SCMH 7 18 Data Science and Artificial Intelligence Webinar
Science & Technology
Introduction
Introduction
On a recent free SCMH webinar, the topic of discussion centered around data science and artificial intelligence (AI). Susan Parsons, representing the IAQG, moderated the session, which featured esteemed panelists Franco Curatella, Muhammad Saeed, and Alberto Cesario. The webinar aimed to provide insights into how data science and AI can enhance quality management, showcase real-world application cases, and introduce attendees to relevant guidance material available within the SCMH framework.
Overview of the Webinar
The webinar began with an introduction to the SCMH, pinpointing its location on the IAQG website (iaqg.org). Attendees were informed that the webinar would cover the core guidance on data science and AI, outlining the objectives, benefits, and application of these technologies within quality management. The agenda included discussions on real-world application cases, alongside short video presentations highlighting successful implementations from participating companies, followed by a Q&A segment.
Panelist Introductions
Franco Curatella, representing the Ariane Group, initiated the panel discussion. He shared an overview of the working group focused on data science and AI, detailing the produced materials under three categories: a summary overview, an introduction to data science terminology and methods, and a catalog of real-world applications shared by group participants. Franco emphasized the importance of predicting and preventing non-quality measures to reduce costs and enhance efficiency in organizations.
Following this, Muhammad Saeed from Boeing introduced key concepts of data science and AI, describing it as a blend of art and science, where understanding the domain is crucial for effective data analysis. He highlighted various data science methodologies, emphasizing using both unlabeled and labeled data to derive meaningful insights through predictive analytics, machine learning, and automated systems.
Lastly, Alberto Cesario from Leonardo Helicopters discussed the significance of having trained personnel in quality engineering teams, calling for the integration of data scientists to enhance capabilities in data management and analysis. He also showcased a customer portal designed for improving after-sales service through better data management and quality control.
Real-World Applications
The webinar included real-world examples showcasing the implementation of data science and AI in quality management. Franco Curatella presented a case study on predictive maintenance and quality at the Ariane Group, specifically focusing on the friction steel welding technology, enabling the company to predict non-quality incidents before they occur through extensive data analysis.
Muhammad Saeed highlighted various successful applications of AI in quality control, such as utilizing drones for visual inspections and integrating time series analytics to predict maintenance needs effectively.
Alberto Cesario then demonstrated the value of having quality management systems enhanced with AI capabilities to improve customer service and increase operational efficiency, particularly through managing customer queries and documentation better.
Closing Remarks and Q&A
As the webinar came to a close, the panelists encouraged participants to consider the adoption of data science and AI in their quality management processes. The Q&A session revealed insightful inquiries from attendees, prompting discussions about training opportunities for quality engineering teams, quality controls for AI, and the integration challenges faced by organizations.
Participants praised the session, highlighting the informative presentations and the potential impact that data science and AI could have on their organizations. Attendees were reminded that past webinars are accessible on the SCMH platform for further exploration.
Conclusion
The SCMH webinar on data science and artificial intelligence provided valuable insights into how these technologies can transform quality management practices. With ongoing developments in this field, organizations are encouraged to engage in continuous learning and adoption of these innovative solutions.