Webinar Replay

Using Data Science to Eliminate Your Fear of Bad Data for Predictive Asset Management

Pinnacle, August 25, 2023

Webinar Overview

In today's industrial landscape, predicting asset health is a fundamental priority, achieved through formula-driven methodologies proven to be highly effective with good data. The real challenge emerges when you are confronted with seemingly bad data. We are all familiar with the term “garbage in, garbage out,” but how we distinguish good from bad is traditionally challenging. Manual scrutiny of data by humans, while invaluable, is often hindered by time constraints, making it impractical for comprehensive analysis. To address this, you can embrace data science to help prioritize human focus, offload mundane tasks, and ensure effective resource allocation.

Inspectioneering teams up with Pinnacle for our webinar, "Using Data Science to Eliminate Your Fear of Bad Data for Predictive Asset Management." During this webinar, we address the challenge of extracting true value from your data and explore how integrating data science methodologies can transform this process and avoid dismissing valuable insights. We will once again be joined by Dr. Andrew Waters and Kevin Birkby who will showcase several compelling case studies and discuss a straightforward approach to building trust in your data by leveraging data science. Participants will gain an understanding of how to perform a data health assessment and learn how to incorporate data science into their reliability resource toolkit to enhance predictive asset management strategies, eliminate manual efforts, and unlock the full potential of data-driven decision-making.

About the Speakers

Dr. Andrew Waters, Director - Data Science at Pinnacle focuses on developing data-driven algorithms to enhance a variety of reliability and maintenance applications. He specializes in utilizing machine learning methods to improve and augment human decision-making and has utilized these skills across a diverse set of industries. Dr. Waters has a PhD in Electrical and Computer Engineering from Rice University and is the author of over 20 publications in the areas of signal processing, machine learning, and Bayesian statistical methods. His research interests include sparse signal recovery, natural language processing, convex optimization, and non-parametric statistics.

Kevin Birkby, Partner at Pinnacle is a senior member of Pinnacle’s Business Development Group. Kevin Birkby collaborates with current and prospective clients to help them use data to drive better decision-making and become more reliable for less cost. In his 12 years at Pinnacle, he has worked on and managed teams from 1 to over 100 people, all with the goal of driving value for customers by implementing, improving, and sustaining industry-leading reliability programs. Before Pinnacle, Kevin worked in manufacturing and air pollution control for 12 years. He now focuses most of his time on being a mediocre performer at home under the management of his wife and twins.

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