Cost-Optimized Reliability Test Planning and Decision-Making Through Bayesian Methods and Leveraging Prior Knowledge

Charles Recchia
Charles H Recchia, MBA, PhD has more than twenty-five years of product development, technical team management, and fundamental research experience with a special focus on reliability statistics of complex systems. He earned his doctorate in Solid-State Physics from The Ohio State University, and a Master of Business Administration degree from Babson College. Dr. Recchia acquired in-depth reliabili...read more



Details

When planning for and interpreting reliability datasets proper application of Bayesian statistics leads to improved decision-making, resource utilization and allows for rigorous treatment of prior knowledge to optimize overall reliability program costs and increase return on investment. In this webinar, we build upon the foundation established in our previous intro-level presentation and provide specific examples of reduced sample sizes enabled by Bayesian methods. We also describe real-world scenarios of improved decision-making during comparative reliability analyses using proper statistical perspectives on relative failure rates between systems.

- Login to view the video -



Slideshow



Interested in Membership?

Take charge of your career and education. Join us today and get access to a wealth of webinars covering cutting edge topics important in reliability engineering today!

Find out more
Webinar Categories
Previous Webinars
  • My data is not complete enough for a Weibull plot, what can I do now?
    December 8, 2016
    View Webinar
  • Reliably Solving Intractable Problems
    April 10, 2014
    View Webinar
Networking

Provide a global forum for networking among practitioners of reliability engineering, management and related topics,

Growth

Facilitate growth and development of division members,

Provide Resources

Promote reliability engineering principles and serve as a technical resource on reliability engineering for ASQ, standards agencies, industry, government, academia and related disciplines

Training

Sponsor, present and promote reliability, maintainability, and related training materials for courses, symposia, and conferences.

27