reliability risk newsletter september 2018...2 2 qe best paper award –call for papers! the...
TRANSCRIPT
Reliability & Risk NewsletterSeptember 2018 Edition
CONTENTSTrevor CraneyChairASQ Reliability & Risk [email protected]
1. 2. 3.
4.5.
6.78‐9. 10. 11.12.13.
14.
Check out our website at: http://www.asqrrd.org/
CHAIR’S NOTE
1
Chair’s Note QE Best Paper AwardDivision Budget Report, Creep, & Risk‐Based Decision ‐MakingASQRRD membership Statistics Social Media status, Future Webinars, and Creep LifeRAMS 2019 Orlando, FLRelyence Software adHBM Prenscia ads2017‐2018 ASQ‐RD Leadership TeamIntroduction of a Book on Risk/Reliability Standard ErrorWorkshop Title: Risk Analysis for Autonomous VehiclesCRE Sample Questions
As we begin the last 1/3 of 2018, some changes have occurred in the leadership team of the ASQ Reliability and Risk Division. As of September 1, I have assumed the role of Chair of the division. Tim Gaens has been appointed to Chair‐Elect and Rong Pan has been appointed to Secretary. Jim Breneman continues in his role as Treasurer and David Auda continues in his role as Past Chair.Another announcement we have finalized the date and location of our new conference to begin in 2019. It will be October 15‐17, 2019 in San Antonio, TX. There will also be pre and
post‐conference courses on Oct 14 & 18, respectively. Look for more details in the upcoming months. The first year of this conference will also be a major event as the division celebrates its 50th
anniversary.RAMS is also coming up in January in Orlando, FL. For those attending RAMS , we will announce in the next newsletter an open session to meet and interact with the division leadership team at the conference. Look to the website (www.rams.org) for details on the conference program and pre and post‐conference courses offered by the ASQ‐RRD.Your division leadership team is hard at work planning other activities and events for networking, content development & sharing, and creating new volunteer opportunities. 2019 is going to be a great year! A lot of focus in ASQ communication this year has been on its impending Transformation. The divisions leadership team will endeavor to provide input and work with the ASQ TCC and ASQ staff to ensure that we are able to continue to bring value to your membership in ASQ and the Reliability and Risk Division. I welcome this opportunity to serve as your Chair of the ASQ Reliability Division and I have very high confidence in the leadership in place to deliver on your needs.Trevor Craney
QE Best paper Award
2
2
QE BEST PAPER AWARD – CALL FOR PAPERS!
The reliability focused papers appearing in the four issues from July 2018 to June 2019 will be considered. For more information, please contact Prof. Rong Pan at [email protected].
$1000 Annual Award for Best RELIABILITY Paper!Continuing in 2018‐2019, the ASQ Reliability & Risk Division
will administer a $1000 annual award for the Best Reliability Paper published in Quality Engineering. To be eligible for the award, at least one of the authors of the paper must be a member of the ASQ Reliability & Risk Division at the time when their paper was published.
We have our winner of the 2017‐2018 ASQ‐RRD Quality Engineering best paper award!
Nathaniel T. Stevens & Christine M. Anderson‐Cook paper “Quantifying Similarity in Reliability Surfaces using the Probability of Agreement”, Quality Engineering, Vol/Issue:29:3, pp 395‐408 has been selected as the 2017‐2018 RRD Quality Best Paper.
Abstract: When separate populations exhibit similar reliability as a function of multiple explanatory variables, combining them into a single population is tempting. This can simplify future predictions and reduce uncertainty associated with estimation. However, combining these populations may introduce bias if the underlying relationships are in fact different. The probability of agreement formally and intuitively quantifies the similarity of estimated reliability surfaces across a two‐factor input space. An example from the reliability literature demonstrates the utility of the approach when deciding whether to combine two populations or to keep them as distinct. New graphical summaries provide strategies for visualizing the results.
