On Thu, Mar 11,  Matthew Hu presented “ASQ RRD series webinar: Robustness Thinking in Design for Reliability – A Best Practice in Design for Reliability”

Abstract
Reliability is one of the most important characteristics of an engineering system. Reliability can be measured as robustness over time as a leading key performance indicator (KPI). Robustness thinking is essential to improve quality and reliability proactively by factoring the activities of design for reliability. Nothing can be substituted for thinking. Early robustness development in manufacturing can reduce the variability of those processes with valuable benefits to manufacturing yields, cycle time and costs. Product Development has a huge impact on revenue stream, reliability. It is most cost-effective and less time-consuming to make design insensitive to uncontrollable user environments in upfront design phase. Robustness development in Design for Reliability (DFR) process provides benefits in reduction of early-on physical testing and traditional test-fix-test cycles. Robustness achieved early in development enables shorter cycle times in the later design phases.

Objectives of the presentation
• Define robustness
• Explain product development using Robust Engineering versus traditional product development
• Explain Robust Design for Reliability
• Define Objective Function, Basic Function, and Ideal Function
• Explain how Ideal Function and Two-step Optimization lead to robust technology development and achieve “Better, Cheaper, Faster” product development
• Explain how to conduct a preliminary robustness assessment
• Explain the value of robustness assessment
• LiDar case study in robust autonomous driving technology development

Important Takeaway
• Make design insensitive to uncontrollable user environment (Noise)
• Early development of robustness is key to proactive quality and reliability Improvement
– Capture, front load noise and manage noise
– Gain control of your product performance
– Optimize robustness – avoid all failure modes
• Apply Robust design principles at early stages of product design to “forecast” problems and take preventive action.


PRESENTATION

ASQ RRD series webinar: Studying Fractures – Recognizing and Understanding Failure Modes

Thu, Jul 8, 2021 12:00 PM – 1:00 PM EDT

Presenter: Shane Turcott

https://register.gotowebinar.com/register/2524763884672852494

Abstract
Investigating equipment failures is one of the key roles of the reliability team. Instead of guessing how a part failed, its fracture features can be studied and the failure mode diagnosed. This talk will introduce how mechanical fracture features of steel failures can be recognized, then how diagnosis can help direct an RCA investigation. Brittle fracture will be used to illustrate the logic sequence applied in diagnosing, understanding why something failed and applying this information towards developing effective solutions.

BIO
Shane graduated with his B.Eng and M.A.Sc in Materials Engineering from McMaster University, Canada. He has performed failure analysis for various employers before founding Steel Image in 2009. Steel Image which is a lab-based metallurgical engineering company supporting reliability efforts by providing failure analysis and on-site material evaluations. He is the past Ontario Chair of the American Society of Materials, author of ‘Decoding Mechanical Failures’ and is the host of the ASM Materials World Class Series.

ASQ RRD series webinar: Fault Tree Analysis as a Means to Promote Safety

Thu, Jun 10, 2021 12:00 PM – 1:00 PM EDT

Presenter: Jennifer B. Akers

https://register.gotowebinar.com/register/7448468213051240460

Designing safe products and systems is critical to reduce accident risk and minimize product liability. There are various reliability and quality analysis methodologies used to ensure safety including risk analysis techniques such as fault tree analysis (FTA), failure mode and effects analysis (FMEA), and others. This webinar focuses on providing an introductory look at FTA and its role in promoting safety. We review basics about fault tree analysis, including what it is, its history, its uses and advantages. A thorough review of qualitative and quantitative FTA results, including minimal cut sets (MCS), quantitative metrics such as unavailability, and importance measures, is included. The presentation concludes with guidance on how FTA qualitative and quantitative results can be used to design inherently safer products and systems.

Jennifer Akers is an Education Development Specialist with Relyence Corporation. She is responsible for training services and technical support offered by Relyence. Jennifer has a Bachelor of Science degree in Chemical Engineering from Lafayette College. Jennifer has over 20 years of experience in the reliability and quality fields. Her work has spanned software development, quality assurance, technical support, and education and training for reliability and quality software tools. She has co-authored several papers and tutorials on topics such as closed loop corrective action, fault tree analysis, and warranty analysis.

