article august 2016

AUGUST 2016

AXIS METALLURGICAL COMPANY WWW.AMCO-CONSULT.COM

MONTHLY TECHNICAL ARTICLE

AMCO-TA-102

An Overview of a Reliability Engineer Tasks

and Reliability Engineering Application from a

Product Design and Plant Operation

Perspective

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FOREWORD

AXIS Metallurgical Company (AMCO) is an autonomous and independent Consulting Company with

the objectives of best Metallurgical Services to Saudi Arabian Oil and Gas, Petrochemical, Power

Generations, Fertilizers, Refineries, Manufacturing, Construction, Manufacturing, Defense and

Automobile Industries.

Our specialization is: Plant Life Assessment /Extension, Failure Investigation, Asset Integrity

Management, Boiler Inspection, Boiler Tube Condition Assessment, Tube Failure Analysis, RCM

Studies, RAM Studies, Single Point of Failure(SPOF) Studies, Plant Cycling, Cost Analysis, Plant

Benchmarking, Crack Assessment, Risk Based Inspection/Maintenance, Probabilistic Assessment,

Fitness-for-Service Assessment, Conditional Assessment, Plan Reliability Studies, Vibration Analysis,

Condition Monitoring, Stress Analysis, Support and guidance in Plant Operation and Maintenance,

Advice in weld repairs, Support with Materials, Inspection and Monitoring; Corrosion and oxidation

issues, Technology Development, Finite Element Analysis, Stress Analysis, P91 Steel Assessment,

Metallography, SEM/EDS Analysis, Contamination Analysis, Plant Mechanical Improvement Studies

with years’ experience around the globe.

The AMCO Monthly Article are offered within the following areas:

i. Plant Life Management

ii. Fitness for Service

iii. Risk Based Inspection/ Maintenance

iv. Advance Materials

v. Reliability Engineering

vi. Qualification, Quality and Safety Methodology

vii. Materials Technology

viii. Pipelines and Risers

ix. Asset Operation

x. Quality Control/Assurance

xi. Corrosion and Erosion

xii. Inspection and NDT testing

xiii. Microstructures and damage mechanisms

xiv. Operations and Maintenance

xv. Vibration and Condition Monitoring

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An Overview of a Reliability Engineer Tasks and Reliability

Engineering Application from a Product Design and Plant Operation

Perspective

About the Author

Mr. Lennox Bennett has more than 20 years of experience providing engineering services for various

industries. His extensive experience includes application of reliability and maintainability analysis

within the appliance, broadcast and wireless communication, medical device, telecommunication,

printing, defense, aerospace and process industries.

Lennox has detailed working knowledge of engineering design reliability concepts and application of

these concepts to real world situations. He has provided reliability and maintenance training for

participants from various industries that includes: Bauxite Mining, Food and Beverage Manufacturing,

Utility (Power System and Water Distribution System).

He is an expert in performing reliability analysis for different product design such as: emergency

beacon, medical devices, communication devices, home appliances and commercial printing equipment

during product development and for fielded products.

Mr. Bennett have developed both design and plant reliability and maintenance training and development

programs that provides extensive details of the contents discussed herein.

Abstract | Summary

In deciding what industry you want to work as a reliability engineer, it is always good to have an

understanding of what functional responsibilities you are expected to execute as a part of the job

function.

One should always carefully review the job description then compare their knowledge acquired through

training and on-the-job experience and ask yourself if you are capable of performing functions required

without additional training.

Furthermore we need to consider our technical limitations and at the same time be aware that the job

description provided may not exclusive represents all the tasks you are expected to perform.

The relationship between expectation and functional responsibilities is often to an extent represented in

a reliability program plan. The information provides herein gives an overview of some of the main tasks

that could be included in a reliability program plan for product design or industrial plant operations.

The focus from a design perspective is to develop a product that is robustly designed. The objectives

from a plant operation view point includes: maximum utilization of equipment, maintenance

effectiveness, high operational availability and equipment reliability.

In this article the author attempts to briefly explain some of the tasks reliability engineers performs and

also make comparison of reliability application in the different environments. It should be noted that

the information provided is not exclusive and the reader is encouraged to conduct further research as

necessary.

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Introduction

In today’s market from a design perspective products are more complex and often times incorporate

various technologies requiring ongoing support from different engineering disciplines. The user expect

the product to perform reliably.