DIVISION BUDGET REPORT (as of August 31, 2018)
3
Calling all Webinar Authors!! Dave Auda ([email protected])
The Shainin Medal National Committee is looking for worthy candidates to be considered for the next round of medal applicants. In 2003, ASQ established an award to recognize the development of statistical methods for solving quality problems in products or services. The award was named for Dorian Shainin, a leading authority on product quality and reliability. During a professional career that spanned nearly six decades, Shainin developed more than 20 statistical techniques for solving problems, controlling processes, and developing highly reliable products. The nomination form is available on the ASQ website (url: https://asq.org/about‐asq/asq‐awards/shainin) . For further details or for answers to questions, please contact Patti Cyr, Shainin Nominating Committee Member [email protected]
ASQ Shainin Medal
• Checking account as of August 31, 2018: $73,608.42 • Income over expenses‐YTD( $53,980.40 ‐ $41,915.11): $12,065.29• Other funds/investments :
• Investing in ASQ(though 8/31/2018): $231.96 (Acct total end of Dec 2017 $32,900.62 withdrawn by ASQ HQ)
• PNC investment account: $ 0.00( Investment account withdrawn by ASQ HQ end of April 2018)
We would like to extend an invitation on behalf of the ASQ Risk and Reliability Division (ASQRRD). If you would be interested in being a presenter of an ASQRRD webinar, contact Dave Auda. Webinars run every 2nd Thursday of the month at noon EDT for 1 hour. The content should be something that the attendees can use, Reliability‐related knowledge and/or skill. Why present? A large potential audience that we invite, an additional entry
to your resume demonstrating competence, refine your skills, AND earn recertification points. If you have need of support in developing, preparing and/or presenting at
such an event, let us know… we can help you. Become a recognized subject matter expert!
ASQ‐RRD MEMBERSHIP STATISTICS
3
Social Media and Webinar Roundup!!
5
Social Media (Tim Gaens [email protected] )
Current follower status on the social media:LinkedIn: 4,064
Twitter: 607 Facebook: 23
Upcoming Webinars
English Webinars:THE RISK‐BASED DECISION‐MAKING by Jim BrenemanDate:September 13, 2018Time: 12:00 PM – 1:00 PM EDT
CATALYSTS FOR HUMAN ERROR IN COMPLEX SYSTEM DESIGN:GLITCHES AND REPRESENTATIONS IN THOUGHT AND ACTION by Audrey MurphyDate: October 11, 2018Time: 12:00 PM ‐ 1:00 PM EDT
Life Assessment of Gas Turbine Blades Under Creep Failure Mechanism M. Pourgol‐Mohammad, Email: [email protected]
Turbine blades are under various loading cases such as inertia, bending and thermal. They work under elevatedtemperature and high stress, and therefore gradual deformation appears with time. The combination of temperatureand stress cause creep and temperature changes causes thermal fatigue. There are several methods for predicting creeplife such: a) model‐based approach b) service‐based approach c) statistical/probabilistic‐based approach.The model‐based approach can further be classified into two sub‐approaches which are total life approach, and thedamage tolerance approach. The creep prediction total life‐based methodologies are divided to three distinctapproaches such: i) Time‐Temperature‐Parametric (TTP) methods ii) strain‐based methods iii) damage mechanicsmethods. Classical Monkman‐Grant empirical relation and Theta projection model and Omega method are examples ofstrain‐based methods that have been successfully used in components creep prediction. Strain based models predictthe life of the material/component by direct calculation of the time‐to failure using creep strain rate or creep strain. TheLarson‐Miller approach can be used to determine creep rupture time for any stress‐temperature combination for a givenmaterial. The Larson‐Miller equation was developed during the 1950s while Miller and Larson were employed by GEperforming research on turbine blade life. The parametric relation they developed is used to extrapolate experimentaldata on creep and rupture life to all temperature‐stress combinations and to time spans that would be impractical toreproduce by laboratory testing. The equation represents a linear expression to calculate a parameter, P, that relatescreep time and temperature to a given stress and creep strain level, typically creep rupture. The expression is shownbelow in equation beow, where t = time in hours, T = temperature in degrees Fahrenheit, and C is an empirical constant.A value of 20 for C is applicable for low alloy steels, and a factor of 30 is sometimes used in the case of higher alloysteels. Larson‐Miller parameter P is sometimes divided by a factor of 1000 for convenience.
6
Reliability & Quality Software
KEYHIGHLIGHTS
• Integratedsuite
• Stand-alonetools
• FMEA,FMECA
• FRACAS,CAPA
• FaultTree
• ReliabilityPredicCon
• ReliabilityBlockDiagram
• PC,Mac,tablet,phone
• On-premiseorcloud-based
• Onlineorin-persontraining
• ImplementaConservices
• Knowledgeabletechsupport
• Free,noinstalltrial
Relyenceoffersacompletesolu1onforallyourreliabilityandqualityso7wareneeds.Alongwithourso7waretools,weoffertop-notchtechnicalsupport,implementa1onservices,andtraining.
