Reliability Growth Curve Plotting using Excel Spreadsheet Guidebook

Reliability Growth Plotting Guidebook using Excel Spreadsheet to Track Reliability Trends

Equipment Reliability Growth Model Using An Excel Spreadsheet Is Explained In This Reliability Growth Plotting Guidebook

A Low Cost Reliability Growth Plot Guidebook That Shows You How To Do Reliability Growth Analysis And Make A Simply Reliability Growth Model In A MS Excel Spreadsheet

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Description

Reliability Growth Modelling in an EXCEL Spreadsheet Guidebook Shows How to Use CROW/AMSAA Method to Trend Reliability

The reliability growth analysis plotting guidebook takes you through drawing a reliability growth model using a MS Excel spreadsheet. You are stepped through the development of the reliability growth model, and the reliability growth plot that results, so you can learn to monitor the plant and equipment reliability improvement.

When you want to know if your reliability improvement project is paying-off you can use a Crow/AMSAA reliability trend plot to do a reliability growth analysis of how well your reliability improvement efforts are going. The detailed instructions provided in the reliability growth analysis guidebook explain how to create a reliability growth plot in an Microsoft Excel spreadsheet.

The reliability growth analysis guidebook walks you through setting-up reliability monitoring charts in MS Excel, converting linear axes to Log-Log axes, showing the trend lines for each phase of life, and calculating the trend line slopes (also known as their beta value). You will produce a reliability growth plot similar to the one below for a steam boiler soot blower. In which the reliability growth analysis shows that three years earlier it was suffering dramatically increasing failures (the slope is greater than 1), but after reliability improvement it is now vastly more reliable (the slope is now 0.83, meaning reliability is constantly improving compared to what it was).

The effects of any reliability improvement initiatives (or the lack of reliability improvement initiatives) are seen in the slope of the graph. In the above reliability growth plot, beta values greater than 1 mean reliability was worsening during the period (they were experiencing failures more often), and where it is less than 1 it means reliability was improving from whatever was done to reduce the number of failures. Clearly the reliability improvement efforts of the last three years were working.

These reliability improvement plots apply to any situation since they measure the rate of failure happening and do not reflect what is suffering the failures. You can use them to measure safety performance, quality system non-compliance, or any process, system or thing where a failure is identifiable. A Crow/AMSAA or Duane plot makes an excellent reliability key performance indicator (KPI). With such a plot you can clearly see if your reliability improvement effort is paying off, or if you need to do something else to fix your problems.

Reliability Growth Charting with Excel Spreadsheet Guidebook (Uses an MS Excel Spreadsheet for modelling reliability growth from past event history)

You can read the introductory pages to the MS Excel reliability improvement graph plotting guidebook by clicking on the link below. With the guidebook you also receive for free three (3) white papers explaining the Duane-Crow/AMSAA method of tracking reliability growth.

View a PDF document showing the first four pages of the reliability improvement plotting guidebook:
Reliability Growth Plotting in Excel Guidebook

Disclaimer

Because it is unknowable how applications will be used, their Developer and Lifetime Reliability Solutions take no responsibility for correctly modelling the situation, or for the outcomes of using an application.

It is recommended that you understand well the theory behind the application you use, so you can confidently judge whether it applies to the situation under investigation and if its output is sufficiently accurate in the circumstances. Remember the warning that applies to all modelling methods — ‘garbage in, garbage out’.

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