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You are here: Home / Archives for Debasmita Mukherjee

Debasmita Mukherjee — New Contributor

Author of the Field Reliability Data Analysis article series. This author's archive lists contributions to articles and episodes.

About Debasmita Mukherjee

Debasmita has used statistical tools and techniques to analyze field data and explore and identify issues, as well as drive root cause investigation. Using automation, she led reliability data analysis at scale to graph performance trends over time.

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.

[Read more…]

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.

[Read more…]

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. 

[Read more…]

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

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