The growth of AI models will continue to affect the packaging industry in a multitude of ways in the coming years, according to a new report from PMMI Business Intelligence entitled, “The AI Advantage in Equipment: Boosting Performance and Bridging Skills Gaps.” Business Intelligence researchers conducted a series of interviews with experts across packaging and processing to find current attitudes and uses of AI within the industry.
The key takeaway from these conversations, according to PMMI, is that AI is more of an evolution than a revolution, with human intervention still required to make final decisions. Researchers found three main impacts that currently available AI solutions will have on the packaging industry.
Increased Staff Productivity
One key advantage for a company implementing AI is that it enables staff to be much more efficient and productive with their time. The AI technology with the most potential to improve this metric is an AI assistant. Time-consuming tasks like data entry and coding can now be completed with the help of these assistants. This increases the speed at which projects can be completed, freeing up additional time for staff members to focus on other valuable tasks.
Digital twin simulations are another example of this. It’s still possible to find solutions to optimize both machine and process performances through traditional methods, but utilizing AI technologies does the same task in a fraction of the time.
The virtual environment allows AI to create and test many different iterations of items, like a specific component of a machine. This greatly reduces development time and streamlines the development process.
Increased Machine Performance And OEE
Another major impact of AI technology is increasing both machine performance and the overall equipment effectiveness (OEE) of automated technologies. Integrating AI into machine vision systems improves decision-making success rates in processes like quality inspection and allows for a wider range of complex tasks to be completed. Digital twin simulations can be utilized by machine builders to optimize key machine metrics, such as throughput, which can improve machine performance. Predictive maintenance reduces the frequency of machine downtime. When combined with improved training from connected worker platforms, this can have a significant impact on a machine’s OEE.
Mitigating Skills Gaps And Labor Issues
The final significant impact AI will have on the packaging industry, according to feedback received from PMMI, is in mitigating skills gaps within the industry. The optimized training provided in connected worker platforms can ensure that all employees are receiving the highest quality training available to bridge skills gaps.
AI assistants and generative AI predictive maintenance solutions allow users to ask questions regarding issues they are having on machines, further enabling staff to upskill independently and reduce the risk of human error. AI assistants can also ensure good practice is upheld during coding by improving syntax and comments.
Due to the nature of AI models, the longer these technologies are used and the more data they process, the better the outputs become. Integrating AI technologies into a company is not a one-time improvement like previous automation technologies; continuous improvement is evident in important metrics.
