Jim McLinn Talks about RMMR @ Accendo Reliability

Tim Rodgers interviews Jim McLinn, chair for ASQ’s Reliability, Maintenance & Managing Risk Conference, about his background and the upcoming Reliability, Maintenance & Managing Risk Conference (RMMR).

In this episode, Tim and Jim discuss:

  • As upcoming chair, Jim discusses the program details
  • Changes, themes, and issues that are attracting more interest
  • Who will be attending
  • Why you should attend

Click on the link for the interview: https://accendoreliability.com/podcast/dtk/dtk-jim-mclinn-consultant-2/

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SLIDES AND VIDEO OF “How Aging Laws Influence Parametric and Catastrophic Reliability Distributions”

Thu, Aug 8, 2019 , Alec Feinberg presented “How Aging Laws Influence Parametric and Catastrophic Reliability Distributions”

In this talk we describe how physics of failure aging laws influence reliability distributions, not only the type of distribution, but the rate of failure as it relates to the aging rate. We illustrate how one can predict parametric failure rates based on the physics of failure aging laws when known.

below a link to the recorded video of the webinar.

A number of statements are concluded. We show that when a manufactured part has a key parameter that is distributed normally, and the physics of failure aging for this key parameter ages in log-time, its failure rate is lognormally distributed.

When the physics of failure is a power law, we illustrate how the Weibull beta and eta can be obtained from the physics of failure aging law exponent and amplitude in the parametric case. We use the example of creep, and make direct comparisons between the full creep ‘rate’ curve and the bathtub curve. Although the example of creep is used many aging laws have a similar power law forms and can be applied in a similar manner. Although we work though parametric failure rate statistics, one can relate it to the catastrophic case.

Presentation: https://www.dfrsoft.com/How%20Aging%20Laws%20Influence%20Reliability%20Distributions%20DfRSoftware.pdf

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ASQ RRD series webinar: Testing – Techniques and Examples – Structural Integrity

ASQ RRD series webinar: Testing – Techniques and Examples – Structural Integrity

https://attendee.gotowebinar.com/register/3038076372846221837

on Oct 10, 2019 12:00 PM EDT

presenters: Timothy M. Hicks, PE and Roch J. Shipley, PhD, PE, FASM

Synopsis:

In the broadest sense, structural integrity is ensured in the design phase by a thorough review of a product’s intended use and foreseeable misuse. Testing is performed for verification as necessary. Materials of construction are typically reviewed to be sure they are appropriate. Manufacturing process controls are developed to ensure that the design intent is met. Documentation for operation, maintenance, and inspection, including appropriate warnings, are developed for users and service personnel.

The emphasis on each of the above areas depends on the application and previous experience. The testing methods utilized for design verification and validation are also critical when it comes to analyzing failures, which makes the content of this webinar appealing to both designers and problem solvers.

The focus of this presentation will be to discuss the different aspects of structural integrity testing and to provide an overview of processes utilized to ensure a successful and safe design, to provide guidance to get it right the first time, avoiding any need for failure analysis.

Professional Analysis and Consulting, Inc. is dedicated to meeting the engineering, scientific, and technical consulting needs of manufacturers, insurance companies, and law firms throughout the U.S. and the world. We have extensive professional experience in various disciplines to assess physical, laboratory, and documentary evidence, and to provide appropriate analysis and testing. We strive to solve complex and challenging problems with integrity by applying our skills and expertise to discover the root cause of failures.

Professional Analysis and Consulting, Inc. is dedicated to meeting the engineering, scientific, and technical consulting needs of manufacturers, insurance companies, and law firms throughout the U.S. and the world.  We have extensive professional experience in various disciplines to assess physical, laboratory, and documentary evidence, and to provide appropriate analysis and testing.  We strive to solve complex and challenging problems with integrity by applying our skills and expertise to discover the root cause of failures.

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ASQ RRD series webinar: Disponibilidad (Availability)

ASQ RRD series webinar: Disponibilidad (Availability)

Sáb., 5 de Oct. de 2019 9:00 – 10:00 EDT

https://attendee.gotowebinar.com/register/2780662009203611659

En esta sesión Dr Jorge Romeu nos compartirá su conocimiento sobre este tópico esencial en mantener servicio y confianza. Independientemente si la organización presta un servicio, produce, o le otorga un producto la expectativa es satisfacer lo que se espera del producto o Servicio. En muchos casos las exceptivas también están reguladas como por ejemplo en la industria automotriz, aeronáutica, petroquímica, la industria de productos para la salud, la industria financiera, la industria del cuidado de la salud, y muchas otras. Más recientemente proveedores de servicios virtuales que aumentan cada día, gracias a la capacidad de computación en la nube (cloud computing) son responsables de mantener la disponibilidad de servicio prácticamente 100% en su tiempo de servicio. Conceptos asociados con Disponibilidad son esenciales para los profesionales ejerciendo en las áreas de Seguridad y Confiabilidad, y prácticamente para las personas que adquieren servicios y productos funcionales.