ASQ RRD Series Webinar: Evolution Of Electrolytic Capacitors- Why A Reliability Engineer Should Know This:

Thursday May 13th, noon – 1pm Eastern Time


Presenter: Greg Caswell

https://attendee.gotowebinar.com/register/6016712758572885776

 Why would a Reliability practitioner need to know this? Where there is electricity, that is, electrons moving collectively, there is capacitance. In systems, especially complex systems, changes in capacitance, or the incidental formative presence of an undesired capacitance can impose a spurious system response which could lead to a functional failure. In the grand scheme of things, it would be advantageous for the reliability practitioner to have a perspective on capacitance. This presentation provides one such viewpoint.

Electrolytic capacitors have long been identified as a weak link for long term high reliability applications.  However, capacitor manufacturers have made significant improvements to the materials and manufacturing processes to enhance their reliability.  This webinar will discuss those changes, provide insight into the various failure mechanisms for electrolytic capacitors and describe appropriate accelerated tests to validate performance.

We will take a deeper dive into the methodologies utilized to improve capacitor performance, e.g. foil purity and electrolyte volume.  We will also discuss, from a reliability perspective, the impact of changing to a higher temperature electrolyte (from ethylene glycol to DMF, DMA and GBL) and also changes in the bung material (from butyl to EPDM).

There are several environmental factors involved in the aging of electrolytic capacitors.  Electrolyte loss due to drying out and leakage current due to oxide degradation are thermally related as is the self-heating associated with ripple current.  The impact of the applied voltage level is also a driver as it can cause leakage current increases as well.  All of these issues result in a capacitance decrease, an increase in ESR, and a change to the dissipation factor.  Many other failure mechanisms associated with manufacturing will also be discussed.

Examples of calculations for life expectancy will be shown to demonstrate the effects of applied voltage, rated temperature, ripple current, and the endurance factor coupled with the application usage profile. 

Bio

•        Greg has over 50 years of experience in electronics manufacturing focusing on failure analysis and reliability. He is passionate about applying his unique background to enable his clients to maximize and accelerate product design and development while saving time, managing resources, and improving customer satisfaction.

•        Greg, a Lead Consulting Engineer for Ansys, is an industry recognized expert in the fields of SMT, advanced packaging, printed board fabrication, circuit card assembly, and bonding solutions using nanotechnology. He has been well-regarded as a leader in the electronics contract manufacturing and component packaging industries for the past 50 years. Prior to joining Ansys Greg was the Vice President of Engineering at Reactive Nanotechnology (RNT), where he led application development for the RNT Nanofoil® and ensured a successful transition of product technology to Indium Corporation. His previous appointments include Vice President of Business Development for Newport Enterprises, Director of Engineering for VirTex Assembly Services, and Technical Director at Silicon Hills Design. He has presented over 270 papers at conferences all over the world and has taught courses at IMAPS, SMTA and IPC events.  He helped design the 1st pick and place system used exclusively for SMT in 1978, edited and co-authored the 1st book on SMT in 1984 for ISHM and built the 1st SMT electronics launched into space.  Look for his new book entitled “Design for Excellence in Electronics Manufacturing” to be published in April 2021.

•        B.A., Management (St. Edwards University)

•        B.S., Electrical Engineering (Rutgers University)

ASQ RRD series webinar: Análisis de las Aplicaciones de Modelos Estadísticos para entender Covid-19

Mar., 2 de Mar. de 2021 12:00 – 13:00 EST

https://register.gotowebinar.com/register/1119714467326028304

Con la perspectiva de salud pública, Dr. Jorge Romeu va a compartir un sumario de su análisis de las contribuciones a la investigación y avance hechas por varias organizaciones que han usado modelos estadísticos con el fin de ayudar a entender Covid-19 y sus efectos. Es esta presentación Dr. Romeu presentara el estado de su análisis que ha conducido de Marzo 4 2020 a Febrero 3, 2021. Dr Romeu propone incrementar el uso de herramientas estadísticas en la profesión e investigación de la salud pública.