TheRelyenceSoluCon.Providing seamless integra0on between FMEA (including Process Flow Diagrams and Control Plans), FRACAS, Fault Tree, Reliability Predic0on, and RBD analyses, the Relyence tool suite empowers you to effec0vely manage your products throughout their lifecycle. You can use each module stand-alone, or combine the tools you need in our Relyence Studio integrated plaJorm.
Power&InnovaCon.Relyence tools pack an impressive list of features. Just a few of the highlights include: customizable cross-module dashboards; user-interface customiza0on; flexible report genera0on; data impor0ng and expor0ng; API func0onality; device libraries; workflow, approvals, and no0fica0ons; user and group roles and permissions; and Relyence innova0ons such always-in-syncTM technology, smart-layout, KnowledgeBankTM for lessons learned reusability, and FMEA-Fault Tree link-syncTM.
Flexibility&CollaboraCon.All Relyence tools can be accessed from any computer, PC, Mac, laptop, tablet, or smartphone for ul0mate flexibility and team collabora0on. You can use Relyence either as on-premise installa0on on individual computers or a network, or as a zero-client, browser-based plaJorm with your data hosted in the MicrosoT cloud or in your own private cloud. You choose!
RelyonExcellence.In conjunc0on with our soTware tools, we provide world-class services to help ensure your success. Our Implementa0on and Training teams can get you up to speed quickly, and our Technical Support team consistently provides support that is unparalleled in the industry.
Signuptodayatrelyence.com!
relyence.com · 724.832.1900RelyenceisatrademarkofRelyenceCorpora4on.Otherbrandandproductnamesaretrademarksorregisteredtrademarksoftheirrespec4veholders.
TRY FOR FREE
FMEA, FRACAS, Fault Tree, Reliability Prediction, RBD
www.hbmprenscia.com
ReliaSoft SEP by HBM Prenscia is a web portal that provides convenient mobile access and quick at-a-glance summaries for analyses performed in ReliaSoft applications. Implementing the website together with ReliaSoft XFMEA offers a powerful and flexible solution for corporate-wide access to FMEAs.
● FMEA teams can utilize full-featured software that facilitates the analysis process along with the convenient mobile access provided by the web portal.
● For managers with multiple teams working on different FMEAs, the web portal offers a quick and convenient way to stay up-to-date on potential risks, assigned actions and whether analyses will be completed on time.
● Colleagues throughout the organization can access the valuable lessons learned for use in other activities, such as designing test plans, troubleshooting for customer support and future product development.
FMEA teams use both desktop and web to facilitate the analysisTeams performing FMEAs can utilize all of the analysis capabilities in XFMEA along with some additional features enabled by SEP. For example:
XFMEA can send alerts when an assigned action is created, modified or ready to be reviewed. With SEP, you can also trigger alerts based on the action due date (e.g., send an alert 1 week before the action is due, then send a reminder every day until the action is complete).
Utilizing FRACAS data when performing FMEAs saves time and leads to more effective risk assessment. If your organization is using XFRACAS for failure reporting and team-based problem resolution, SEP makes it easy to view the field failure data for a particular part or failure mode.
Improve corporate-wide FMEA collaboration with SEP web portal
SEP makes it easy to view field failure data in XFRACAS, and to open the full analysis in XFMEA
www.hbmprenscia.com
If SEP is configured for “Remote ReliaSoft,” users can launch XFMEA on a remote server without having to install and update software on each client computer. (There are additional hardware and license requirements for this feature.)
Managers use the website to track progress and sign off on FMEA versionsWhen an FMEA is ready to review or approve, the analysis team can copy or e-mail a link to an at-a-glance summary that the manager can view in any web-enabled device.
You can easily track key indicators such as:
● number of failure modes and the percentage fully analyzed
● top failure modes
● status of assigned actions, with % complete
If the team is using the change log tracking feature in XFMEA, the manager can also use the website to sign off on the controlled analysis version.
Stakeholders use SEP to access lessons learnedFor colleagues throughout your organization, SEP provides multiple ways to share the latest analysis and lessons learned… with no desktop applications installed.
The web portal shows the latest FMEA, custom dashboards and finalized report documents that are saved with the analysis project.
