The first reason is the advancement of artificial intelligence (AI) technology, which is a driver for “smart factory to come to life,” she said. The second reason is the maturity of the technology and reduced costs associated with adopting it, she said. AI-enabled smart factory technology is no longer limited to pilot programs but instead is being adopted “across the ecosystem.”
“The big driver that has changed in the last couple of years is, again, I would say the maturity of the technology and the cost and access of AI across the board,” Kaur said.
“We used to have platforms that were not talking to each other,” Kaur said. “The data was not accessible. The data was not moving across the systems.”
However, refinements and increased availability of AI have allowed manufacturers to integrate information between systems and reach the next level of process efficiency, she said.
Smart manufacturing is moving beyond connecting machines and collecting data toward using AI to interpret data across the entire manufacturing and supply chain operation. For plastics processors, Kaur sees potential applications ranging from process optimization and equipment maintenance to production planning, material purchasing, inventory management and customer fulfillment.
She said AI now allows manufacturers to answer questions such as:
- How much should I produce?
- How much raw material should I buy?
- How much inventory should I keep?
- Why did this batch come out wrong?
- How should market demand affect my production?
In addition, as the quality of artificial intelligence evolves, manufacturers are moving closer to lights-out operations, she said.
“We are getting very, very close to autonomous operations because the system is able to understand, collect the data and understand what is going on,” Kaur said. “It then uses the AI to start making decisions and start taking actions in the system … We are finally working toward an intelligent and autonomous plant of the future.”
While technology is advancing rapidly and adoption is growing, it’s still not in use everywhere. The size of a manufacturing operation is a major factor in determining whether a company is adopting the technology.
“What I’m seeing, it’s in the early stages, and the companies that have deeper pockets or are at least a decent size, they are the ones who are at the forefront of adoption of these technologies,” Kaur said.
However, smaller manufacturers don’t have to be left behind. They can start the journey to AI-driven smart manufacturing without investing in all new equipment. Smaller manufacturers can install sensors on existing equipment and select processes to gather data and work with a third-party company to provide AI services, she said.
Contact:
Deloitte, deloitte.com
