section 5b data collection slides compatibility mode

1PEUSS 2011/2012 Data Collection and Analysis Page 1

Data Collection and Analysis

Dr Jane MarshallProduct Excellence using 6 Sigma

Module

PEUSS 2011/2012 Data Collection and Analysis Page 2

Objectives

Understand the relationship between data andanalysis objectives

Understand the data collection planning process Appreciate human factors of data collection


What is data? The terms 'data' and 'information' are used

interchangeably However the terms have distinct meanings:

Data are facts, events, transactions and so on which havebeen recorded. They are the input raw materials from whichinformation is processed.

Information is data that have been produced in such a way asto be useful to the recipient.

In general terms basic data are processed in someway to form information but the mere act of processingdata does not itself produce information.


Data Characteristics

Data are facts obtained by reading, observation,counting, measuring, and weighing etc. which are thenrecorded.

Called raw or basic data and are often records of theday to day transactions of an organization.

Data are derived from both external and internalsources.

Data may be produced as an automatic by-product ofsome routine but essential operation


Data Characteristics

The pool of data available is effectively limitless. This abundance means that organisations have to be

selective in the data they collect. They must continually monitor their data gathering

procedures to ensure that they continue to meet theorganisation's specific needs

The data gathered and the means employed naturallyvary from business to business depending on theorganization's requirements.


Why collect data?

Measure reliability Document spares consumption Provide statistics

These are reactive Better to be pro-active


Why collect data?

Maintenance planning Maintenance improvement Identify & justify need for modification Calculate future resource & spares requirements Assess likelihood of mission success Confirm contractual requirements


Why collect data

To assist achievement of worthwhile objectives

Data collection is time-consuming & costly. We should only collect data where there is an

identified and worthwhile benefit from doing so.


From data to worthwhileobjectives

Operation

Data Collection

Analysis

Results

Decisions

Achievement ofObjectives


Put planning into datacollection

Operation

Data Collection

Analysis

Results

Decisions

Achievement ofObjectives


Put planning into datacollection Worthwhile objectives require decisions:

To changehow much, what, when, how To not change

Decisions need clear supporting evidence: Analysed resultsnot all analysis is equal

Analysis needs data Good results need good analysisbut good analysis may

need expensive data Optionsconsider alternatives and identify most cost-

effective that enables objectives


Put planning into datacollection Data collection does not need to satisfy all

objectives all the time. For example: Objective 1: Identify quickly that there is a reliability

problem Routine data collection sufficient to allow SPC or CUSUM

analysis of occurrences Objective 2: Identify accurately what the problem is

Special data collection once a problem has beenidentifiedpossibly using sampling techniques andengineering analysis rather than data analysis


Data collection must have apurpose! Data should be collected for a purpose:

to enable analysis, Focus on increasing understanding of item operation and

failure, Application of this knowledge to a goal or objective.

Without a definition of the objective for the future dataanalysis and the application of its findings, collection ofdata is likely to be aimless and will omit important data,allow corruption of data, or may waste time andresources by including data that offer little benefit.


Questions to consider

What observed availability is achieved with theapplied maintenance regime?

What values have been achieved with a former,similar product?

Does the product conform to the requirements? What affect has environment and usage on

dependability? How stable is the dependability of manufactured

items with time?


Level of reporting

Structure of items

system; equipment; module or unit; part or component; software module.

Generically thesecan all be termeditems

Different phases of the lifecycle : production to delivery; installation; operation; time of warranty; long term behaviour, useful

life, service effort; withdrawal from operation;


Inventory Information proving that a particular item exists in the field How that item is configured What other items that item contains

Usage Information about when an item was placed into the field, How that item is operated in the field When that item was removed from the field

Environment Information about the operating conditions of the item

Events Information about any thing that has happened to the item during

its life

What data needs collecting?


Data sources Servicing records, warranty records, repaired product records spares used records Disposal records Customer complaints Customer reports and comments can also be used to

help complete a data set. Insurance claims and coverage records


Resources The infrastructure :

Diagnosis and service utilities as necessary for maintenance; Computerized tools for data storage, aggregation, Analysis and

reporting; Facilities for raw data recording computerized facilities Remote condition monitoring and data collection.

Economical and financial aspects to be considered are: Cost for implementation and maintaining regular data collection; Benefits gained by improvement of processes caused by measures

based on the information feedback from field data.

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Data Validation Why validate

Avoid garbage-in, garbage-out Avoid wrong decisions with costly consequences Reliability analysis often requires large amounts of data, collected over a

long period of timeit is too late to find that data is corrupt when analysisis attempted

How to validate Input masks, cross-checks (e.g. serial # fitted previously is serial #

removed, serial # fitted is serial # removed from stores, item fittedmatches host equipment, etc.), usage matches expectation, gaps in data

Use electronic aids such as smart-chips, bar-coding Validate incrementallyvalidate at point of data entry


Human factors in datacollection

Make simple to get data collection correct Make difficult to get data collection wrong Complexity? Layout? Masks? Computer

assistance? Involve those who collect the data in the

planning processbuy-in to objectives

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Analysis

Analysis is often as much detective work as it isstatistics Analysis answers a statistical questionbut the

human must identify the question to ask There are no absolutes in reliability or

maintenance data analysis Results give guidance to decisions

Always start with the simple analysis beforeattempting more advanced methods


Examples of Analysis

Count number of failure events?what is afailure event?

Calculate the rate of occurrence against usage? Identify the distribution of the events with time? Examine the causes of failure events?

each is more complex than the previous

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What is usage?

Which measures of life-consumption should beused?hours, days, cycles, time-since-overhaul?

What factors potentially affect the rate of life-consumption?time of year, production batch,user?

What is the influence of the environment?effects of different market segments?


Analysis data censoring Complete data means that the value of the life time of each item

is observed or known. For example, for life data analysis, thedata (if complete, which is unusual in field data collection) wouldcomprise the times-to-failure of all units in the field.

Often when life data are analyzed, all the units may not haveexperienced events of interest or the time of the event is notknown. This type of data is censored data.

There are three types of possible censoring schemes, right censored data (also called suspended data), interval censored data, and left censored data

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Analysis right censoring

The most common case These data are

composed of units thatdid not experience anyevents.

The term "rightcensored" implies thatthe event of interest is tothe right of the analysispoint.

Unit 1

Unit 2

Unit 3

Unit 4

Unit 5


Analysis interval censoring

Interval censoreddata containsuncertainty as to theexact times theevents happenedwithin an interval.

Unit 1

Unit 2

Unit 3

Unit 4

Unit 5

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Analysis left censoring

An event occurrencetime is only known tobe before a certaintime

Unit 1

Unit 2

Unit 3

Unit 4

Unit 5


Results

Use the results Support decisions to enable achievement of

objectives Improve data collection process

Refine Target

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Syndicate exerciseYou are project managers in a car design and manufacturing company. Your company has links to a network of car dealers (sales, repair and

servicing). It does not currently have contact directly with end-users. Identify 3 key objectives for a data collection and analysis system to be used

by your company. For each objective give examples of:

Type of data Method of collection Costs implications

With appropriate consideration of technology, human factors, businessfactors and costs, design a cost-effective data collection and analysis systemidentify: Benefits How well it will meet the objectives

Present your work


Summary

Reliability & Maintenance data collection shouldpro-actively support management objectives.

R&M data may be expensive and should betailored for maximum cost-benefit.

The analysis process is feasible only with validdataHuman factors are an important issue

section 5b data collection slides compatibility mode

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