Acerca de nuestro panalista
Jorge Luis Romeu es un estadístico industrial. Ha trabajado por 14 años como profesor de Estadísticas y Matemáticas en la Universidad del Estado de Nueva York (SUNY), y actualmente es Investigador de la SUNYIT, así como Consultor del Centro de Confiabilidad (Reliability) de Sistemas RIAC (Reliability Information Analysis Center).

Picture © B. Poncelet https://bennyponcelet.wordpress.com
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ASQ RRD series webinar: Implementing DFMEAs and PFMEAs Using the new AIAG-VDA FMEA Handbook

ASQ RRD series webinar: Implementing DFMEAs and PFMEAs Using the new AIAG-VDA FMEA Handbook

https://attendee.gotowebinar.com/register/3538508094229234445

Thu, Sept 12 2019 12:00 PM – 1:00 PM EDT

presenter: Richard Harpster

The new AIAG-VDA FMEA Handbook has now been officially released. The handbook was anticipated to represent a harmonization of the FMEA methodologies found in the current AIAG and VDA FMEA manuals. However, a close review of the published handbook reveals that the core FMEA methodology found in the handbook is an adoption of the software based VDA FMEA methodology first released for use in 1996. For AIAG FMEA subscribers this change is significant on multiple levels.

Along with the core FMEA methodology change, users of the handbook will also find considerable changes in the rating systems as well as the replacement of RPN (Risk Priority Number) with AP (Action Priority).

Using the DFMEA and PFMEA examples provided in the handbook, the webinar will provide the following information:

  1. History of software based VDA FMEA methodology which is the core FMEA methodology found in the handbook
  2. How to construct DFMEA using handbook methodology and how it differs from DFMEA created using DFMEA method found in the AIAG 4th Edition FMEA manual
  3. Why the number of DFMEAs and DVPs required using the handbook DFMEA methodology may significantly increase for complex products
  4. Why some companies currently using Excel will find if very difficult if not impossible to implement the handbook DFMEA methodology using Excel
  5. How to construct PFMEA using handbook methodology and how it differs from PFMEA created using PFMEA method found in the AIAG 4th Edition FMEA manual
  6. Common problems typically experienced by current users of VDA FMEA methodology when attempting to create DFMEAs and PFMEAs and some tips that may help in overcoming them.
  7. Review of rating system changes
  8. Introduction to Action Priority (AP)

Picture © B. Poncelet https://bennyponcelet.wordpress.com

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SLIDES AND VIDEO OF “Software FMEA”

On Thu, Jul 11, 2019, Richard Harpster presented “Software FMEA”

below a link to the recorded video of the webinar.

The Design FMEA (DFMEA) has been used for many years to manage hardware design risk.  This has led to improvements is hardware designs and increased efficiency in their development.  Unfortunately, the same cannot be said for using the DFMEA for managing software design risk.

 The purpose of this webinar is to describe how to use the DFMEA to manage risk related to the software design that controls the hardware as well as software design when no hardware is involved.  The expected benefits of the use of Software DFMEAs is improved software designs and decreased software development time.  The webinar will cover:

1. Definition of software related risk and how it is eliminated or reduced to acceptable levels;
2. Four objectives of the Software DFMEA;
3. Software DFMEA basics;
4. Using Software DFMEAs with Scrum.

Click on the picture for the presentation

 

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RMMR Conference – October 15-16, 2019 San Antonio, TX – Early bird price ends at 1st of August

Register to RMMR now!

Keynote speaker:

Dr. Ali Mosleh:
Distinguished Professor and Evelyn Knight Chair in Engineering at UCLA
Former Director of the Center of Risk and Reliability at the University of Maryland
Elected to the US National Academy of Engineering
Fellow of SRA and ANS
Served on the U.S. Nuclear Waste Technical Review Board

Rest of program coming soon…
http://www.asqrd.org/RMMR/ 

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TECH SPOT: SAMPLE CRE QUESTIONS (PART 6)

Answers to CRE questions in June 2019 Newsletter

1. Consider the regression results from the regression of Y against X for 50 observations:Y = 5.0 – 1.5 X
The standard error of the estimate is 0.40 and the standard error of the coefficient is 0.45.
The predicted value of Y if X is 10 is:
a.-10
b. 4.5
c. 10
d. 20

2. Which of the following is an assumption of linear regression? The:
a. expected value of the residuals is zero.
b. residuals are normally distributed.
c. variance of the residuals is constant across the range of the data.
d. All of the above

3. Consider the following graph of residuals and the regression
line from a time-series regression:

These residuals exhibit the regression problem of:
a. homoskedasticity.
b. multicolinearity.
c. autocorrelation.
d. heteroskedasticity.

