When and how will OEMs start to see the full benefits of AI across the manufacturing cycle? In our latest blog, Peter Gutschi, member of the ESCATEC board of directors, explores the potential long-term, transformative effects of AI in the EMS industry.
“AI is one of the most profound things we're working on as humanity. It's more profound than fire or electricity,” said Alphabet Inc. CEO Sundar Pichai.
Is he right?
Fire made all human tech progress possible. It led to metal tools, steam, electrification, and (by extension) the IT revolution and the birth of AI. It’s taken roughly 6000 years for that spark of tamed fire to take us from the Iron Age to Industry 5.0.
But AI promises to accelerate future discovery and industrial innovation at a rate we’ve never seen before.
And the manufacturing sector is no exception.
"AI is expected to boost global manufacturing productivity by up to 40% by 2035." Source: Accenture
As McKinsey concluded in 2023, LLMs (Large Language Models) are ushering in a new era of technological progress.
“Generative AI is… pushing technology into a realm thought to be unique to the human mind: creativity.”
Source: McKinsey
In other words, generative AI is not just sucking in and rearranging pre-existing information like older AI applications but minting original ideas based on gathered insight, analysis, and its own learning from massive datasets. And it can do so in seconds.
To take just one example, in the bioscience realm, AI platforms powered by machine learning have already collapsed the discovery time for certain novel cancer treatments from decades to months.
With these self-learning AI models, it’s possible to imagine product development and manufacturing cycles, prompted by humans but refined, managed, and automated by computers from beginning to end.
"Companies using AI in their product development processes can reduce time to market by 20-40% and cut development costs by 20-30%."
Source: Virtasant
Here’s an overview of some of the exciting possibilities of AI and associated innovations happening in the electronics manufacturing industry right now:
AI is already being used by major companies to project trends and generate innovative product ideas:
AI tools are also being used by manufacturers to generate various critical assets in the product development cycle:
When it comes to production planning, AI-powered tools are transforming processes by enhancing efficiency, which is, in turn, reducing time to market and optimising resource use across industries:
In the supply chain, AI algorithms are optimising inventory management, demand forecasting, and logistics, helping businesses handle supply chain challenges more effectively, minimising disruptions and improving overall resilience.
AI-powered robots and cobots are improving manufacturing processes on the factory floor:
Technology like sensor data is being used by AI tools to analyse and improve equipment performance:
In electronics, AI-powered machine vision systems are enhancing product quality across the industry:
AI facilitates the comprehensive analysis of product performance and customer feedback, helping businesses prime assembly lines for next-generation models with minimal human input:
Already, we are seeing different EMS companies using AI in various ways to offer a competitive advantage to their customers.
Change will be profound.
Routine tasks will be automated, leading to a decline in certain roles.
However, there will be a much greater need for a highly skilled manufacturing workforce with a broad range of experience and technical skills, such as:
Workers will collaborate more fully with robots and AI systems, and human roles will focus more on problem-solving, creativity, and adaptability.
Existing workers will need to acquire new skills. Successful training will need to focus on AI-literacy, programming, and understanding of the new AI-driven systems we have explored above.
Soon, there will be intense competition for those with these skills in the employment market.
Many EMS companies are already integrating AI into their processes, and those workers exposed to these systems are adapting fast.
But there are serious obstacles to negotiate, too.
As Adam J. Fleischer of Altium points out in his recent analysis of the impact of AI on electronics manufacturing:
“While AI can lead to significant cost savings in the long run, the upfront costs of implementing AI systems can be a blocker for smaller manufacturers.”
Plus, there are considerable challenges ahead in finding ways to validate the workings of ‘black box systems’, as they take more responsibility for designing, building and testing potentially lethal devices.
"IBM’s Global AI Adoption Index found that 56% of businesses using AI are not working to develop ethical AI policies, and 74% are making no efforts to reduce unintended biases."
Source: IBM
How quickly will AI transform the EMS sector?
The most significant push for AI adoption in the manufacturing sector will likely occur within the next 3 - 5 years. As AI matures, organisations will need to restructure roles as learning and development programs accelerate.
Companies will need ‘all hands on deck’ to figure out how they can best use AI to design and develop their products. This includes working out where they can most usefully outsource to manufacturers with the equipment and big data needed to build products more efficiently and to the highest quality.
Additionally, they need to consider how they can harness new AI technologies to accelerate the pace of their production ideation, R&D and prototyping.
Companies that have implemented Kazien processes for continual improvement and have a collective road map for organisational change will be best placed to transform the quality and efficiency of their practice with AI.