Given the advent of mechatronics and its application to new product design, engineers encounter more

challenges in developing practical solutions that will ensure products are of high quality, performs

reliability, safely, with minimum variations and risk.

Regulations, product liability, human reliability, and potential warranty cost are other elements that

must be considered when the engineers develop a product design. The consequences of poor reliability

is one of the drivers for designing products that are robust. Life for reliability engineers is much easier

if he/she has comprehensive formal training and experience in reliability engineering.

In reality this is often not the case for a lot of engineers who are assigned the role of a reliability

engineer.

In my view the reliability engineering task becomes more challenging if the new engineer is not very

knowledgeable and experience in applying reliability engineering principles and at the same time is not

prepared to undertake research on the job.

This is particularly true in companies where products requires both hardware and software reliability

analysis to be performed. Common examples include: insulin pump, breaking system, mobile phone,

refrigerator, dialysis machine and ATM machine. Typically a reliability engineer knows either software

reliability or hardware reliability, and often not both.

On the other hand from a plant operation perspective often times attention is given to reliability when

equipment is aging and numerous failures begin to occur. More and more companies are now focusing

on preventive maintenance or predictive maintenance (PdM | CdM) as a means to improve equipment

reliability and availability. Some reluctantly choose to implement RCM.

Technical Discussion

Reliability from an hardware perspective can be defined as the probability that the device, system, or

process will perform its prescribed duty without failure for a given time when operated correctly in a

specified environment.

Software reliability can be defined as the probability that a given program module or modules will

operate for a specific time without a software error (Failure) when executed within its intended design

specification.

Reliability Centered Maintenance (RCM) has been selectively chosen by some companies to help

optimize maintenance decisions for critical equipment. Risk Based Maintenance and Risk Based

Inspection are other strategies employed especially in petrochemical and power plants to ensure reliable

and safe performance of selected assets.

Some engineers entering the field of reliability engineering does not know enough about these

techniques to feel comfortable or confident to support their application in the plant. This is really a

challenge for these new engineers.

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Table 1: Comparing Product and Plant Reliability Activities from

Program Plan

Product Development - Requirements Plant Performance - Requirements

Hardware Reliability Metrics Reliability of 95% after 10 years of Operation

Demonstrate 90% reliability after 5 years of

operation with 90% Confidence Overall Equipment Effectiveness (OEE) of 85%

Mean Time Between Failure (MTBF) of 5000

Hours Operational Availability of 99%

Availability Total Effectiveness Equipment Performance

(TEEP)

1 - Inherent of 0.95%

2 - Achieved of 97%

3 - Operational of 99%

Mean Time Between Maintenance (MTBM)

Mean Time to Repair (M 11K) lt.) of 30

Key Performance Indicators (KPI)

Software Metrics Power System Application

Probability of Failure on Demand [POFOD] of

0.001 Failure rate per year

MTBF of 10,000 Hours [CPU Time] Outage duration

Rate of Occurrence of Failure [ROCOF] of 0.01 Availability Factor

Defect removal efficiency shall be CNN Level S —

95% SAIFI I CAIDI I SAID'

The frequency and duration of recoverable

anomalous events shall be less than 0.0001 Water Distribution System

Probability of successful detection and service

restoration is at least 0.9995% Network System Analysis

Reliability data used to determine

maintenance strategy

Failure data used to determine

maintenance strategy

RCM - Maintenance Optimization

1 - Pd).1 I CdM

2 - Preventive Maintenance

3 - Run to Failure I CM

4 - Redesign

RCM - Maintenance Optimization

1 - PdM I cam

2 - Preventive Maintenance

3 - Run to Failure I CM

4 – Redundancy

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Methods for Risk I Safety Analysis Methods for Risk I Safety Analysis

FMEA I FAECA FMEA I FMECA

Fault Tree Analysis [FTA] Fault Tree Analysis [FTA]

Preliminary Hazard Analysis [PHA] Preliminary Hazard Analysis [PHA]

System Hazard Analysis [SI-Lk] Human Reliabiltiy

Risk Analysis - EEC 14971 MORT

Consequent Analysis

Human Factor I Human Reliability Analysis Utilized Maintenance Data

Design and Analysis of Experiment Reliability Growth - .A.MSAA Model

FRACAS Maintenance Effectiveness

Design Analysis Plant Reliability Model Development

System Reliability Modeling System Reliability Modeling

Worst Case Circuit Analysis Process Reliability Assessment

Component Derating

Tolerance Analysis

FEA I Thermal Analysis I Reliability Prediction

ESD I EMC I Other environment test

Sneak Circuit Analysis

Reliability Testing and Verification

Accelerated Life Testing (ALT) I ADT

High Accelerated Life Testing (HALT)

