Kyle Huebner looks at where the electronics industry is today
There is a tendency to refer to new and innovative technology as ‘disruptive’, akin to something negative or irritating, when really it has the potential to introduce fresh and exciting ideas to an industry. While that potential is exhilarating, the transition into the new normal is a time of uncertainty. A meaningful disruption of any industry is a meticulous process, gradually testing and introducing entirely new techniques, technologies and ideas with deliberation. When enough of these ideas come to fruition at the same time, the results can be revolutionary.
Industry 4.0 is the label assigned to the latest transformation in manufacturing. It is a collective term for the continually expanding explosion of data exchange and computerisation in the manufacturing space. The digitalisation and connectivity that are already fundamental to many elements of modern manufacturing offer the potential for the bar in manufacturing to be permanently raised. In the words of MIT scientist George Westerman, such technologies are the difference between ‘a caterpillar turning into a butterfly [and] a really fast caterpillar.’
Artificial intelligence (AI) is the most important catalyst in the change facing the industry today. AI is capable of mechanising processes, boosting efficiency and saving labour by automating human involvement. When truly integrated with automation, the benefits transcend the shop floor and permeate the business from the top down. AI can connect machinery in a way that allows devices to ‘speak’ to each other, collating countless volumes of data to analyse performance across the entire manufacturing process.
This data can, with the right strategy and insights, result in hugely enhanced performance and operational versatility. Not only can existing processes become more streamlined and cost-effective, but manufacturers can make operational changes based upon the projections that AI provides.
No other technology has offered the physical on-site benefits alongside such strategic introspection since the computer. From the supply chain to the introduction of robots, AI is driving industry-wide digitalisation through self-evaluation; it introduces both game-changing mechanisms and the analytical lens to improve them.
All this buzz has led customers to approach design through to manufacture companies and specifically ask how they leverage AI to build products more efficiently or how the end result benefits.
This will differ in every use case. As AI doesn’t have a universally agreed definition, it means it’s easy for companies to add excitement to a product or services by namedropping it. Deep learning, machine learning, neural networks and so on are amalgamated into an exciting, complex and nebulous idea that is used as something of a marketing ploy.
As a general rule, the brute-force element that is Industry 4.0 has given way to the idea of more ‘sophisticated manufacturing’, which has erroneously at time been termed as AI. This is the use of technology to incrementally improve every part of the business. There is the potential here for paper to transcend into the digital, with every document or data point becoming another node of information to help decision makers and operation management.
For all of the excitement around AI, there is an understandable risk of attempting too much, too soon. You can’t go into every function on the manufacturing floor and plug in technology to guarantee improvement.
Once the hype around AI dissipates and the real-life applications of the technology become more commonplace, expectations will begin to find a balance between idealism and realism. The better we get at writing and understanding the behaviours of AI, the more function can be applied on both sides of the customer relationship. Demands will be met in a more reliable and predictable fashion, and the production cycle will be quicker than ever before.
The human factor
Just as AI champions can be too enthusiastic in the applications of the technology, so too can sceptics bring the negative associations of ‘the all-knowing machine’ into their evaluation of how and where the technology should be disrupting processes and industries.
Some would argue that streamlining is not necessarily beneficial if it eliminates jobs. As recently as January The Daily Telegraph suggested that four in five manufacturing firms are struggling to secure skilled workers, whilst Engineering UK’s 2018 industry report highlighted a shortfall of 124,000 skilled (Level 3+) engineers. The removal of further positions in favour of an AI-based alternative could theoretically exacerbate this.
History has proven this sort of thinking to be false. It may be difficult for manufacturers to acquire skilled employees, but a technology that makes a powerful and beneficial impact will demand that people learn how to use it. We did so with the computer, which is now a staple part of business communications. At the time of adoption, the level of familiarity and education of the tool was quite varied.
Every company in the AI sector expects AI to create more jobs and is strategising based on this assumption. When the ATM was invented, people said it would destroy banks by removing the need for tellers. But less tellers per bank meant that banks could open more branches, allowing them to vastly widen their footfall and hire more tellers than ever.
“At the dawn of the self-service banking age in 1985, for example, the United States had 60,000 automated teller machines and 485,000 bank tellers. In 2002, the United States had 352,000 ATMs – and 527,000 bank tellers. ATMs notwithstanding, banks do a lot more than they used to and have a lot more branches than they used to,” – Charles Fishman, The Toll of a New Machine, FAST COMPANY.
There are also elements of manufacturing that simply do not suit automation and AI’s involvement. Humans are exceptional at handling variation, have a creative capacity that data cannot accommodate for, and – even if nothing else – are needed to maintain executive control on the AI systems that are being introduced.
Ultimately, AI is a tool for humans to harness. It makes industry more attainable and manageable, opening up far more opportunities than it kills. The impact that it will make in the long term on the human skill-set will create jobs across every industry in maximising its potential.
Kyle Huebner is Manufacturing Automation Manager at Plexus. Plexus is an industry leader that specialises in serving customers with complex products, providing global Design and Development, Supply Chain Solutions, New Product Introduction, Manufacturing and Aftermarket Services. With a culture built around innovation and customer service, Plexus’ teams create customised end-to-end solutions to assure the realisation of the intricate products in demanding regulatory environments.