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The impact of the pandemic and the ongoing global skills shortage will continue to drive investment in industrial automation through 2023, not only to increase the number of existing workers, but also to open up new business opportunities and ideas.
Automation has been the driving force behind progress since the first industrial revolution, but the rise of robotics and artificial intelligence has increased its impact. According to Precedence Research, the global industrial automation market is estimated at $196.6 billion in 2021 and will exceed $412.8 billion by 2030.
According to Forrester analyst Leslie Joseph, this boom in automation adoption will occur in part because organizations in all industries are immune to future events that could again affect the availability of their workforce.
“Automation was a major driver of job change long before the pandemic; it has now taken on new urgency in terms of business risk and resilience. As we emerge from the crisis, companies will look to automation as a way to mitigate the future approach to the risks the crisis poses to supply and human productivity. They will invest more in cognition and applied artificial intelligence, industrial robots, service robots and robotic process automation.”
Initially, automation was focused on increasing productivity while reducing labor costs, but the top 5 automation trends for 2023 indicate a growing focus on intelligent automation with broader business benefits.
According to a 2019 study by the Capgemini Research Institute, more than half of the top European manufacturers have implemented at least one use of AI in their manufacturing operations. The size of the artificial intelligence production market in 2021 was $2.963 billion and is expected to grow to $78.744 billion by 2030.
From intelligent factory automation to warehousing and distribution, the opportunities for AI in manufacturing abound. Three use cases that stand out in terms of their suitability for starting the journey of an AI manufacturer are intelligent maintenance, product quality control, and demand planning.
In the context of manufacturing operations, Capgemini believes that most AI use cases are related to machine learning, deep learning, and “autonomous objects” such as collaborative robots and autonomous mobile robots that can perform tasks on their own.
Designed to work safely side by side with people and quickly adapt to new challenges, collaborative robots highlight the potential of automation to help workers, not replace them. Advances in artificial intelligence and situational awareness are opening up new possibilities.
The global market for collaborative robots is expected to grow from $1.2 billion in 2021 to $10.5 billion in 2027. Interact Analysis estimates that by 2027, collaborative robots will account for 30% of the entire robotics market.
“The most immediate advantage of cobots is not their ability to cooperate with humans. Rather, it is their relative ease of use, improved interfaces, and the ability for end users to reuse them for other tasks.”
Beyond the factory floor, robotics and automation will have an equally important impact on the back office.
Robotic process automation allows businesses to automate manual, repetitive processes and tasks, such as data entry and form processing, that are traditionally done by humans but can be done with codified rules.
Like mechanical robots, the RPA is designed to do basic hard work. Just as industrial robotic arms have evolved from welding machines to perform more complex tasks, RPA improvements have taken on processes that require more flexibility.
According to GlobalData, the value of the global RPA software and services market will grow from $4.8 billion in 2021 to $20.1 billion by 2030. On behalf of Niklas Nilsson, Case Study Consultant GlobalData,
“COVID-19 has highlighted the need for automation in the enterprise. This has accelerated the growth of RPA as companies move away from stand-alone automation features and instead use RPA as part of broader automation, and the AI ​​toolkit provides end-to-end automation for more complex business processes.” .
In the same way that robots increase the automation of production lines, autonomous mobile robots increase the automation of logistics. According to Allied Market Research, the global market for autonomous mobile robots was estimated at $2.7 billion in 2020 and is expected to reach $12.4 billion by 2030.
According to Dwight Klappich, vice president of supply chain technology at Gartner, autonomous mobile robots that started out as autonomous, controlled vehicles with limited capabilities and flexibility now use artificial intelligence and improved sensors:
“AMRs add intelligence, guidance and sensory awareness to historically dumb automated vehicles (AGVs), allowing them to operate independently and alongside humans. AMRs remove the historical limitations of traditional AGVs, making them more suitable for complex warehouse operations, etc. cost-effectively.”
Instead of just automating existing maintenance tasks, AI takes predictive maintenance to the next level, allowing it to use subtle cues to optimize maintenance schedules, identify failures, and prevent failures before they lead to costly downtime or damage, predict failures.
According to a report by Next Move Strategy Consulting, the global preventive maintenance market generated $5.66 billion in revenue in 2021 and is expected to grow to $64.25 billion by 2030.
Predictive maintenance is the practical application of the Industrial Internet of Things. According to Gartner, 60% of IoT-enabled preventive maintenance solutions will ship as part of enterprise asset management offerings by 2026, up from 15% in 2021.