Jorge Luis Romeu es estadístico industrial especializado en Calidad y Confiabilidad. Es Profesor Emerito de la Universidad del Estado de Nueva York (SUNY), tras 14 años de enseñar matematicas y estadisticas. Romeu es Fellow de la Royal Statistical Society, miembro de ASA (American Statistical Association) y IASI (Inter American Statistical Institute), Senior Member de la American Society for Quality y mantiene certificaciones de Reliability (confiabilidad) y Quality (Calidad). Dr. Romeu es autor del libro “A Practical Guide to Statistical Analysis of Material Property Data”, de estadísticas para ingenieros, y dirige el Proyecto Juárez Lincoln Marti, de Educación Internacional (http://web.cortland.edu/matresearch).

El evento califica para 0.1 RU crédito profesional si usted atiende, estos se distribuyen en su correo electrónico (e-mail) que usa para registrarse en este evento, y se manda días después del evento.

ASQ RRD Series: Analysis of Survival Data in Engineering, Business, and Medicine

Thu, Apr 8, 2021 12:00 PM – 1:00 PM EDT

Presenter: Dr. Wayne Nelson

https://register.gotowebinar.com/register/6305580850384875023

This talk is an introduction to survival data analysis in engineering, business, and medicine. It presents basic concepts including the Weibull distribution, its age dependent failure rate, and simple probability plots. The talk shows applications to engineering, business, and medicine,, including

• The reliability of products designed and manufactured by engineers (e.g., toaster life).
• The distribution of time to a bank’s loss of bank accounts and TV service’s loss of subscribers.
• The life distribution of patients under treatment and life of medical devices (e.g., heart pacemakers).
The life distribution of patients and products, e.g., median life, % surviving 5-years or warranty.
• Whether a product failure rate increases or decreases as the population ages. This information is used to determine whether preventive replacement of old units in service reduces in-service failures.
• A prediction of the number of population failures in a coming month, quarter, or year.
During product development, a prediction of the improvement in product life that would result from eliminating one or more failure modes.
• Comparisons of 1) medical treatments, 2) business policies, and 3) product designs, vendors, materials, operating environments, manufacturing methods, etc.


SPEAKER. Dr. Wayne Nelson is an expert on reliability data analysis and accelerated testing. He worked at GE Research & Development for 24 years, and now consults privately. He is a fellow of the Amer. Society for Quality, the Institute of Electrical and Electronic Engineers, and the Amer. Statistical Assoc. ASQ awarded him the Shewhart and Shainin Medals and the Hahn Award for his lifetime achievements, and the Brumbaugh and Youden Prizes for articles on innovative methodology. He was the second person to receive the Lifetime Achievement Award of the 2,000-member IEEE Reliability Society for his innovative contributions to reliability methodology and reliability education.

ASQ RRD series webinar: Robustness Thinking in Design for Reliability – A Best Practice in Design for Reliability

Thu, Mar 11, 2021 12:00 PM – 1:00 PM EST

Presenter: Matthew Hu

https://register.gotowebinar.com/register/2625796907172545805

Abstract
Reliability is one of the most important characteristics of an engineering system. Reliability can be measured as robustness over time as a leading key performance indicator (KPI). Robustness thinking is essential to improve quality and reliability proactively by factoring the activities of design for reliability. Nothing can be substituted for thinking. Early robustness development in manufacturing can reduce the variability of those processes with valuable benefits to manufacturing yields, cycle time and costs. Product Development has a huge impact on revenue stream, reliability. It is most cost-effective and less time-consuming to make design insensitive to uncontrollable user environments in upfront design phase. Robustness development in Design for Reliability (DFR) process provides benefits in reduction of early-on physical testing and traditional test-fix-test cycles. Robustness achieved early in development enables shorter cycle times in the later design phases.

