microsoft power point - section 10a_lcc_weibull [compatib (1)

8/14/2019 Microsoft Power Point - Section 10a_LCC_Weibull [Compatib (1)

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Section 10

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e a y oo s



Continuous Reliability Improvementof Rotating Equipment

“Increasing Productivity and Reducing Maintenance Coststhrough Outstanding Equipment Reliability”

Section 10: Life Cycle and Reliability Tools

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Presented byRalph W. Pete” Peters, FounderThe Maintenance Excellence Institute

For SALVO Global Singapore



Life Cycle Costs Acquisition Costs

• The initial cost of acquiring and installing the system –

conceptual studies, development, installation andcommissioning

Operating Cost

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Maintenance Costs

• Labour, parts etc

Costs of failure

• Downtime expenses Disposal Costs or Income

• Decommissioning and sale of plant



Minimize the Life Cycle Cost

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Reliability, Availability andMaintainability (RAM)

Understanding Reliability and Availability

• Reliability is the probability that an item will survive a

given operating period, under specified operating

conditions, without failure.

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• Availability is1. The time a machine or system is available for to

operate to a specified condition or performance

standard, whether needed or not

2. From the Overall Equipment Effectivenesscalculation, the actual run time of a machine or

system divided by the scheduled run time



Maintainability

• Maintainability is the ability to retain or restore functionwithin a specified period of time, when provided with anidentified level of tools, training, and procedures.Maintainability factors include

Reliability, Availability andMaintainability (RAM)

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- Access - Equipment, its components, and facilitiesshould be accessible for maintenance

- Material - Choose materials for durability, ease of maintenance, availability and value

- Standardization - Minimize use of special or one-of-a-kind materials, fittings, or fixtures. Maximizecommonality of equipment component parts. Choosestandard equipment for multiple uses where feasible



Life Data Analysis (Weibull Analysis)

Life data analysis (also called "Weibull analysis") attempts tomake predictions about the life of all products in the

population by "fitting" a statistical distribution to life data

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This distribution for the data set can then be used to

estimate important life characteristics of the product such

as reliability or probability of failure at a specific time, the

mean life for the product/item and failure rate



Life Data Analysis (Weibull Analysis) Life data analysis requires:

• Gathering life data for the product/item of equipment• Selecting a lifetime distribution that will fit the data and

model the life of the product (item of equipment)

• Estimatin the arameters that will fit the distribution to

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the data• Generating plots and results that estimate the life

characteristics, such as reliability or mean life, of theproduct

Specialist software packages are available to conduct lifedata analysis

Life data analysis should be conducted by trained analysts




Life data:• The term life data refers to measurements of the

life of products. Product lifetimes can be measured’

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applies to the period of successful operation of aparticular product

• Since time is a common measure of life, life data

points are often called "times-to-failure" andproduct life is usually described in terms of time




There are different types of life data:

• With complete data, the exact time-to-failure for the unit isknown (e.g. the unit failed at 100 hours of operation)

• With suspended or right censored data, the unit operated

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could have continued) to operate for an additional unknownperiod of time (e.g. the unit was still operating at 100 hours of operation)

• With interval and left censored data, the exact-time-to failure

is unknown but it falls within a known time range. Forexample, the unit failed between 100 hours and 150 hours(interval censored) or between 0 hours and 100 hours (leftcensored)




Lifetime Distributions

• Statistical distributions have been formulated bystatisticians and engineers to mathematically model or

represent certain behaviour. The probability density

function d is a mathematical function that describes

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the distribution. The pdf can be representedmathematically or on a plot where the x-axis represents

time




Life data analysis is sometimes called "Weibull analysis"

because the Weibull distribution, formulated by Professor

Wallodi Weibull, is a popular distribution for analyzing life

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a a

The analyst chooses the life distribution that is most

appropriate to each particular data set based on past

experience and goodness of fit tests




Parameter Estimation

• In order to "fit" a statistical model to a life data set, theanalyst estimates the parameters of the life distribution thatwill make the function most closely fit the data

• The parameters control the scale, shape and location of the

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p unc on

• For example, in the 3-parameter Weibull distribution:

- The scale parameter, (eta), defines where the bulk of thedistribution lies

- The shape parameter, (beta), defines the shape of thedistribution and

- The location parameter, (gamma), defines the location of the distribution in time



- Probability of Failure Given Time: The probability that a

product will fail at a particular point in time. Probability of failure is also known as "unreliability" and it is thereciprocal of the reliability. For example, there is a 12%chance that the product will be failed after 3 years of


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successfully)

- Warranty Time: The estimated time when the reliabilitywill be equal to a specified goal. For example, theestimated time of operation is 4 years for a reliability of

90%.- etc.

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