F102: How to Improve Your Production with Detailed Data

OEE vs. Detailed Data: How to Improve Your Production Metrics
OEE is a common production metric that combines performance, availability, and quality. However, OEE does not reveal the root causes of inefficiencies and requires further manual analysis. With detailed data from machines, we can gain more insights into the production process, such as the run time, the alarms, and the program performance. This can help us identify and address the specific issues that affect productivity, quality, and reliability. In this presentation, you will see how detailed data coming directly from the machines can supercharge your improvement efforts by providing answers that OEE can’t.
Casey Greer – Amada America

Advancements in Welding Data Collection: Data Collection Methods, Part Traceability, and Machine Learning
Join our discussion on welding data monitoring, where we explore practical data collection methods, discuss the significance of part traceability, and examine how automated machine learning enhances anomaly detection in welding. Our focus will be on the practicality of data collection and the reliability of data models. We will present specific data tied to a customer use-case to demonstrate how machine learning can be used to identify weld anomalies. By attending this discussion, you will discover how these elements work together to improve your bottom line.
Brian Meess – The Lincoln Electric Company and Emily Stuart – Lincoln Electric