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Jeff Kavanaugh

Every day, we hear of new examples of artificial intelligence (AI) being used to support, or supplant, the human workforce. Many of these discussions revolve around consumer-facing situations. However, the AI wave could have an even larger impact on the manufacturing sector, with its complex processes and machine-to-machine interactions spanning products and assets, within factories and across global supply networks.

This was highlighted in a recent study that investigated the approach of senior decision-makers in large organizations toward AI and its future applications.

Consider the digitization of factories. Flush with data from a sensor-enabled landscape, they’ve had a chance to join the ranks of the information intelligentsia and effectively drive rich floor output. Unfortunately, some in the manufacturing sector have ignored or even denied the disruptive impact of digital technologies. It took leaders like GE to envision how the Industrial Internet could become real for manufacturers. 

Smart Manufacturers are Automating Data

According to Oxford Economics, the Industrial Internet, with its connected sensors, represents more than 60 percent of the gross domestic product for the top 20 national economies. So for those using data automation to make more informed decisions, the opportunity — and also competition — is exploding with the emerging Industrial Internet binding products, equipment, and systems in a web of communication.

Eventually, Industrial IoT will permeate global supply chains, allowing manufacturers to accelerate product launch, coordinate demand-supply planning, and optimize production, in ways not possible without such advanced collaboration. Currently, the Industrial Internet is still in early development, but early adopters are seeing anecdotal successes as proof of concept projects continue to mount. 

Smart Manufacturers Can Automate Processes, too

The recent Infosys study, Ampliyfing Human Potential: Towards Purposeful Artificial Intelligence, surveyed 1,600 IT and business decision-makers from organizations of more than 1,000 employees with $500M or more annual revenue and from a range of sectors. The research was carried out in the U.S. and six other manufacturing and industrial nations.

It found companies planning to or currently using AI technology, such as robotics, anticipate a nearly 40 percent boost to their organization’s revenue by 2020. The economics of investing in robotic efficiencies is not lost on manufacturers. An example is Bosch, the German manufacturing company, which hopes to earn $1 billion dollars in additional revenue, and save another billion in costs, by using machine learning for predictive maintenance and self-monitoring.   

With robots attaining greater and greater degrees of sensitivity in their touch capabilities, they will be able to take over more assembly and movement-dependent activities on the manufacturing floor. At the same time, improvement in sensor and vision technology is creating smarter, lighter and friendlier co-bots that humans can work with safely. For instance, automobile maker BMW’s self-driving Smart Transport Robot travels the manufacturing floor, and sends out communication on any critical situation it sees.

Future of AI in Manufacturing

Savvy manufacturers will buck the offshore trend, use data to replace inventory, and experience enormous improvements in efficiency and reduction in costs as robots take over most of the assembling, moving, packaging, transporting and other physical tasks. Robots will be collaborative, working together and giving each other feedback. They will learn and improve and make smarter decisions — not just deterministic ones based on their programming, but proactive decisions based on their experiences. 

However, AI will bring challenges as well. According to the survey, 37 percent of manufacturers believe that training employees will be a significant issue when it comes to deploying AI. The rapid evolution and convergence of multiple disruptive technologies that are part of AI make this a continuous challenge.

There’s another dimension to this reskilling that’s important to consider. With several of the current roles, becoming the domain of smart machines, people skills must evolve to meet the mandates of fluid, totally new, even unforeseen roles that machines cannot fulfill — like deeply understanding product personalization needs or evangelizing adoption of new kinds of consumption. Ultimately, this means embedding “learnability” among employees in a systematic process of lifelong learning. 

Beyond Profitable Business

Smart manufacturers also understand that demonstrating genuine interest in employee well-being will help them be preferred places to work and will attract the best talent. The AI survey revealed in 80 percent of the organizations that have replaced or plan to replace roles with technology will retrain or redeploy those who are displaced. This supports the notion that manufacturers and other businesses see AI as part of remaining competitive and profitable, but recognize that AI will amplify and augment human workers.

With the advancing adoption of AI, manufacturers will automate mundane and routine tasks, and free employees to pursue higher value tasks, develop new ideas and collaborate together in the realm of intelligent machines.

Jeff Kavanaugh is a Senior Partner in the Manufacturing Practice at Infosys Consulting.

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