The Mantua Group

Simple Black and White Asset Management, Reliability Expertise, and Maintenance Execution Perfection.

Insights

One Size Fits All – or Not

Discover why one size fits all approaches often fail to deliver. In this episode, I speak with Philip Sage about organizations’ challenges with recording failure data and making the most of it, how this affects their ability to make data-driven decisions, and their inability to apply an Asset Management framework specific to their risk profile.

If you want to learn more about creating an Asset Management framework tailored to your needs reach out to Philip Sage through LinkedIn.

Getting it Right

Join Philip and Fred as they discuss the need to purchase, install, and maintain equipment with precision.
Topics include:

  • A mindset to get it right and enjoy the benefits
  • Alignment as an example
  • Rotating equipment benefits significantly with ‘getting it right’ attention to detail.

Enjoy an episode of Speaking of Reliability. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.

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Competing Risks or Not

Join Philip and Fred as they discuss the difference in data analysis and results when the dataset does or does not have competing risks of failure.
Topics include:

  • What are competing risks?
  • The extreme value family of distributions.
  • Does your software just assume competing risks?

Enjoy an episode of Speaking of Reliability. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.

Play

Podcast: Play in new window | Download

Industry Research by The Mantua Group

UTILITY INSIGHTS

January Edition – Bridging Qualitative and Quantitative Research in Asset Management

Feature Article: A Mixed-Methods Approach to Asset Performance

Background

Modeling asset performance is essential for ensuring reliability and efficiency in the electrical utility sector. However, the early retirement of assets, informed by qualitative health indices like dissolved gas analysis (DGA), introduces informative censoring. This challenge limits the reliability of quantitative service life models, impacting decision-making and resource optimization.

The Research

This study develops a mixed-methods framework that integrates qualitative health assessments with quantitative modeling to address these challenges. The research examines how qualitative health indices influence early retirement decisions and their effects on statistical evaluations of asset service life.

  • Quantitative Analysis: Evaluates right-censored service life data to enhance modeling accuracy.
  • Qualitative Insights: Investigates DGA-derived health indices, categorizing assets into states like “Good” or “Faulty.”
  • Methodology Adaptation: Refines traditional qualitative approaches to suit industry needs, prioritizing scientific measurements over social methods.

Impact

This framework reduces prediction errors, enhancing asset management and resource allocation. The study’s findings support improved reliability analysis and operational strategies while offering a scalable model for integrating qualitative and quantitative approaches across industries.

Learn More
Explore more industry innovations or contact us at https://mantua.group/contact/