Measurement and analysis drives initiative, innovation, development, lateral thinking. Statistical tools help in analyzing measurements in many ways.
Maintenance relevant Statistical Tools
- Failure Rate Percent Per Year (FRPCPY)
- Bench Marking
- ABC Analysis
- Pareto chart
- Bath Tub
- Statistical Analysis ( Mean, Mode, Median and Standard Deviation )
Failure Rate Percent Per Year (FRPCPY)
This is a compilation of data on a uniform base of 100 and for a period of 12 months. This is very commonly used in Indian Railways to compare the performance of same item maintained at many locations and over a period. Para 2.8 of the book titled ‘Electrical Fire and Failure’ written by Mr. A A Hattangadi describes it as follows
- FRPCPY = (No. Of failures * 100*12) /Population*Period in months
- This formula provides uniformity in comparing the data of different units, in a different application, of different make etc.
- RFPCPY data are compiled by RDSO of different unit over the common period and is a very important tool to identify the problem which can conveniently be solved.
- FRPCPY data of different units shall be examined to formulate strategies for the future.
|Sl No.||No. of failures||Population||Period(months)||FRPCPY|
Benchmarking is the process of measuring performance parameters, cost, services, and processes against those of organizations known to be leaders in one or more aspects of their operations. Efficiency and Research Directorate of Railway Board has issued benchmarking data on manpower per unit output for all the units of Indian Railways.
- Benchmarking provides necessary insights to help you understand how your organization compares to similar organizations, even if they are in a different business or have a different group of customers.
- Reasons for excellent and average performance is generally not supported by analytical tool and more reasoned subjectively.
- Better than last year is commonly followed as benchmarking tools
Initially this tool was designed for material management technique categorizing as:
- A Items: Very tight control
- B items: Medium tight Control
- C Items: Normal control
This analysis is very helpful in prioritization of problem with respect to cost, failure implication, down time of asset and can be done in many ways such as
- Defects for which Cost of repair and down time high: The cost of repair and down time is high when it involves lifting of the rolling stock, coaching stock marked sick requiring withdrawn from service. Such defects shall be identified with valuation of each defect for its role in down time and cost of repair.
- Implication of defect on Line failure
- Cost of maintenance material: Listing the cost of material
This is a statistical technique in decision making.
- It uses the Pareto Principle (80%-20% rule), the idea that 20% of the work generates 80% of the benefit of doing the whole job. Or in terms of quality improvement, a large majority of problems (80%) is produced by few key causes (20%).
- This is also known as VITAL FEW TRIVIAL MANY OR PENNY WISE POUND FOOLISH
- The challenge is to find out the vital 20%
- It is done by statistical analysis
The technique is used for reliability study and performance dependence with time.
A typical time dependence performance curve looks like
The most important part is to identify the interval of the three different stages of failure pattern. The interval will depend on the type of equipment. The wear out failure will establish the life the equipment. There are possibilities when a sudden jump of failure is observed during constant random failure due to manufacturing/maintenance or operating defect and taken as wear out failure, this will result in an evaluation of wrong life and replacement will start prematurely. This increases cost and corrective action not taken. It may be of interest that wear out failure shall be performed on a sample locomotive/asset and condition monitored in a very controlled conditions at frequent interval.