-Robert Le Busque, Regional Vice-President, Asia Pacific, Verizon Business
In Australia, the rapid development of artificial intelligence (AI) has coincided with the Government’s announcement of the $15 billion National Reconstruction Fund (NRF), $1 billion of which will be dedicated to reinvigorating, accelerating, and building up advanced manufacturing capabilities.
As businesses have already started adopting AI for various use cases, the Government has also recently launched a public consultation to seek advice on how to mitigate any potential risks and ensure it is applied responsibly.
One of these uses cases is advanced manufacturing, which is a broad term that encompasses technologies applied to any manufacturing facility, including application software and AI tools to augment and generate higher value manufacturing output.
Advanced manufacturing is also likely to use AI to embed faster and safer means of production and better operations management for industrial processes.
Generating speed, safety and enhanced production
Part of removing human error to make manufacturing safer and faster means reducing reliance on human observation. As machinery drivers and operators are among the top three occupation groups with the highest rate of work-related injuries in Australia at 6.5 percent in the 2021-2022 financial year, this makes a use case for AI analytics in augmenting workplace health and safety.
High precision tracking, for example, detects faults in machinery micro-components at a scale previously unachievable – this improves productivity, output, and profitability for manufacturing companies.
AI analytics can match workers’ physical position in relation to how they interact with machines, particularly heavy industrial machinery, facilitating a more comprehensive understanding of safety in workplace operations and injury.
AI software can also manage workflows more effectively by identifying and allocating tasks. This can be taken one step further, with large site and heavy industrial manufacturing operations using digital twins to optimise these workflows – by using a virtual model designed to accurately reflect the manufacturing process to model operations and planning at significant scale.
These digital twins can show how people and equipment can be moved and managed more quickly and safely around a site in a controlled manner before applying it to the actual operations.
These use cases for AI are less about employing “robots to take manufacturing jobs”, and more about creating a productive workforce and giving advanced manufacturers a competitive edge. The challenge for individuals and corporations is to understand and embrace how this technology can enhance current advanced manufacturing processes, rather than downplaying the potential.
Upskilling workers and investing as a business in emerging tech
Businesses that will benefit most from AI tools are those that couple the technology with well-trained professionals with the skills to augment and uplift automation processes. There is a great opportunity for workers within this sector to upskill and familiarise themselves with these technologies to enhance their careers.
Now is the time for those employed in the manufacturing sector to consider opportunities for retraining and upskilling, in particular within organisations that have a vested interest in facilitating such training to enhance future career pathways.
While a majority of Australians (59%) are worried that automation is putting their jobs at risk when responding to a survey facilitated by PwC, the report also shows that of the 39,000 workers surveyed, 60 percent agree the technology presents more opportunities than risks.
Most heartening is that three quarters of respondents to the survey are ready to learn new skills or completely re-train in order to remain employable in the future.
With capital decisions carrying longer term implications, it’s important for manufacturing businesses to consider their investment in any technologies and operational uplift, whether that be AI or other emerging technologies, including the current and future needs of upskilling their workforce and plan at least 5 or ten-years’ ahead to avoid sunken costs and stranded assets.
IT will also require upskilling of the workforce and considerations regarding ethics, privacy, and cybersecurity. Therefore, a comprehensive approach that combines AI implementation with human expertise is crucial for successful transformation in the manufacturing sector.
We are yet to see what the future looks like where advanced manufacturing is largely driven by AI, but from what we have seen so far, we know it will make production more agile, efficient, and safe for a workforce that will become more highly skilled as they grow familiar with and train in it.