Reliability Growth (RG)

High Accelerated Stress Testing (HASS)

Ongoing Reliability Test (ORT)

Software Reliability Testing [Unit, Module,

Integration, System, Acceptance]

Warranty Analysis Determine Optimum PM Interval

Utilization of warranty models

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Table 1 above identifies some of the tasks a reliability engineer has to perform or support in a process

for designing reliability into a product.

Figure 1: Representative Role of an RE in Plant

Figure 1 also cite activities typically undertaken by the plant reliability engineer. It should be noted that

typically when a reliability engineer is not experienced in these areas a consultant is often brought on

board to help.

From both a product design and plant operation perspective the reliability engineer need to have basic

understanding of how reliability is specified. As indicated in the table, for a product with both hardware

and software we have two different sets of metrics. One set is generally specified for hardware and

another for software.

It should be noted that not all these metrics are used at the same time. It is the responsibility of the

reliability engineer and the development team to select the ones for use. For software reliability different

metrics are used depending on the software objectives and stage of software development.

The system reliability of the product is a combination of both the software and hardware reliability.

Both are determined separately either by one or two different reliability engineers. The reliability

engineer is expected to determine, verify or quantify both the components and the product system

reliability. This is often accomplished through reliability modeling and analysis.

As with product design various metrics are specified to assess the reliability performance of the

equipment. There are general metrics selected such as operational availability that can be applied. In

general, the metrics applied will depend on one or more of the following: component reliability, system

reliability and in some case in what industry the assessment is done.

In the manufacturing industry OEE and TEEP is common. Power plants use a unique sets of reliability

metrics to quantify transmission or distribution reliability. There are several analytical and simulations

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models utilized to determine reliability of water distribution networks. Reliability engineers operating

in these environments are expected to be at least familiar with these means of quantifying reliability.

RCM is utilized particularly with complex product design to optimize maintenance strategies as well as

for product redesign, modifications, and redundancy decisions. RCM Utilizes functional FMEA and a

decision matrix to determine appropriate maintenance based on potential failure rate of a given

component. Often times this technique is underutilized or not used due to lack of knowledge on the part

of the reliability engineer.

In a plant environment the RCM process also enables an effective an optimal maintenance strategy to

be developed. Given that the equipment is operating in the field, failure data will be available for use

with the FMEA and a decision matrix. The reliability engineer is required to ensure accurate, reliable

and complete data are available for analysis.

The engineer also needs to identify the equipment (critical assets) that are candidate for RCM analysis,

and determine required infrastructure or support necessary for successful implementation, and should

also be able to answer the question why is RCM necessary?

This technique is commonly applied in power plants, petrochemical plants and water distribution

systems. Different variations of RCM are implemented as well as an RCM audit process is established

for ongoing monitoring. As in the case of product design successful implementation is highly dependent

on knowledge and experience of reliability engineer in this area of specialization.

If the reliability engineer plan is to work in the petrochemical or power system industry knowledge and

experience in Risk Based Maintenance (RBM) based on AP – 913 equipment reliability guideline or

FTA for probability assessment and Risk Based Inspection (RBI) are certainly a plus.

Risk base methods are utilized to match criticality to equipment and determine inspection frequency

based on high risk failures. The emphasis here is on the effect of maintenance on reliability of plant

equipment. Knowledge of probability and consequence reduction strategies are important.

As an integral part of the product development process the reliability engineer is expected to use one or

more technique to evaluate safety and determine residual risk of the design. For military products these

analyses are performed in conjunction with one or more military handbooks or standards (MIL-HDBK-

882B, MIL-STD-1629A). Products for commercial use may require different standards.

General risk analysis of medical devices is performed in conjunction with IEC 14971. In general safety

analysis methods typically includes, FMEA, FMECA, FTA (IEC 61025 for MD), PHA, and SHA.

Successful application requires the engineer to have knowledge of these methods of analysis as well as

an understanding of the appropriate standards or regulations that may be specified in the requirement

document.

