How digital transformation can help process manufacturers secure the next generation of talent

March 30, 2020

The manufacturing and process industries are currently struggling to attract newer employees. Competing with the media-darling tech companies and facing a regular drum beat of negative publicity over sustainability issues that is affecting their public images, the manufacturing, energy and chemical industries are having a difficult time replacing the more experienced workers that will be retiring in ever greater numbers.

Young people are simply not as inclined to work in manufacturing as they are in flashier industries. The National Association of Manufacturers (NAM) has taken notice, having just last month pushed out a campaign to boost manufacturing’s “workforce of tomorrow.” NAM’s “Creators Wanted” national tour aims to secure the interest of more students in taking manufacturing career paths, increasing enrollment in trade schools as well as apprenticeships.

While initiatives like NAM’s are invaluable to positioning manufacturing as an industry where one can build a rewarding career, the current wave of digital transformation initiatives can play an equally important role.

Making manufacturing roles more interesting through AI

Artificial intelligence (AI) is, no doubt, one of the hottest technology topics of the last few years. While the term is sometimes applied too generously to describe certain technologies, that is far from the case in the manufacturing sector. In manufacturing, AI is now shaping up to become a critical piece of the tech stack, helping companies and their workers make better decisions by offering them previously unattainable insights and expert, prescriptive suggestions.

One of the challenging aspects to working in manufacturing in the past was the general lack of insight into operations and performance. This was true at both the equipment and unit operating levels as they relate to the rest of the asset, group of assets or even the overall supply chain. With limited insights into the overall implications of data or events, it was difficult to make well-informed decisions, foresee unanticipated consequences or drive maximum efficiencies.

Fast-forward to tomorrow’s AI-enabled landscape, and it is leveraging data and pattern recognition to uncover deep insights that paint a better picture for the overall health of a plant or factory environment, the knowledge of which gives workers the ability to make more informed decisions, or even to automate functions that make the environment safer and more productive. For example, AI enables predictive maintenance, predicting potential equipment breakdown weeks in advance of it occurring – when workers have this level of insight, they can adjust accordingly and in advance, instead of having to deal with emergency situations. It makes industrial work safer and is less likely to disrupt non-work time.  It also helps to make these workers feel more in control and reduces many of the tedious elements that make industrial work more frustrating and less satisfying.

Putting advanced technologies in the reach of workers immediately changes the nature of the work they do. For example, AI can help manufacturers automate certain repetitive tasks that then free up workers to undertake more important, gratifying and strategic initiatives. With the addition of new technical capabilities enabled through digital transformation, manufacturing doesn’t seem like such an “old” industry anymore. Students and young workers alike need to be made aware of the fascinating technology changing the industrial landscape.

Going “green” with operational technologies

One of the defining characteristics of next generation workers is their concern for the environment and emphasis on sustainability. However, as sustainability continues to be top of mind, globally, industrial companies continue get the brunt of public backlash, especially when it comes to energy, solid waste and emissions.

However, new technologies are enabling greener operations across the manufacturing world. From capturing data that can help plants use less energy to eliminating poor-quality end-product that ends up as waste, and the ability to re-engineer materials to be more readily recyclable technology is powering a more sustainable future for manufacturing across almost every dimension.

AI also has a play on the sustainability front, again on the predictive maintenance side. By predicting issues that crop up well before they become a problem, AI-enabled predictive maintenance gives workers a chance to proactively reduce the chance of a major incident that could result in unplanned emissions or releases of hazardous materials.

As manufacturing companies inevitably move towards more sustainable operations, and have an increasingly strategic role in solving the energy and environmental issues, it should become an increasingly attractive sector for employment. 

Ultimately, technology isn’t the only driving force the industry needs to secure talent, but it is a key factor in reshaping general sentiment around manufacturing careers. As innovations continue to surface and the industry leverages technology for social good, the manufacturing field will become more enticing to new talent. However, it is critical that industrial companies work to educate society on the impact the industry has on our quality of life and our sustainable future. 

Paul Donnelly is EPC Industry Marketing Director at AspenTech        

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