Objectives of the presentation
• Define robustness
• Explain product development using Robust Engineering versus traditional product development
• Explain Robust Design for Reliability
• Define Objective Function, Basic Function, and Ideal Function
• Explain how Ideal Function and Two-step Optimization lead to robust technology development and achieve “Better, Cheaper, Faster” product development
• Explain how to conduct a preliminary robustness assessment
• Explain the value of robustness assessment
• LiDar case study in robust autonomous driving technology development

Important Takeaway
• Make design insensitive to uncontrollable user environment (Noise)
• Early development of robustness is key to proactive quality and reliability Improvement
– Capture, front load noise and manage noise
– Gain control of your product performance
– Optimize robustness – avoid all failure modes
• Apply Robust design principles at early stages of product design to “forecast” problems and take preventive action.

1.  A stand‐by redundant system uses two identical units. The failure rate of each unit is 0.0007 failures per hour. What is the system  reliability for 200 hours (Assume the sensing and switching reliability is 0.9).

A.0.991      B. 0.983      C. 0.979         D,  0.965

2. Which of the following is true if all the subsystems in a series system have a constant failure rate?

A. The failure rate of the system is constant

B. The failure rate of the system will increase as more subsystems are added

C. The failure rate of the system is the sum of the subsystem failure rates

D.  All of the above

3. What is the reliability of this system?

A. 0.9191

B. 0.9244

C. 0.9297   

D. 0.9856

4. A parallel system has three subsystems each with a reliability of R.

The system reliability can be calculated as

A. 3R

B. R3

C.  1 ‐ (1 ‐ R)3  

D.  1 ‐ (1 ‐ R3)

5. To place confidence limits on a prediction which of the following is true?

A. The Chi Square distribution is used

B. The  F distribution is used

C. The t distribution is used

D.  A prediction is probabilistic, therefore confidence does not apply

6. 50 electronic devices have been tested for 3,000 hours without failures.

What is the approximate MTBF of this   device at 90% lower confidence ?

A. 65150 hours  

B. 25500 hours 

C.  6500 hours 

D. 6500 hours

7. Which one is not the reliability prediction technique?

A. Weibull plot

B. Duane plot  

C.  Uniform Precision Design   

D. Fix effectiveness Model?

8. In success testing, how many samples need to operate for one lifetime without failure to demonstrate 95% confidence with  99% reliability?

A. 298 samples   

B.  90 samples   

C.   59 samples   

D.   458 samples

9. The following data is used for thermal stress evaluation of ICs using Arrhenius Equation.

What is the acceleration factor ?

Wearout Activation Energy is  in eV

  • Ea = 0.5 eV k is Boltzmann’s Constant,
  • 8.617 x 10-5 eV / K
  • T1 is Temperature in degrees C = 70 deg C (343⁰K)
  • T2 is Junction temperature during test in degrees C= 125 deg C  (398⁰K)

A. 10.4

B.   5.2     

C.  9.5   

D.   10.0

10. The reliability of a system consisting of two units in parallel is 0.96.

If the reliability of each component is increased by 10%, what is the percentage increase in the reliability of the system?

A. 10%

B.  5%  

C.  3.33% 

D.  2.66%

On 14th of January 2021, Bob Deysher presented: ASQ RRD Series: Auditing ISO 9001 Clause 8.3, Design and Development of Products and Services (Risk Based Thinking)

Internal auditing is a requirement in ISO 9001:2015. Its purpose is to assess if processes are maintained and effective. This webinar will review how internal auditing, as well as the use of risk based thinking (RBT), can add value to the process of design and development of product and services. Focus will be on project reviews as well as verification and validation requirements providing examples of areas that had shown prior weaknesses. It is also recognized that industry specific standards such as aerospace (AS 9100) and automotive (IATF 16949) have added additional design and development requirements. These requirements will need to be audited if the organization registered to the industry specific quality management system.