Improving worker optimization on the factory floor with artificial intelligence
Artificial intelligence (AI) can be used to enhance worker productivity by gathering information about their work performance and turning it into actionable data.
Artificial Intelligence Insights
- Artificial intelligence (AI) and advanced analytics can be used to make workers better and more productive in their jobs.
- Manufacturers are dealing with a skills gap, which is exacerbated by a training gap. Getting new workers up to speed quickly is a difficult process. AI can gather information about the training processes and tailor that information to help specific workers for their jobs.
Today’s manufacturing landscape is a dynamic mix of workforce challenges, which have been exacerbated due to the COVID-19 pandemic and the resulting Great Resignation. Chris Kuntz, VP of marketing for Augmentir, admits this is a challenge, but companies can still find ways to maximize productivity, he said, in his presentation “Using AI To Unlock the True Potential of Today’s Workforce” at IMTS 2022 in Chicago.
“It’s important to realize the human side of manufacturing and how AI augments the worker rather than replacing them,” Kuntz said.
That’s easier said than done with a major skills gap in manufacturing, which is being made because the tenure rate for a manufacturer has dropped. Before COVID, it was down 20%. It got much worse, Kuntz said, during and after the height of the pandemic.
Kuntz cited a food and beverage manufacturing that was looking to reduce machine downtime. This was made worse because they didn’t have enough maintenance personnel. Production lines would go down, hampering their ability to make the product.
To solve this problem, the company had four goals they wanted to achieve:
- Reduce downtime by relying more on self-guided operations
- Lower the hiring bar so they could hire more people
- Get new workers skilled and productive faster
- Achieve standard work with a highly variable workforce.
Thanks to smart AI implementation and a dedicated plan, the company reduced equipment downtime by 27% and reduced training time by 76% by streamlining and simplifying the program to make it easier for workers to get acclimated.
Smart connected worker solution with AI
Kuntz said the overall goal was about bringing together what a worker has been trained on compared to how they’re doing on the job. With workforce variability, it gets harder because there so many different factors involved. It can be hard meeting safety, quality and production goals. Kuntz said the old way of onboarding and training workers, because they don’t stick around like before, doesn’t work, and thus, the “hire to retire” process, which was not uncommon 30 to 40 years ago, needs to be reimagined.
Digitizing these procedures and bringing them into the modern age is difficult, but AI can help streamline the process and make it easier for old and new workers alike.
“There’s a lot of data and information that comes out of the skills matrix,” Kuntz said. The key is using AI to enhance that data and find the insights on how to make the workers better. It’s about creating a smart connected worker solution, which uses AI to help workers in four ways:
Smarter onboarding and training. Utilize and automate onboarding and training processes to help get workers skilled and operational faster to offset a rapidly churning workforce.
Smart support. Support workers in the flow of work with easy access to curated knowledge and remote expert support. AI-bots also can provide autonomous support.
Smart guidance. Provide personalized guidance to each worker matched to their needs to allow workers of different experience levels to complete work safely and correctly at their personal best productivity.
Smarter upskilling and reskilling. AI-drives insights to decide who has to be reskilled and who should be upskilled. This helps improve productivity and increases engagement.
Kuntz described it later as, “Think of it is overall equipment effectiveness (OEE) for people.”
Advanced analytics and OEE and other advanced metrics are nothing new in the world of business or in everyday lives—think sabermetrics in baseball, which provided a new way of looking at the game and maximizing productivity.
AI can do the same for workers. Kuntz said AI can help many questions such as:
What is the skills inventory of my team in attendance today?
Who can/should perform this work?
Who would benefit the most from targeted retraining?
Where should we focus for process improvement?
What type of training would give us the biggest return?
How many hours of productivity opportunity do we have?
What training materials need improvement?
A solid plan and goal must be in place, but the information is all there and AI can help synthesize and enhance what already exists to create the best possible workforce for a company.
Chris Vavra, web content manager, CFE Media and Technology, firstname.lastname@example.org.
Original content can be found at Control Engineering.