The general principles and application of risk analysis employed for design analysis are essentially the

same when applied to industrial plant equipment. Other analysis such as human reliability assessment,

consequence analysis and MORT are particularly important for safety in the mining industry. In some

organizations these analyses are performed by safety engineers and reliability engineers are expected

to participate.

Human reliability/human factor assessment are usually required for defense products. It is also an

important particular for class III medical devices. It is relevant to determine the probability of failure

occurring due to human error given that consequence can be serious injury or death. This is however

an area of reliability assessment techniques that escapes numerous reliability engineers.

Reliability engineers utilize Design and Analysis of Experiments to both identify and optimize critical

product parameters during design and development. This analysis is also utilized in accelerated life

testing to identify stresses that can have significant effects on product reliability performance.

Knowing how and when to apply this technique is crucial to successful application to improve the

reliability of the product design. It is certainly advantageous for the reliability engineer to have this

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knowledge. Often times the quality engineer who has this knowledge is not proficient enough to apply

it to improve product reliability.

During product development the reliability engineer is expected to work with the product development

team to ensure failures that occurs are appropriately documented and can be quickly retrieved when

required for reliability analysis. A Failure Reporting and Corrective Action System (FRACAS) is

utilized for this purpose.

For medical device application some companies integrate this system with their CAPA process. It is

also used for products that are deployed to capture data required for warranty analysis and product

improvements. Several software modules are however available that facilitates this application. It is

very essential for reliability engineers to understand this process. This application is most popularly

used in a military environment.

In a plant environment failure data are managed by other kinds of database software application

(CMMS, SCADA), hence the reliability engineer usually focused on what is available. FRACAS

systems can however be found in some industrial plants. It is therefore necessary for the reliability

engineer to have some knowledge of this application.

The reliability engineer is expected to know how to utilize the failure data to determine equipment

availability, reliability, maintenance frequency and reliability growth/improvement. Several models can

be utilized to model reliability growth and predict failures from the failure data/maintenance data. The

AMSAA Model is one method that is commonly used.

From a planning perspective being able to predict failure will support maintenance strategy decisions.

Engineers who lacks training in this area will certainly be at a disadvantage and may have to do some

remedial work to come up to speed.

Other design analysis such as: reliability prediction, worst case circuit analysis, component derating,

FEA, tolerance analysis, thermal analysis and environment testing selection are part of the

responsibilities of the design reliability engineer.

If the reliability engineer entering the field does not have a basic understanding of these techniques,

then his/her job will have some initial challenges especially if a good reliability program is established

within the company. In such situation delegation where possible is recommended. Let’s say for example

FEA could be done by the mechanical engineer. Thermal analysis by the electrical engineer.

The plant reliability engineer on the other hand performs system reliability modeling of the plant assets.

In addition, he/she is expected to determine the reliability of the process. It should be noted that process

and equipment reliability are different.

Product reliability is typically verified through testing. There are different categorizations of

classification schemes used for testing: development testing, qualification testing, environment testing,

and reliability testing of hardware. Reliability engineers are expected to be able to distinguish between

these, develop test plans, recommend number of units to be tested, analyzed test data and in some

instances develop test reports.

Test includes: accelerated life testing, accelerated degradation testing, high accelerated life testing. High

accelerated stress screening, reliability growth testing and ongoing reliability test. An understanding of

the stage in the development process where specific test is used is required.

Accelerated Life testing utilizes various models that depends on the stress application and other factors

to identify design deficiencies and predict product reliability. The development team relies on the

reliability engineer as the subject matter expert. There are also several models from which to quantify

reliability growth. Again here knowledge is essential for the reliability engineer to be able to provide

guidance.

Qualification test can include compliance tests such as IEC 60601 and other environment tests or test

to standards such as GR-468-CORE. Products are expected to perform robustly in its intended

environment of use. As a means to verify specification requirements products are tested to standards

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such as: ISTA 3B, MIL-STD-810, RTCA/DO-160E, and MIL-STD-461. The engineer is often expected

to provide guidance on the relevant standard for the product been designed.

The software used with the product must also be tested to verify the level of reliability as the software

goes through the development cycle. There are many types of test that are executed as a part of the

verification and validation process. The process involves: units testing module testing, integration

testing, system testing and acceptance testing.

The software reliability engineer is expected to: identify the reliability test that can be used at each

phase as well as recommends the reliability prediction or growth estimation models to be employed to

analyze the failure data, and perform reliability assessment.

