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You are here: Home / Archives for Articles / on Product Reliability / Field Reliability Data Analysis

Field Reliability Data Analysis

In this article series, we will review stories and examples to highlight the importance of product field data and how it can be used to drive business decisions. We will learn the benefits and when to use different analyses to detect issues using data exploration tools such as histograms, box plots, life distribution, and Weibull analysis. We will also cover statistical techniques for root cause investigation, such as Regression Analysis and Decision Tree. Fundamentals of reliability modeling techniques such as Reliability Block Diagrams, Fault Tree Analysis, and Monte Carlo Analysis will also be covered.

by Debasmita Mukherjee 1 Comment

Reliability Block Diagram Fundamentals

Reliability Block Diagram Fundamentals

Basic Definitions

  • Reliability: Ability to provide continuous and stable system/component function under defined operating conditions without failure(s).
  • Mean Time Between Failures (MTBF): Average expected time interval between failures. Often a measure of reliability.
    • Failure Rate is the expected no. of failures over a period of time. MTBF is the inverse of failure rate.
  • Availability: Percentage of time a system or component can perform its intended function without failure.   
    • Key aspects involve individual component reliability, system architecture, redundancy, and implementation of control strategies to ensure uninterrupted service. 
    • Availability = Uptime/(Total Operation Time) = MTBF/(MTBF+MTTR), MTTR is a measure of time to repair the system/component
    • For example, 99.999% (5-9’s of availability) -> 5 min downtime in one year
  • Reliability Block Diagram: Reliability Block Diagram (RBD) is a graphical representation used to model reliability in complex systems. Illustrates interconnections between various components or subsystems within a system.
[Read more…]

Filed Under: Articles, Field Reliability Data Analysis, on Product Reliability

by Debasmita Mukherjee Leave a Comment

One-sample t-test

One-sample t-test

A one-sample t-test is a statistical test to determine if the sample mean differs significantly from a known or hypothesized population mean (expected value). It is commonly used when we have a single sample and want to compare its average to an expected value.

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Filed Under: Articles, Field Reliability Data Analysis, on Product Reliability

by Debasmita Mukherjee Leave a Comment

Normal Distribution in Reliability Analysis

Normal Distribution in Reliability Analysis

Normal distribution is most common in real life scenarios be it modeling any reliability performance parameter at a specific time. Central Limit Theorem (CLT) shows why normal distribution occurs so often.

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Filed Under: Articles, Field Reliability Data Analysis, on Product Reliability Tagged With: Statistics distributions and functions

by Debasmita Mukherjee Leave a Comment

Understanding Data Distribution in Reliability Analysis

Understanding Data Distribution in Reliability Analysis

Having a knowledge of how the data is distributed is critical to model failure times and life in reliability analysis. Every distribution is unique and suitable for different types of reliability data. 

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Filed Under: Articles, Field Reliability Data Analysis, on Product Reliability Tagged With: Statistics distributions and functions

by Debasmita Mukherjee Leave a Comment

Data Storytelling Using Histogram

Data Storytelling Using Histogram

In the current century, data is ubiquitous but how to make use of it to drive product decisions can take time and effort. Data visualization is a useful technique to identify patterns in a dataset and derive exploratory statistics to analyze trends.

[Read more…]

Filed Under: Articles, Field Reliability Data Analysis, on Product Reliability

The Field Reliability Data Analysis logo Photo of Debasmita MukherjeeArticles by Debasmita Mukherjee

in the Field Reliability Data Analysis article series

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