Why AI Is Manufacturing's Future, But People Are Still Needed

Tags: IIoT, manufacturing

The manufacturing industry is experiencing a growing talent shortage. Data from Deloitte shows that by 2025 the manufacturing skills gap will widen, creating the need for 3.4 million skilled workers, with 2 million of those roles going unfulfilled. Driving this void will be the 2.7 million workers who will retire or leave the industry by 2025, in addition to the roughly 700,000 jobs that will be created by growth within the industry.

Misperception: AI and Automation Will Result in Fewer Jobs

There still exists a widespread misperception that automation and robots will put manufacturing jobs at risk. This is not the case. Human beings will always be a necessary part of the manufacturing process. As facilities continue to evolve and connect more of their assets, people will be needed to digest the vast amounts of data generated from the floor so they can build things faster, better and cheaper. In order for them to do this, that data will need to be converted into information that is digestible by a person. Artificial intelligence (AI) can help with that.

AI can convert large amounts of raw data into information that a human can read and interpret. Without it, people would have to learn how to gather data from multiple database systems, connect them together, know what features to investigate, extract them manually using spreadsheets and then interpret the results. This process would be cumbersome, tedious and very error-prone. By the time the data was prepared for analysis, they would have already run out of time and patience to perform the analysis. With the help of AI, these individuals can spend their time drawing useful intelligence from that data and putting it into action, instead of spending their time manually crunching numbers.

To further dispel the notion of AI and automation taking jobs away from people, recent research from AT Kearney and Drishti reported that 72 percent of manufacturing jobs are still performed by people, and those same people actually drive three times more value than their machine counterparts. Even with more parts of the manufacturing process becoming automated, no machine will ever be able to replace human judgement and intuition.

As consistent with industrial revolutions of the past, innovations in technology always generate new positions. A PwC report found that robotics and AI will produce a net gain of 200,000 jobs in the United Kingdom by 2037. AI, machine learning and automation create jobs because of the specialized skill sets that are required to support and maintain them. After machines start generating troves of data, software is needed to analyze that data and convert it into human-readable information. In order to leverage this information, we still need humans to use it in a meaningful way and take relevant action.

Filling a Void

Crucial to filling these roles will be attracting talent from younger generations. While this is possible, the job profiles that will be enticing to them will be different than the jobs currently available on the factory floor. The younger workforce, being products of their environment, have grown accustomed to getting everything on-demand, including access to information. This holds true as they enter the workforce. Therefore, digitizing the manufacturing business is a strong first step.

Younger generations are showing an increased interest in science and engineering careers. According to the National Science Foundation, roughly 30 percent of bachelor's degrees earned in 2012 were in science and engineering majors. Additionally, 58 percent of doctorates awarded were also in those fields.

As more students demonstrate an interest in science and engineering, pursuing careers in advanced technologies is a logical progression. AI and machine learning will continue to mature, and with them, we will begin to see AI become a more mainstream component of technology-focused college curricula and training programs.

AI Is a Key Component to Manufacturing's Future

The volume of data generated within manufacturing is immense, but there is little point in gathering it all if it will not be used to gain information. For example, it is paramount that facilities know how their machines are operating, if they’re suddenly consuming too much power, or if they’re headed toward a malfunction. Proactively noticing indicators, such as temperature and pressure, and acting on them can prevent costly downtime.

Unfortunately, there is simply too much data for any person or team of people to analyze, which again demonstrates the need for AI and machine learning to work with humans. These technologies will empower them, not replace them. AI and machine learning were made to analyze troughs of information, identify the trends within them and enable business leaders to make more informed decisions faster.

Manufacturers are always looking for ways to improve margins. The information generated by AI is key to operating a leaner facility and addressing potential concerns proactively. The longer a condition persists, such as a machine running at suboptimal capacity, the more money a manufacturer flushes away. AI is already helping organizations stay ahead of their assets’ performance and impact their bottom line. This trend will continue. It will also help create more jobs that will attract the next generation of talent, which is keen to work with the latest technologies.

As the industry continues to change, the roles supporting it will change as well. The future workforce will not just focus on keeping machines running but will learn from the data that’s being generated. This will enable them to make better decisions for their company.

About the Author

Prateek Joshi is the founder and CEO of Plutoshift, which provides a performance monitoring software solution to the process industry, including water, food, beverage and chemicals. Joshi is an artificial intelligence researcher, the author of eight published books and a TEDx speaker. He has been featured on Forbes 30 Under 30, CNBC, TechCrunch and more.

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