Design Engineering

The automation agenda: Unlocking potential and building resilience

By David Morgenstern   

Automation Accenture AI Automation digital twins

Canada is on the cusp of seismic change in manufacturing. Innovative technologies, advancements in sustainability and a new generation of talent are reshaping the industry. They’re also creating new opportunities for Canadian companies to scale and build resiliency through technology. This change is desperately needed after several years of historic disruption.

Geopolitical unrest, high energy prices, rising materials costs and demand fluctuations during the pandemic—each of these and more have challenged businesses like never before. Globally, businesses missed out on more than CA$2 trillion in revenue growth, according to a recent Accenture report. These disruptions have also exposed dangerously low levels of resiliency within engineering, supply chains, manufacturing and operations. 

As a result, businesses are taking action to rebalance operations closer to home, localizing sourcing and production, to reduce risk and cost. By 2026, 73 per cent of Canadian companies plan to buy key items from regional supplies, while 91 per cent plan to produce and sell most products in the same region.

For years, Canada has had a reputation for producing high-quality, precision-engineered goods, while developing cutting-edge technologies and processes such as automation, but as global demand calls for even faster innovation, Canadian manufacturers will need to take action not just to gain competitive advantages.

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Investing in automation

There is a noteworthy increase in automation investment, driven by the need for rapidly changing consumer demand, a diminishing pool of skilled labour and supply chain disruptions. Simultaneously, companies are recognizing the hyper-flexibility and high customization capabilities of autonomous production, which are pivotal for their capacity to adapt to change and reconfigure effectively.

Today, in Canada and the United States, only 10 per cent of factory labour (maintenance and operations) use technologies that enable remote workers. Just 27 per cent of companies use artificial intelligence (AI) extensively.

Companies that use advanced technologies like data, the cloud and AI to make their factories and plans smarter will see more productive, responsive, sustainable and safe results.

For example, automated machines streamline operations resulting in greater outputs in less time than traditional methods. These automated systems also provide an opportunity to reduce waste and energy consumption through resource optimization and decreased downtime. Ultimately, manufacturers who deploy automation across their production lines will be better equipped to handle fluctuations in demand and scale up and down as appropriate.

Automation also benefits workers. In hazardous environments with heavy machinery and strenuous labour, it can increase their safety by reducing the role of humans in dangerous or repetitive tasks. Workers can prioritize maintaining and improving automated systems and increasing efficiency.

 

Embracing digital twins

An increasing number of manufacturing executives are coming to understand highly adaptive plants which are closely integrated into the supply and product chains. This means leveraging massive amounts of data and AI to optimize operations automatically, requiring a new approach to manufacturing operations management. As a result, interest in digital twins has been growing at a rapid pace.

It’s important to remember that resiliency isn’t just a matter of agile supply and production; it’s also about getting products right from the start. By moving engineering activities to earlier in the development process—the so-called “shift-left approach”—companies can assess the potential impacts of disruption on the product at the time of design and reduce lead times.

Digital twins and simulations are vital enablers of this approach, and these solutions help build resiliency by enhancing transparency and offering real-time visualization of production activities. The digital replicas allow product designers and engineers to identify and troubleshoot potential prototype issues or defects and iterate the design before production begins. They also democratize access to valuable product data and insights, fostering improved collaboration during research and design phases.

 

Driving innovation with generative AI

As operational digital twins gain traction, generative AI will be imperative for accessing and managing the massive amounts of data they generate. There is already work being done to deploy “operations co-pilots,” allowing workers to interrogate the twin as they would an experienced manager to get support when completing tasks or solving issues. Generative AI will support the early resolution of issues before they can be addressed with repeatable and validated AI solutions.

By the end of 2024, generative AI experimentation will accelerate and lead to concrete realizations. With the right foundation, businesses will be able to easily adopt these emerging technologies and apply generative AI to functions across the organization, such as:

  • Maintenance job planning, which is currently a manual, human-intensive and repetitive process involving highly skilled practitioners.
  • Generative design and prototyping to help engineers and designers explore a broader range of design options for plants and products alike, as well as quality testing, supporting innovation and product differentiation, all in the same or shorter time, and reducing the number of iterations. For example, automotive crash tests are no longer required because they can all be simulated.
  • Code conversion from legacy automation equipment, which is often cost-prohibitive and where industrial engineers and maintenance technicians lack multiplatform skills. Generative AI offers the opportunity for assisted or even automated code conversion that is much more cost-efficient—and potentially more reliable.

Whether it’s using generative AI for prototyping purposes, improving human-robot collaboration or optimizing supply chain processes, there are efficiency gains to be made to improve overall productivity and growth.

 

Critical role of skilled workforce

The need for more skilled labour isn’t new for manufacturers. In Canada and other developed economies, an aging workforce and the ongoing reshoring of production capabilities are driving the competition for talent to new heights. The higher the companies set their ambitions to reinvent manufacturing with digital technologies, the bigger the issue becomes.

This scarcity is acute among data scientists and other technology and IT specialists. As automation evolves into semi-autonomous and, eventually, fully autonomous operations, a manufacturer will only survive with strong data and AI expertise. But the technology will also require new skills on the shop floor. One crucial skill that all workers need to have—and which companies must ensure workers can obtain—is the ability to use data to make decisions at the frontlines of business.

The growing impact of data and AI will also create new roles. The role of production engineers will evolve from keeping operations running to optimizing them via the twin. Maintenance technicians will prevent failures and plan interventions rather than react to crises once they happen.

Eventually, how people work together will change, as well. So-called autonomous teams will operate, maintain, schedule and quality manage lines or shops independently, rather than having line or shop operators and departments for planning, scheduling, quality control, maintenance, etc. A digital twin-based, real-time hypervisor (software that uses virtualization technology to create, run and manage virtual machines) will support them.

Fundamentally, achieving lasting resilience depends on a strategy for enhancing and updating skills, which involves uniting people and technology. Developing customized interventions, such as personalized learning pathways, offers a practical, scalable and cost-efficient approach to addressing the skills gap. By adopting this strategy, businesses can more effectively cope with shortages in crucial skills, foster an agile culture and offer swift, adaptable upskilling.

 

What’s next?

With Canada’s strength across energy, mining, nuclear, utilities, products and automotive sectors, manufacturers have a significant opportunity for growth and to become more resilient. This begins with making strategic investments in automation and technologies, such as operational digital twins and gen AI. These will only go so far, however. To achieve its full potential, organizations will need to put equal investment and dedication into building skilled workforces and re-imagining what and how work is done.

 

David Morgenstern is president of Accenture in Canada, where he supports leaders in business and government to embrace change, transform their organizations, and become more resilient for the future. He is passionate about advancing Canada’s position as a global leader in innovation, technology, sustainability and energy transition. This article was originally published in Manufacturing Automation magazine.

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