable full-stack AI solutions, which are chosen based on ease of implementation, fast operational outcomes and clear ROI they provide. Full-stack AI solutions that can create resiliency in manufacturing have been a major focus of manufacturers over the last two years.

Augury’s Machine Health platform is a great example of a new generation of full-stack AI-driven solution that has gained rapid adoption during the pandemic due to its clear ability to reduce quickly unplanned downtime, easily scale and to provide foundational insights for future digital capabilities. Utilizing AI to in this manner ensures that factories overall are more productive; machines are always running at optimal capacity; and that manufacturers can truly futureproof their ability to overcome the next industry-wide disruption in manufacturing.

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