From art to science: the opportunity for AI in manufacturing
July 2019 | SPOTLIGHT | BOARDROOM INTELLIGENCE
Financier Worldwide Magazine
July 2019 Issue
Artificial intelligence (AI) is expected to nearly double employee productivity gains in Asia Pacific (APAC) by 2021, according to a recent study from IDC Asia/Pacific and Microsoft. However, there is a long way to go before then, with nearly 60 percent of manufacturers who responded to the study saying they have not adopted AI as part of their business today. The gap between where manufacturers are and where they believe they will be in just a few short years highlights two important lessons.
First, AI is an immense opportunity. Progress and improvements are being made all the time in manufacturing, but there is not a new piece of equipment, improved assembly process or management style that even comes close to the breadth and depth of the potential improvements being associated with AI. The fundamental difference is data. Every single element of manufacturing, or any business for that matter, generates data and AI is the only way all that data can be utilised; it is simply too much for any human to handle.
Second, there are real, tangible barriers to AI adoption which companies must address to take advantage of the technology. Though they will be felt differently from company to company, these challenges are similar across the manufacturing industry and beyond. What is the opportunity for AI and how can it be actioned? How can a company culture be established and maintained to support AI adoption and integration? How do companies help their workforces capitalise on the benefits of AI while addressing the inevitable changes that will come with its implementation? What policies and regulations will allow AI to thrive, while preserving trust and equity?
In The Future Computed: AI and Manufacturing, Greg Shaw addresses these lessons with examples from leading manufacturers, following their stories as they use AI to create the factories and supply chains of the future. Their successes and setbacks reveal an industry eager to push to the forefront by adopting transformative new technologies and using data-driven technologies to optimise processes, increase productivity, develop new products and services and create safer working environments.
The book’s focus on manufacturing highlights the industry’s foundational role in economies across the world.
Through AI, manufacturers will have the opportunity to advance their work in previously unimaginable ways. For example, once siloed data sources, such as environmental conditions and upstream production changes, can be merged to save a fraction of a second during a process. That saving can be repeated tens or hundreds of thousands of time a day, yielding enormous efficiencies. Where front-line employees might have been able to make these decisions accurately from time to time, AI will be able to consistently take advantage of these opportunities, adjusting throughout the process so efficiency is not gained in one area only to be lost in another.
At the same time, AI can also be leveraged to reduce the risks from slowdowns or stoppages, alerting managers to preventive maintenance opportunities and reducing workplace injuries through creative solutions like ‘cobots’(collaborative robots that work alongside their human counterparts and which have enough intelligence to avoid accidents common with existing equipment and machinery) or from repetitive or difficult tasks. These efficiencies can increase a company’s ability to leverage its human capital, while also increasing workplace satisfaction for workers by removing hazardous and laborious tasks.
Manufacturers must step up and play a role in developing strategies to support an increasingly distributed workforce, increase the availability, quality and governance of data – including working with policymakers to maintain trust and define ethical use cases – and reskilling workers to providing opportunities for everyone to realise the benefits this technology offers.
The book does not claim to have all the answers; rather, it provides a platform to advance these important discussions among manufacturers, policy makers technology providers, and other stakeholders in Asia Pacific and beyond. As these conversations occur, manufacturers and many other businesses will better understand the steps they need to take in their AI journey.
Scott Hunter is regional business lead, manufacturing and resources at Microsoft. He can be contacted on +65 6888 8774 or by email: firstname.lastname@example.org.
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