What Will Be the Top 5 Trends in Automation in 2023?
Industrial automation investment will continue to be driven by the pandemic’s aftereffects and the ongoing global skills shortage in 2023, not only to supplement the existing workforce but also to unlock new business capabilities and insights.
Since the first industrial revolution, automation has driven advancement, but the emergence of robotics and artificial intelligence has increased its influence. According to Precedence Research, the size of the global industrial automation market was estimated to be USD $196.6 billion in 2021 and is expected to reach USD $412.8 billion by 2030.
According to Forrester analyst Leslie Joseph, this surge in automation adoption will be fueled in part by businesses of all sizes taking precautions against potential future events that might affect the availability of their workforce.
Automation has played a significant role in reshaping work since well before the pandemic; however, it is now becoming more urgent in light of business risk and resilience. Businesses will turn to automation as we come out of the crisis to reduce the risks that upcoming crises pose to the supply and productivity of human workers. They will increase their investments in industrial robotics, service robots, cognitive capabilities and applied AI, as well as robotic process automation.
The top 5 automation trends for 2023 indicate a shift toward intelligent automation, which unlocks a wider range of business benefits, from the initial focus on increasing output while lowering labour costs.
01. Artificial Intelligence
According to 2019 research from the Capgemini Research Institute, more than half of Europe’s top manufacturers have already implemented at least one AI use case in manufacturing operations. The market for manufacturing artificial intelligence was worth USD $2,963 million in 2021, but it’s expected to grow to USD $78,744 million by 2030.
AI has many applications in the manufacturing industry, including intelligent production automation and distribution and warehousing. In terms of their suitability for launching a manufacturer’s AI journey, the three use cases that stand out are intelligent maintenance, product quality control, and demand planning.
According to Capgemini, the majority of AI use cases in manufacturing operations revolve around “autonomous objects” that can complete tasks on their own, such as collaborative robots and autonomous mobile robots.
02. Collaborative robots
Cobots demonstrate the potential of automation to support workers rather than replace them because they are made to work safely side-by-side with humans and quickly learn new tasks. New capabilities are being unlocked by developments in artificial intelligence and situational awareness.
Global sales of cobots are anticipated to increase dramatically, from USD $1.2 billion in 2021 to USD $10.5 billion in 2027. By 2027, according to Interact Analysis, cobots will make up 30% of the entire robot market.
Principal Analyst at ABI Research Rian Whitton says
“Collaborating with humans is not where cobots’ most immediate advantage lies. Instead, it is in their relative simplicity of use, enhanced user interface, and end users’ ability to repurpose them for various tasks.
03. Robotic Process Automation
Robotics and automation are expected to have an equally significant impact in the back office as they will on the factory floor. Robotic process automation (RPA) enables businesses to automate manual, repetitive processes and tasks that, while typically performed by people, can be managed by set procedures, such as entering data and processing forms.
Similar to mechanical robots, RPA is made to perform simple heavy lifting. RPA advancements are enabling it to handle processes that call for more dexterity, just as industrial robotic arms progressed from welding cars to handling more complex tasks.
According to GlobalData, the market for RPA software and services will be worth USD $20.1 billion worldwide in 2030, up from USD $4.8 billion in 2021. For Nicklas Nilsson, a Thematic Research Consultant at GlobalData,
The importance of coordinating automation throughout a business was highlighted by COVID-19. RPA’s development has accelerated as a result, as businesses now offer RPA as a component of a larger toolkit of automation and artificial intelligence technologies, enabling the end-to-end automation of more complex business processes.
04. Mobile robots that are autonomous
Autonomous mobile robots are advancing logistics automation in a similar way that robots are advancing automation on the production line. According to research firm Allied Market Research, the market for autonomous mobile robots was estimated to be worth USD $2.7 billion in 2020 and is expected to grow to USD $12.4 billion by 2030.
According to Dwight Klappich, VP Analyst, Supply Chain Technology at Gartner: “Autonomous mobile robots have evolved from autonomous guided vehicles with limited functionality and flexibility to take advantage of artificial intelligence and improved sensors.”
“AMRs give previously “dumb” automated guided vehicles (AGVs) intelligence, guidance, and sensory awareness, enabling them to function independently and around people. Traditional AGVs have historical limitations, which AMRs address, improving their suitability and cost-effectiveness for complex warehouses.
05. Predictive Maintenance
Artificial intelligence is advancing predictive maintenance beyond the simple automation of current maintenance tasks by enabling it to pick up on minute cues to optimise maintenance schedules, identify faults, and anticipate breakdowns before they result in expensive downtime or damage.
According to a report from Next Move Strategy Consulting, the global market for predictive maintenance generated USD $5.66 billion in 2021 and is projected to grow to USD $64.25 billion by 2030.
A real-world use of the Industrial Internet of Things is predictive maintenance. According to Gartner, enterprise asset management products will deliver 60% of IoT-enabled predictive maintenance solutions by 2026, up from 15% in 2021.