Verification measurement includes test coverage and reliability modeling (WeibullModel, Rayleigh

Model, Reliability Growth Model). Static verification such as FTA and FMECA are also applied to

prevent reliability issues. Decision for software release is dependent on reliability demonstrated.

If an engineer does not have any training or experience in these techniques, then he/she may not be

adequately prepared for a role as a reliability engineer in this area. It cannot be over emphasize for the

engineer to evaluate his/her strengths and weaknesses before deciding what area they will be

comfortable to work.

Companies specify warranty policies for their product based on warranty policy and reliability analysis.

Management expects products to be designed for warranty cost reduction. The reliability engineer is

expected to utilize selected warranty cost models as well as used failure data to determine optimum

warranty period.

He or she is expected to perform reliability estimation from warranty claim following deployment of

products.

Conclusion

Engineers entering the field of reliability engineering often ask the question, what is the difference

between reliability engineering application in product design and in an industrial plant operation

environment?

The answer to this question helps to provide guidance to the new engineer as well as means for he/she

to distinguish between how reliability engineering activities are applied uniquely in the different

environments.

As presented in this article several reliability methods in the reliability toolkit are utilized on a day-to-

day basis in product design and plant operations. The competence of the reliability engineer is one of

the factors that can be used to determine how challenging respective task will be.

Self-assessment is always a good means of checking one’s readiness of the job at hand. An engineer

should seek to have a good understanding of the challenges of the job he/she is planning to undertake.

References

1. Handbook of Software Reliability Engineering, Michael R. Lyu, McGraw Hill Companies, 1996

2. Reliability Technology, Human Error, and Quality in Health Care, B.S. Dhillon, CRC Press, 2008

3. Accelerated Testing “Statistical Models, Test Plans, and Data Analysis”, Wayne Nelson, John Wiley

& Sons Inc. 1990

4. Handbook of Medical Device Design: Richard C. Fries, Marcel Dekker, Inc. 2001

5. Reliable Design of Medical Devices – Richard C. Fries, 3rd Edition, CRC Press, 2013

6. Life Cycle Reliability Engineering – Guangbin Yang, John Wiley & Sons Inc. 2007

7. System Reliability Toolkit: “A Practical Guide for Understanding and Implementing a Program for

System Reliability, RiAC and DACS, 2005

8. Practical Reliability Engineering – Patrick D. T. O’Connor, 4th Edition, John Wiley & Sons Inc.

2002

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9. Design for Reliability – Dev Raheja, Louis J. Gullo, 1st Edition, John Wiley & Sons Inc., 2012

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Publishing, 2013.

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& Francis, 1997.

12. Roy Billinton, Ronaldo N. Allan., “Reliability Evaluation of Power System”, Plenum Press, NY,

1996.

13. Andrew K. Jardine, Albert H.C Tsang., “Maintenance and Replace – Theory and Application”,

Taylor and Francis, 2006.

14. Andrew K. Jardine, John D. Campbell., “Maintenance Excellence – Optimizing Equipment Life

Cycle Decision”, Marcel Dekker Inc., NY, 2001.

15. Larry W. May., “Water Resources System Management Tools, McGraw Hill, NY, 2005.

16. Water Distribution System Handbook – Larry Mays.

17. Evaluation of Water Distribution Network Reliability – Y.K. Tung.

18. Approval of Source Heads Methods for Calculating Reliability of Water Distribution Network by:

T.T. Tanyimboh, M. Tabesh and Burrows.

19. D. N. Prabhakar Murthy., “Product Reliability – Specification and Performance, Springer, 2008.

20. Charles E. Ebeling., “An Introduction to Reliability and Maintainability Engineering”’ McGraw

Hill, 1997.

21. Elsayed A. Elsayed., “Reliability Engineering”, Addison Wesley, 1996.

22. The Maintenance Frame work “Model & Methods for Complex Systems Maintenance” – Adolfo

Crespo Marquez.

23. NAVAIR-0025-403 - Guidelines for the Naval Aviation Reliability Centered Maintenance Process.

24. Reliability modeling and Prediction, and Optimization: Wallace R. Blischke, John Wiley and Sons

Inc, 2000

25. Software Reliability Growth Models: Overview and Applications, Razeef Mohd, Mohsin Nazir,

Journal of Emerging Trends in Computing and Information Science, 2012.

AMCO

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