The IndustryWeek Talent Advisory Board offers monthly perspectives from industry leaders on getting ahead in the manufacturing world. This month's question was:
What are the implications for manufacturing technology of artificial intelligence or new technology in general?
Every month, we ask the group a new question about their careers or life experiences. If you have a question for the group, please send it to IndustryWeek Talent Editor Ryan Secard.
AI has already begun to fundamentally change the world of manufacturing. AI models are uniquely capable of quickly parsing through complex, large datasets to identify patterns, trends, and anomalies and harness valuable insights. Shopfloor AI use cases that are taking hold include testing, visual inspection, and predictive failure and maintenance while factory line optimization, anomaly detection, inventory management, and bottleneck prevention show promise.
Effective AI deployments have the power to boost production efficiency, quality, and sustainability and create opportunities for employees to focus on more fulfilling, non-repetitive work, broaden their skillsets by managing new technologies, and deliver greater value to customers.
However, critical considerations for organizations to get the most out of their AI investments include clearly understanding the problem at hand, defining success, prioritizing change management, and securing employee buy-in. For example, by proactively managing the change process, organizations can implement AI deployments seamlessly into existing workflows and think about the different necessary touchpoints to include employees from the beginning. By doing so, organizations can take advantage of AI deployments that drive tangible business outcomes, are embraced by their workforce, and provide maximum value.
— Paul Baldassari, President, Manufacturing and Services, Flex
AI is proving to be a game-changer in manufacturing, particularly in maximizing the two critical factors that always come into play in this industry: resources and time. As customers continue to demand the best quality products with the quickest turnaround possible, AI is helping manufacturers meet—and even exceed—these expectations.
While all industries can benefit from establishing clear guidelines around AI, I see its rise in manufacturing as largely positive. AI is unlocking exciting opportunities to enhance operations, streamline production planning, and create more value for customers. By automating tasks that were once labor-intensive, AI frees up time for employees, empowering them to focus on planning, innovation, and ensuring top-notch quality.
We’re already seeing the positive impact of AI in our manufacturing operations. Our team in Alpharetta, GA is leveraging AI by digitizing reporting processes to streamline supply chain management. Linking data from internal and external sources to a centralized hub through machine learning and robotic process automation, they have eliminated the labor-intensive processes of data mining, reporting, and forecasting. Now the most accurate data is at our employees’ fingertips to enhance production planning and decision-making!
As AI becomes increasingly integrated into the manufacturing industry, there is an opportunity to deliver even greater customer value while setting new standards in efficiency and innovation.
— Tami Wolownik, Head of People & Organization, North America at Siemens Mobility
Artificial Intelligence (AI) is absolutely impacting manufacturing. There are numerous areas where this evolving technology is coming to life, from robotics and automation, software development, digital twins, simulation/process optimization, material flow, data visibility, and more.
Some early examples include training machine vision systems using Deep Learning technologies to reduce implementation time for automated visual inspection stations when compared to traditional vision applications. This allows us to produce a better-quality appliance and understand and resolve new issues in real time for our consumers.
Software products are beginning to include Large Language Model training on manuals and help files, which provides a more intuitive experience for users needing support or questions answered, accelerating learning curves on the factory floor when new processes or equipment are being brought online.
External Large Language Models, rather than traditional web search engines, are becoming the primary source feedback regarding syntax of programming languages during automation software development, a critical enabler for our controls, programmable logic controller, and product functional test equipment engineers.
In the realm of industrial robotics, AI is set to revolutionize the field by enhancing intelligence, efficiency, and adaptability. This includes improvements in flexibility, predictive maintenance, quality inspection, and overall process optimization. Machine Learning promises to enable automated business insights when coupled with information obtained from the factory floor. The ability to see, interpret, and react to information in real time, on the factory floor, allows for a common understanding of the data and rapid problem solving.
— Michael Land, Executive Director, Advanced Manufacturing Engineering, GE Appliances
