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Lucian Boldea, President and CEO of Honeywell Industrial Automation.
The manufacturing industry faces persistent challenges, including a growing skills gap. As experienced workers retire, they take invaluable knowledge with them, potentially creating experience and knowledge gaps that hamper productivity and innovation.
Enter artificial intelligence. AI captures and shares expert knowledge, but humans will remain essential to the manufacturing process. AI should be viewed as complementing and enhancing workers’ roles, improving job quality and autonomy.
By utilizing the best practices below, business leaders can address critical issues and leverage AI to expand human potential and make manufacturing jobs more attractive and fulfilling for the modern workforce.
Capturing Essential Knowledge
The manufacturing industry is faced with the impending retirement of many experienced and highly skilled workers. In fact, U.S. manufacturing is expected to have 2.1 million unfilled jobs by 2030, according to a study by Deloitte and the Manufacturing Institute.
As veteran employees leave the workforce, their wealth of institutional knowledge built over decades—such as detailed understanding of processes, equipment, troubleshooting techniques and best practices—often leaves with them. This “brain drain” of lost expertise and information that is difficult to fully document and preserve can pose a significant risk to operations and productivity.
Manufacturers should deploy AI to mitigate this loss. It can capture the specialized knowledge of seasoned workers through data collection, machine learning models and interactive training systems, then digitalize and distribute this mission-critical information. Manufacturing intelligence will no longer be confined to the minds of a few key employees; it can be broadly shared and persistently maintained.
Enabling Workers To Do More
I’ve found that AI can act as a multiplier that empowers employees and enables them to make more informed decisions. Whether it’s an oil refinery operator or an airline pilot, AI can help optimize a worker’s productivity. Workers won’t be replaced by automation; they’ll instead have AI as an intelligent assistant to enable them to make more informed, safer and more efficient decisions.
Companies that have applied AI in industrial processing plants report a 10% to 15% increase in production. These productivity gains are driven by AI’s ability to enable a reduction of downtime through predictive maintenance and systematically help to remove bottlenecks and sources of inefficiency. AI can also unburden workers from tedious monitoring tasks and free up their time and mental bandwidth to focus on higher-value activities.
Upskilling Employees In Real Time
Companies can use AI to help an organization’s most inexperienced employees, enabling even entry-level plant operators to make more informed decisions.
That’s what AI copilot technology does. It’s designed to provide information on plant operations and provide instructional prompts for personnel as they go about their work. Rather than wade through training manuals, new employees can enjoy quicker, more efficient training.
This allows even recent hires to make informed decisions. Workers can also engage in a meaningful dialogue with AI to ask questions and receive guidance—anywhere, anytime. In large industrial plants like those in the refining and petrochemical industries, this can potentially translate into millions, if not tens of millions, of dollars in benefits associated with better throughput, reliability and human efficiency.
Expanding And Elevating Job Roles
Leaders can leverage AI to impact the manufacturing workforce by introducing new job roles and skill sets. As intelligent systems become more prevalent, there may be a growing demand for professionals who can develop, maintain and integrate AI technologies seamlessly into the manufacturing process.
In addition, there is an increasing need for “hyperintelligence” workers—experienced individuals who can properly configure AI systems to look for useful insights in complex data sets. Even the most advanced AI requires this type of expert human guidance to focus its capabilities. Data analysts are also essential to ensure that the data feeding AI models is valid, relevant and beneficial to the processes being optimized.
There may also be a growing demand for AI governance professionals. These are the human overseers tasked with keeping AI systems operating as intended by monitoring for potential biases or cases where the AI may be exceeding its intended boundaries of operation. The role of governance professionals is to ensure that AI “stays in its lane” and does not inappropriately impact processes in unforeseen ways.
Attracting New Talent
The manufacturing industry is under pressure to replenish its aging workforce. Many younger workers simply don’t see the field as a desirable career path. But the arrival of AI, automation and other advanced technologies may bring an opportunity to rebrand the work and attract digital-native Gen-Z workers who wouldn’t otherwise consider a career in manufacturing.
The recruitment challenge is particularly large in fields like oil and gas, which will need to fill a staggering 1.9 million jobs by 2035. According to the U.S. Bureau of Labor Statistics (BLS), employment in the oil and gas extraction industry has decreased by approximately 7% over the past year. The implementation and use of AI, machine learning, robotics and the latest Industry 4.0 solutions could make this field and others much more appealing to Gen-Z. The lure of working alongside AI assistants, intelligent automation and cutting-edge human-machine interfaces could fill the manufacturing industry with a fresh influx of tech-savvy recruits.
AI is expected to transform manufacturing roles by automating routine and repetitive tasks, freeing workers to focus on higher-value activities that require human creativity, problem-solving and decision-making skills. This shift may enhance job satisfaction and foster a more engaged and motivated workforce. While some initial apprehension is understandable, history shows that technological revolutions have consistently improved workers’ quality of life. There is no reason to believe it will be any different with AI.
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