4. Which of the following is a potential remedy for multicollinearity?
a. Increase the sample size.
b. Take first differences of the dependent variable.
c. Add dummy variables to the regression.
d. Omit one or more of the collinear variables.

5. Products that fail a functional test gate get reworked and get sent through this functional test again. Some products go through this cycle multiple times. The manufacturing area is deciding to implement some type of SPC chart to track the number of times each product fails this functional test before being accepted and shipped. Which type of SPC Chart would you suggest to be used?
a .C-Chart
b. Individuals and Moving Range Chart
c. P-Chart
d. NP-Chart

6. An MBA class project requires your team to estimate the proportion of people that will vote in the next election. You have no prior knowledge of how many are expected to vote. In order to assure an estimate that falls within five percentage points of error, how many people do you and your team have to survey to achieve this estimate with 95% confidence (assume Normal approximation applies)?
o 385 people
o 271 people
o 73 people
o a minimum of 30 people is recommended

7. Product from three production lines is mixed in a final packaging area. Line A is known to be 2% defective, Line B is 4% defective, and Line C is 6% defective. Both Line B and Line C operate at half the manufacturing rate of Line A. What is the expected defect rate of the final shipped material?
o 3.5% defective
o 4% defective
o 6% defective
o 12% defective

8. Which of the following are measures of central tendency?
o Mean and Mode
o Mean, Median, Percentile
o Mean, Median, Mode
o Mean, Percentile, Mode, Median

9. The statistical technique that allows estimates about population parameters with a known level of certainty is called:
o Control Limits
o Confidence Intervals
o Specification Limits
o Action Limits

10. Five samples of a product are tested for power after a reliability testing to assess any degradation. The products measured 10, 10.1, 10.5, 9.8, and 10.7 watts. If the average wattage is greater than or equal to 10 watts at 95% confidence level, we can conclude that the degradation has occurred. Calculate the appropriate statistics and conclude.
o 1.329, No degradation
o 2.132, No degradation
o 1.329, Degradation has occurred
o 2. 132, Degradation has occurred

Picture © B. Poncelet https://bennyponcelet.wordpress.com

Posted in General

ASQ RRD series webinar: How Aging Laws Influence Parametric and Catastrophic Reliability Distributions

ASQ RRD series webinar: How Aging Laws Influence Parametric and Catastrophic Reliability Distributions

https://attendee.gotowebinar.com/register/1268716971598298125

Thu, Aug 8, 2019 12:00 PM – 1:00 PM EDT

presenter: Alec Feinberg

In this talk we describe how physics of failure aging laws influence reliability distributions, not only the type of distribution, but the rate of failure as it relates to the aging rate. We illustrate how one can predict parametric failure rates based on the physics of failure aging laws when known.

A number of statements are concluded. We show that when a manufactured part has a key parameter that is distributed normally, and the physics of failure aging for this key parameter ages in log-time, its failure rate is lognormally distributed.

When the physics of failure is a power law, we illustrate how the Weibull beta and eta can be obtained from the physics of failure aging law exponent and amplitude in the parametric case. We use the example of creep, and make direct comparisons between the full creep ‘rate’ curve and the bathtub curve. Although the example of creep is used many aging laws have a similar power law forms and can be applied in a similar manner. Although we work though parametric failure rate statistics, one can relate it to the catastrophic case.

Picture © B. Poncelet https://bennyponcelet.wordpress.com

Posted in General

SLIDES AND VIDEO OF “Systems Theoretic Process Analysis”

On JUN 6, 2019, John Thomas presented “Systems Theoretic Process Analysis”

below a link to the recorded video of the webinar.

This webinar will introduce Systems Theoretic Process Analysis (STPA), a new systems approach for more effective design and analysis of large complex systems. The interdisciplinary approach is designed to capture often-overlooked issues such as incomplete, incorrect, or missing requirements, flawed automation, unanticipated interactions among components or subsystems, and unexpected human interactions. Although STPA can be used for safety analysis, it can also be used for other goals such as quality and security and it can be used to guide initial development efforts under design uncertainty when some of the most critical decisions are made. While STPA is relatively new, it is now being used in many industries including aviation, spacecraft, automotive, nuclear, petrochemical, and defense.

Click on the picture for the presentation

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