Reliability Raises Customer Expectations
Klaus M. Blache | October 1, 2021
Q: What does reliability mean?
A: It depends on who you ask and where you look. In Merriam-Webster, it’s defined as:
• the quality or state of being reliable
• the extent to which an experiment, test, or measuring procedure yields the same results on repeated trials.
I was taught that you shouldn’t define a word by using the same word in the defining sentence, but that’s a discussion for another day.
In psychological research, reliability refers to the consistency of a research study, survey, or repeatability of a measurement-related test. In any quantitative research you’re looking for a consistent measure of something. Your measurement choice should produce similar (reliable) results, even if conducted by different individuals at different times.
The ASQ (American Society for Quality, Milwaukee, asq.org) defines reliability as the probability that a product, system, or service will adequately perform its intended function for a specified period or will operate in a defined environment without failure. It can be observed as probability of success, durability, dependability, quality over time, and availability to perform a function.
SMRP (Society for Maintenance & Reliability Professionals, Atlanta, smrp.org) defines reliability analysis as a technique (with predictive tools) used to estimate the life of an asset (product). It’s usually expressed in terms of hours as mean time between failures (MTBF). Reliability analysis of systems/assets ensures delivery of good products or services. Analysis helps to identify and to avoid some catastrophic events due to failure of component(s).
A commonly used textbook, (Practical Reliability Engineering-5th edition, P. O’Conner and A. Kleyner, Wiley publication, 2012), states:
“The objectives of reliability engineering, in decreasing order of priority, are:
• To apply engineering knowledge and specialist techniques to prevent or reduce the likelihood or frequency of failures.
• To identify and correct the causes of failures that do occur, despite the efforts to prevent them.
• To determine ways of coping with failures that do occur if their causes have not been corrected.
• To apply methods for estimating the likely reliability of new designs, and for analyzing reliability data.
The reason for the priority emphasis is that it is, by far, the most effective way of working, in terms of minimizing costs and generating reliable products.”
The word reliability has been around since the early 1800s and there have always been applications, products, and inventions that required better reliability to be feasible. Such things as communications (from telegraph to internet and satellites), electrical/electronics (from vacuum tubes to semiconductors and computers), and military applications and consumer products that were failing too often. The standard approach for many years was “fix it when it breaks.”
In the 1950s, groups and some conferences began to focus on improving reliability. Some early examples are the Advisory Group on the Reliability of Electronics Equipment (AGREE) and the Institute of Electronic and Electrical Engineers (IEEE). Many professional societies added a reliability group to their organization, ISO standards added reliability components and, much later, the SMRP was formed by practitioners from eighteen companies.
The Certified Maintenance and Reliability Professional (CMRP) exam was developed in the late 1990s during my two-year tenure as SMRP chair. Wallodie Weibull’s work gained popularity in the 1960s. After successfully putting Weibull concepts to practice, Dr. Robert Abernathy eventually authored The New Weibull Handbook.
Weibull analysis, now used around the globe, is a statistical methodology used to perform life data analysis to predict failure trends. We use the handbook and associated SuperSMITH software (authored by Wes Fulton, weibullnews.com) and offer this as a course in our professional-development certification.
As reliability efforts evolved, numerous insights and statistical contributions were established. Several handbooks were published by the U.S. Navy, U.S. Army, and SAE (Society of Automotive Engineers). The bathtub curve was replaced by multiple failure patterns (showing much higher non-age-related failure) from the F.S. Nolan and H.F. Heap United Airlines study (1978). These contributions, and many more, all were part of the reliability growth path.
If you look at reliability, the list of what can be considered is extensive—predictive technologies, condition-based maintenance, life-cycle costing/purchasing, PM optimization (deciding what PM tasks are value added, what type of maintenance to perform, and how often), failure modes and effects analysis, reliability modeling and predictions, planning and scheduling, reliability statistics, and overall asset management.
Because of reliability, the bar has been raised. I’m referring to better reliability associated with what you do, what you produce, transportation, products, and related warranties. Remember that reliability can also be viewed as sustaining quality and original functionality over time.
Reliability is observed when:
• your car starts when you turn the key
• your flight departs and arrives on time
• your package arrives on time
• spare parts are available when needed
• clean and safe water comes from your faucet every time you turn it on
• medication at the pharmacy is properly dispensed
• steel consistently contains the right amount of carbon
• machines perform within specifications
• power plants produce electricity without disruptive power spikes/surges
• your internet connection is consistent
• your favorite meal at your favorite restaurant is prepared as ordered every time
• stated hours of battery life are attained or exceeded
• production quality is accomplished within required limits every day
• software correctly calculates requirements
• team members perform their standardized work according to established procedure.
Somewhere in there also is infrastructure such as bridges and roadways. Basically, reliability covers about everything.
In a work setting, improving reliability benefits safety, quality (as operational stability increases), throughput, and cost. Reliability tools have helped shorten product- development times, enabled numerous items to improve and, overall, made assets and products more dependable and safer. EP
Based in Knoxville, Dr. Klaus M. Blache is director of the Reliability & Maintainability Center at the Univ. of Tennessee, and a research professor in the College of Engineering. Contact him at email@example.com.