Embracing Digital Transformation and AI in Manufacturing: Insights from OMTEC 2024
Eyelit Technologies, General Manager – MESTEC MES Mark Carleton was invited by ELOS Medtech to participate in a panel debate at this year’s Orthopaedic Manufacturing & Technology Exposition and Conference (OMTEC) in Chicago. This year’s hot topic, “Digital Transformation and the Use of Artificial Intelligence (AI) in Manufacturing,” sparked engaging discussions and valuable insights.
The panel, featuring industry experts Jani Rad, Steve Campbell, Eric Kimberling, and Chris Plaskos, provided a holistic view of the impact of digital transformation across the entire supply chain—from initial manufacture to final patient outcomes. Despite diverse perspectives, several key themes emerged.
Understanding AI’s Role in Manufacturing
The term AI encompasses various technologies, gaining popularity due to advancements in “Generative AI.” This technology facilitates rapid searches through extensive knowledge libraries, extracting and formatting relevant content into human-readable formats. It brings significant productivity efficiencies. Many have experimented with tools like ChatGPT to draft emails or presentations. However, a poll of the audience revealed that routine AI usage in weekly work-life is still limited. This is expected to change, particularly in the software industry, where generative AI is anticipated to draft initial code versions. While some fear job threats, “I believe AI will free developers from mundane tasks, enhancing productivity and innovation.” Says, Mark Carleton, General Manager- MESTEC MES.
Beyond Generative AI: Vector Search and Predictive Analytics
AI encompasses other transformative technologies such as “Vector Search,” which enables rapid comparisons of documents, text, or images. The potential applications are vast. For example, searching a library of non-conformances to quickly find causes and resolutions for previously encountered issues or automatically recognizing defects in visual inspections. This can reduce debates in medical device manufacturing about what constitutes a defect.
Predictive analytics and machine learning represent another AI branch. A common AI application in manufacturing is predictive maintenance. By monitoring vibration signals from assets, machine learning models can predict failures, allowing for preventative rather than reactive maintenance.
AI’s Impact on Supply Chain Productivity
The panel unanimously agreed on AI’s potential to enhance productivity across the supply chain in various ways, emphasizing that AI is more than a passing trend. However, they were cautious about organizational readiness to adopt the latest AI technology. AI and machine learning discussions remain academic if quality data is still recorded on paper. Predictive analytics require data to analyze. Therefore, leveraging AI benefits in the mentioned use cases necessitates robust data collection.
Laying the Foundations for AI Adoption
The journey toward an AI-enabled manufacturing utopia begins with foundational steps often overlooked in marketing materials. Data preparation, digital data collection, and open data sharing are essential not only for utilizing AI but also as the bedrock for broader digital transformation.
If you are ready to embark on the first steps of this transformative journey in manufacturing, please get in touch with us.
// Stay tuned for more insights and updates on how digital transformation and AI can revolutionize your manufacturing processes. #DigitalTransformation #AIinManufacturing #OMTEC2024 #SmartManufacturing #Industry40