Users can also run saved queries for any FMEA or group of FMEAs, to get customized output such as actions that are not complete or failure modes with high risk.
ConclusionImplementing SEP together with other ReliaSoft applications provides convenient, mobile access to key reliability analysis results and helps to facilitate cooperation across different areas of expertise. In addition to the FMEA solution described here, you can also use SEP to share selected results from Weibull analyses, reliability growth testing, system simulations and other reliability studies performed in Weibull++, ALTA, RGA, BlockSim, RENO or Lambda Predict.
Quick at-a-glance FMEA summary and sign off via the web
Multiple ways to share FMEA lessons learned throughout the organization
Contact Trevor Craney [email protected] to volunteer with us today!
2018‐2019 ASQ‐RRD LEADERSHIP POSITIONS
10
Elected Positions
ChairTrevor [email protected]
Chair‐ElectTim [email protected]
SecretaryRong [email protected]
TreasurerJim [email protected]
Past ChairDave [email protected]
Appointed PositionsMembership ChairTim [email protected]
Nominations ChairDave [email protected]
Education Chair Jim [email protected]
Regional Counsellors CoordinatorVacant
Audit ChairTim [email protected]
Arrangements ChairTrevor [email protected]
Newsletter Editors:Jim Breneman
[email protected] Pourgol‐[email protected]
QE Best Paper Award ChairRong [email protected]
Social Media:Tim [email protected]
Webmaster:Tim [email protected]
MarketingAngleat [email protected]
RAMS Board of Directors: (2 people) Trevor Craney, vacant
RAMS Management Committee:Julio Pulido, vacant
RAMS Best Paper Chair:vacant
Webinar OutreachExecutive Producer & Speaker Manager: David Auda ([email protected])Chinese Host: Frank Sun ([email protected])English Hosts: David AudaSpanish Host: Norma Antunano ([email protected])Data Analysts: Rachel Stanford ([email protected]), Tim GaensVideo Editor: Ward Baun ([email protected])
INTRODUCTION OF A BOOK ON RISK/RELIABILITY
11
Handbook of RAMS in Railway Systems: Theory and PracticeQamar Mahboob, Enrico Zio (2018)
Modern railway systems are complex systems. Such complexity is the price to pay for improvedfunctionality and is due to the use of modern technologies, including computers, microprocessors,communication and IT technologies. These interface with the traditional electromechanicalcomponents through a complex network of inter‐ and intra‐ dependencies. In this complexity, there stillremains the target for the designers, operators, maintainers and approvers to consider the acceptablelimits of the systems states, with respect to RAMS (Reliability, Availability, Maintainability, Safety).Modeling, assessment and demonstrations of RAMS require careful and combined handling of• Railway engineering systems;• Development and application of mathematical and statistical methods, tools and techniques;• Compliance with international and local standards, and laws and specific project requirements;• Associated finance and economics.
The primary objective for carrying out RAMS activities is to obtain a safe, highly reliable andavailable, innovative and sustainable railway system. RAMS studies are also fundamental to increasethe lifetime of railway systems. The railway RAMS related standards provide RAMS specifications, andespecially require the railway manufacturers and operators to implement a RAMS management systemand demonstrate particular safety standards and RAMS requirements. These standards mainly providegeneral guidelines on different RAMS topics and do not provide details on how to use them in realworld projects.
The topics provided in this handbook aim to improve the understanding and application of RAMS‐related standards and theories, methods, tools and techniques suggested in these standards. For thisobjective, dedicated efforts have been coordinated worldwide in writing this handbook. The result isthe first‐ever, comprehensive reference handbook that deals with the many unique RAMS issuesinvolved in the difficult environment of an operating railway system. This is of great relevance, giventhat the EU and some other parts of the world have already mandated the use of RAMS in legislationfor railway RAM and safety management systems. The handbook provides detailed guidance for thoseinvolved in the integration of the highly complex multidisciplinary systems that must performseamlessly to guarantee a safe and reliable railway transport system. It can be used as guidance inorder to get the RAM and Safety tasks accomplished successfully, especially in complex railwayprojects. The handbook includes 38 chapters authored by senior key experts from industry and well‐known professors and researchers from academia. The contributions are organized in two mainsections: Section 1, Basic concepts and prediction and estimation techniques; Section 2, RAMS inpractice and special topics. A graphical view of the highlights of the topics covered under each Sectionis presented below.
