After months of lockdown and social distancing due to the pandemic, consumers have been forced to shop differently — reprioritizing what is essential and swapping the checkout line for online shopping more than ever before.
These changing consumer expectations are altering packaging and processing industry priorities. Manufacturers must find ways to increase efficiencies to meet demand and stay competitive in the marketplace. In order to do this, brand owners recognize the urgent need to increase connectivity and broaden the use of automation in their operations, according to the Automation Timeline: The Drive Toward 4.0 Connectivity in Packaging and Processing white paper from PMMI, The Association for Packaging and Processing Technologies.
When it comes to manufacturing, the industrial internet of things (IIoT) is one of the most powerful systems that consumer-packaged goods (CPG) companies should consider putting into place. The ability to connect machines, materials, computers, order processing and operational technology keeps the entire manufacturing process reviewable, streamlined and operating with the power of automation. As traditional manufacturing evolves to meet the changing demands, the implementation of Industry 4.0 will be a vital solution that helps manufacturers remain competitive.
According to PMMI’s Automation Timeline white paper, a comprehensive IIoT strategy is lacking at most manufacturers. In order to implement a viable 4.0 strategy, individual machines within an operation need to be integration-ready, meaning they are prepared for and designed to easily link up with a larger IIoT network. In many ways, IIoT integration and data acquisition are the keystones to expanding automation, enabling deployment of many other advanced automation strategies.
One of the challenges manufacturers face with implementing industry 4.0 technology is finding and retaining the needed skilled labor to pursue, achieve and maintain their automation goals. OEMs and suppliers can help their customers overcome labor shortages by employing the opposite strategy: making the functionality of their equipment significantly more complex through advanced automation. Specifically, OEMs and suppliers can harness the power of artificial intelligence (AI) and machine learning to mitigate manufacturers’ labor challenges. These automation tools can analyze production data, allowing an operation to be streamlined from individual movement/processes all the way up to the entire integrated production strategy. By utilizing automation to identify and execute improvements, manufacturers are able to take optimization responsibilities out of the hands of individual employees, freeing up labor that can be deployed elsewhere.
AI and machine learning are technologies that, at first glance, may seem expensive investments that are better suited for the future, but they are increasingly affordable and available solutions that can bring measurable efficiencies to smart manufacturing.
One example cited in the PMMI white paper is using AI and machine learning in tandem to improve operating efficiencies. Sensors are deployed to key areas of the operation to gather continuous, real-time data on efficiency, which can then be analyzed by an AI program to identify potential tweaks and adjustments to improve the overall process. This technology has proven to be more efficient than human analysis for applications ranging from the movement of patterns of robots on the line to the rotational speed of turbines to optimize energy usage.
One study released by Accenture and Frontier Economics found that by 2035, AI-empowered technology could increase labor productivity by up to 40%, creating an additional $3.8 trillion in direct value-added (DVA) to the manufacturing sector.
Another area of automation and machine connectivity forecasted to grow by manufacturers is the use of predictive analytics. Predictive analytics allows manufacturers to monitor machine conditions and identify future problems such as failures or malfunctions. Operators can then address issues before an emergency shutdown and downtime are necessary.
Like the deployment of AI, predictive analytics relies heavily on a network of integrated sensors that continuously monitor and record production data. Unlike AI, however, these sensors are more attuned to the performance of individual machines on the line, keeping track of their wear and tear to identify when maintenance will be required. This allows manufacturers to proactively plan their machine maintenance.
There is significant opportunity to expand IIoT and integration-ready machines at CPGs, who have identified only a small portion of their plant floor as fully IIoT enabled. According to the PMMI white paper, while this portion continues to rise (going from 15% in 2017 to 30% in 2020), there is still a significant gap to be met when it comes to connectivity and IIoT capability.
New technologies, solutions and education addressing the changing landscape of packaging and processing machinery connectivity will be on display at PACK EXPO Las Vegas co-located with Healthcare Packaging EXPO 2021 (Sept. 27-29, Las Vegas Convention Center) where the packaging and processing community will reunite. With over 1500 exhibitors, no other event in 2021 will bring together a more comprehensive gathering of suppliers offering new products, technologies and solutions. It’s where executives and plant managers, engineers, brand managers and packaging designers come to see machinery in action, connect with suppliers, network and gain the latest perspective on a plethora of industries in over 40 vertical markets. The two shows will bring attendees and suppliers of packaging equipment and materials together.
To learn more about the advanced packaging solutions that will be on display as well as the educational, networking opportunities and the virtual component of the show, and to register, visit www.packexpolasvegas.com.
Report Abusive Comment