AICC White Paper (CONT’D FROM PAGE 24)
Systems like these can significantly improve both pro- ductivity and reliability. For example, an ML system can bring to the attention of maintenance and operations the need to replace specific wear items (predictive main- tenance) and, given authority, even order the part auto- matically so you are not fighting lead times. We all know how critical the feeder transmission is on a traditional ma- chine. With the right sensors and the application of ma- chine learning, a system can predict the transmission fail- ure weeks in advance - giving the operations team ample time to plan downtime and proactively change it. To be fair, there was a time when experienced and skillful mainte- nance techs could do the same based on their knowledge. But that is a hard skill to find today, and machinery has also changed significantly in the past decade making some of that knowledge obsolete. Let’s take the example of machine learning models de- ployed for machine reliability. The power of AI is that it is not making this recommendation based on a set rule but rather from a learned understanding of the typical use of the machine, the type of orders you're running, the actual sensor feedback and historical failures. It’s like having that hard-to-find machine maintenance expert make recom- mendations. True AI learns without the need for added en- gineering as long as it’s given input and enough resources (computing power), it will learn from its mistakes quickly. Similarly, it can suggest (like an experienced operator) how best to run a certain order to maximize output and quality. This is where the augmented portion is truly transforma- tional for box plants. With systems like this there can be a 20 percent or more increase in OEE, 30 percent or more in quality, with 30 percent or so decrease in overall costs. That is the impact this technology has had in early adopt- ers in other industries. (reference, www2.deloitte.com) Box plant general operations is another area where AI tools can have a profound impact. “AI can best be implemented from the inside out. As a manufacturer, you want to know what is happening in the plant. You may want to know the top order, the shipping day, machine problems. And you want this information without having to create reports manually. With the ability to do this all through AI, you can increase work efficiency by as much as 40 percent. Training is more effective by up to 54 percent. You can see what is happening in Design, on the CAD table, and looking at measurements such as ‘how do I get 10 boxes on a tray, and x number of trays in a truck,’ and more. AI facilitates a quicker, more accurate rate of knowing what is happening in your plant 24 hours a day. Education and training, office support, and production work is where AI is really going to help. Start generally, not specifically. If you don’t have the support in place right now, bring in experts to help implement customer service, production, and training. Focus on real world situations,” said Greg Tucker, Chairman and CEO of Bay Cities. CONTINUED ON PAGE 28
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January 22, 2024
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