Practical and insightful descriptions are presented throughout the book in order to nourish RAMSpractitioners of any level, from practicing and knowledgeable senior RAMS engineers and managers tobeginning professionals and researchers. Each chapter has been written in an introductory style,providing the background and fundamentals, describing approaches to the practical issues, giving realworld and example applications, and concluding with a comprehensive discussion and outlook. Thecomprehensive contents and the involvement of a team of multidisciplinary experts provide confidencethat this handbook is of a high quality.
Standard Error in 2013vANSI/IEC/AAMI ES60601‐1:2005 & A1:2012
12
Larry George, [email protected] ANSI/IEC/AAMI ES60601‐1:2005 & A1:2012 “Medical Electrical Equipment, Oxygen‐Rich Environment” sub clause 11.2.2.1 b) 3) says, “…The time interval tc for checking the seals can be calculated as follows: Estimate the probability per time pe of an electrical failure that exceeds the values given in 11.2.2.1 a). Estimate the probability per time of an oxygen leak po:. Determine the accepted probability of dangerous failures per time r. Calculate tc = r/(0.5*pe*po).”
That formula doesn’t account for the ignition event sequence, leak before electrical failure, because P[X(leak) <Y(spark)] = po/(po+pe), not 0.5. However, that correction isn’t sufficient for the occurrences before inspectiontime tc. The probability of failure depends the end of time interval tc and the times to first leak and spark. Theformula gives too‐long time interval tc and failure probability greater than “accepted probability” r, becausefailure probability P[X < Y]*po*pe*tc is not the same as P[X < Y < tc]. Furthermore, electrical failures may berecurrent events so there could be at least one spark after O2 leak but before (end of) time interval tc. I.e.,assuming constant electrical failure rate pe, sparks could be events in a Poisson process.Workbook IECompar.xlsx computes alternative ignition probabilities in time interval tc[https://docs.google.com/spreadsheets/d/e/2PACX‐1vQ1plPzF2lusn8IQIsCm7VmiUmErIFXDcCLb6eCQ_eB07NyKFnjAegXC1zeWta42LDRrdPV‐3Cu0t5z/pub?output=xlsx or https://docs.google.com/spreadsheets/d/1VdJ_j84ZMcHlHh1EEm‐CLoUNUC0ckyWBvdfdHKRlUfo/edit?usp=sharing]:
0.5*po*pe*tc; (IEC 60601‐1)(po /(po+pe))*po*pe*tcP[X < Y < tc]: X and Y are independent, exponentially distributed times to first O2 leak and first electrical failureP[Leak AND at least one spark after leak AND before tc], integral from y = 0 to tc, (1–Exp(pe*(–tc + y)))*po*Exp[–po*y]dy (Poisson process sparks)Same as 3 and 4 with bivariate exponential distribution to represent shocks, simultaneous leak and electrical failure.
The correct alternatives 3 and 4 are the upper line, practically the same for chosen event rates. ANSI/IEC/AAMIEC60601‐1 sub clause 11.2.2.1 b) 3) should be corrected and perhaps recommend reporting when at least oneelectrical failure has occurred. The IEC and AAMI have acknowledged that the sub clause revision will beconsidered for edition 4 maybe in 2019. Meanwhile, the workbook IECompar.xlsx contains a risk‐of‐delayanalysis a la ISO 14971:2007.Numerical methods could be used, if event times have non‐exponential distributions. Send data [email protected], and I will test hypotheses, estimate distributions, and recommend inspection time.
Workshop Title: Risk Analysis for Autonomous Vehicles; Issues and Future Directions
13
Co‐Organizers: Professor Mohammad Modarres, Centre for Risk and Reliability (CRR), University of Maryland, College ParkDr. Mohammad Pourgol‐Mohammad, Safety Engineering and Risk/Reliability Division (SER2D), American Society of Mechanical Engineers (ASME)/Ducted Systems, Johnson Controls Inc.
