AICC White Paper (CONT’D FROM PAGE 1)
chine immediately, without the delay of travel time, shop visits, and sometimes even training. This technology has also led to predictive maintenance on machines. Digital twins help manufacturers speed up training and product development processes. With the high volume of new ma- chine installations in the past few years, these technolo- gies have become standardized and will continue to be part of the future. Currently, there are 2 important categories of AI in Man- ufacturing: Machine Learning and Deep Learning. Machine Learning: Tools That Supplement And Super- charge Current Operations And Talent Machine Learning enables computers to learn from data and make predictions or decisions without explicit programming. Automation like Robotics and newer equip- ment deliver efficiencies, but they also deliver a data source that previously has not been cost effective or use- ful to harness. If you collect and connect this data with the right AI tools you get that first layer of intelligence: Aug- mented Intelligence. The tools used to leverage this data and provide results fall under the technical term machine learning. Machine Learning (ML) focuses on the develop- ment of algorithms and models that enable computers to learn from data and make predictions or decisions without explicit programming. The key parameter is unlike every- thing we have today in the box plant because the algo- rithms are not written out by programmers but are learned. CONTINUED ON PAGE 26
Is now the right time? Yes. For 2 reasons: It will not be cost-prohibitive given the value it offers. What this means is that the combination of investing in IoT (which includes sensors and connectivity options) and AI, as well as the decreasing costs and widespread availability of cloud computing resources, has made it much more feasible and affordable for small to medium-sized businesses to adopt and benefit from these technologies. In simpler terms, it's now easier and more cost-effective for smaller operations to use advanced tech like IoT and AI, thanks to the reduced prices and greater accessibility of cloud services. There was a time when servo technology was expensive and unreliable but now it is on every new ma- chine. The second reason to consider is that investing in AI can be compared to saving for retirement. Just as be- ginning your retirement savings early can lead to signifi- cantly larger gains due to compound interest, starting to implement AI technology sooner rather than later can lead to vastly greater advantages as the benefits accumulate over time. This is because all Artificial intelligence models need good-quality data. It’s no secret that over the past 10 years, Artificial Intel- ligence (AI) has brought many innovations like augmented reality (AR) and virtual reality (VR) solutions to the manu- facturing shop floor. VR headsets or smart glasses help manufacturers work with suppliers to troubleshoot a ma-
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24 January 22, 2024
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