Date: April 26, 2019, Venue: Kay 1‐2 Boardrooms, Kim Building of Engineering, University of Maryland, College Park
Background:In the past few years we have witnessed remarkable technology advancements and competitions inautonomous and connected transportation vehicles. These include major developments of self drivingelectric cars by Tesla, Google and Mobileye. The traditional car manufacturers have also entered thecompetition with their own designs such as Mercedes‐Benz’s self‐driving bus and Rolls‐Royce remote‐controlled cargo ship. Urban areas are bracing for a rapid infusion of these technologies into their roads inthe near future. More recently Beverly Hills City Council unanimously approved plans for replacement oftheir public transport vehicles with driverless vehicles. While technology development has been the primefocus of most recent technology innovations, we have witnessed only meager advances on issues of risk,reliability and resilience. A number of accidents have already occurred, for example on 14 February 2016 aGoogle self‐driving car while trying to avoid road sandbags struck a bus. Also, news media reported a fatalaccident involving a Tesla vehicle on autopilot on 7 May 2016 in Florida, which crashed into a tractor‐trailer.Most surveys show that while the public at large is extremely excited about these technologies, concernsover safety, software reliability, security, hacking/misuse, and licensing remained as paramount, especiallyamong educated and affluent individuals. Centre for Risk and Reliability (CRR), University of Maryland,College Park and Safety Engineering and Risk/Reliability Division (SER2D), American Society of MechanicalEngineers (ASME) organizes one‐day workshop on risk analysis of autonomous vehicles. The objective is togather the experts from academy, research institutes and industry to discuss the issue, identify the gapsand propose the directions for basic and applied researches. The conference will follow with acongressional briefing to update the policy makers about the risk of the technology and potential directionsfor necessary funding.The workshop will include following topics:‐Intellectual and laboratory resources in the related areas of‐Risk, reliability and resilience (R3) engineering, ‐Communications, information and network security, ‐Transportation and Road Infrastructure. ‐Robotic learning and Reasoning to Control Complex Behavior and Response ‐Legal, Ethical and Regulatory ‐Public Policy Initiatives ‐Energy and Environment Policies related to Autonomous Transportation Systems‐Educational Programs Related to the Autonomous VehiclesSponsors:‐Center for Risk and Study, University of Maryland, College Park‐Safety Engineering and Risk/Reliability Analysis Division, American Society of Mechanical Engineers‐Research Committee on Risk Technology (CRT), American Society of Mechanical Engineers
TECH SPOT: SAMPLE CRE QUESTIONS (Part 3)
1.Which of the following statements is NOT true?o Designing for reliability requires risk assessment of the producto Project schedule should not include tasks for risk assessmento Cost estimates for reliability testing should be included in the project budgeto Designing for reliability should include user hazard assessment
2. In which of the following product life cycle phases should product disposal issues be addressed?o Design/Developmento Concept/Planningo Operation/Repairo Wearout/Disposal
3. During which phase of the product life cycle should testing begin to validate the design?o Design/Developmento Production/Manufacturingo Concept/Planningo Operation/Repair
4. Which of the following is a metric to describe robust functionality?o Mean Time To Failureo Signal to Noise Ratioo Cost to Value Ratioo Mean Time To Repair
5. MTBF and MTTF are two reliability terms that are:o Synonymous with each othero Based on the use of the same lifetime distributiono Are applied differently. MTTF is applicable for maintainable systems. MTBF is only applicable for non‐maintainable / non‐repairable systems
o Are calculated using the second moments of the lifetime distribution.
6. Which of the following expressions is best used to describe the pattern of failures over time for repairable systems?o Rate of Occurrence Of Failureso Hazard rateo Mean Time To Failureo Mean Time To Repair
7. What is the most appropriate definition of Mean Time Between Failures (MTBF)?o The longest time period that a piece of repairable equipment failed in the record.o The average time period that a piece of repairable equipment takes to be repaired.o The average time period that a piece of repairable equipment is operational in the past 6 months.o The average time period that a piece of repairable equipment is operational.
8. Which element(s) make a complete reliability goal statement?o Function, probability, duration and environment.o Only need MTBFo Probability, useful life and wear out mechanismo Function, probability, shipping and environment
9. The equation, R(t) = e‐λt, is applicable during a product's:o infant mortality stage.o useful life stage.o wear‐out stage.o break‐in, useful life stage and wear‐out stages.
10. Which of the following best describes availability?o The ability of a product, when used under given conditions, to perform satisfactorily when called upono The probability that a product will perform the intended function, in the manner specified, for a particular period of timeo The probability that a failed system can be made operable in a specified interval of downtimeo The degree to which a product is operable and capable of performing its required function at any randomly chosen time during its specified operating time, provided that the product is available at the start of that period
14Answers will appear on ASQRRD blog by Sept 24