Your Reliability Engineering Professional Development Site
This article series by Ray Harkins explores the tools essential for quality or reliability engineers and managers. Topics include statistical process control, reliability engineering, root cause analysis, and business finance.
One of the more confusing distinctions for quality professionals, especially those working within one of the quality management standards such as IATF 16949 or ISO 13485, is the difference between a Corrective Action Request (CAR) and a Preventive Action Request (PAR). [Read more…]
Metropolises in 2020, like New York and Shanghai, disconcertingly resembled London in 1831, in that a strange new disease passed through the population leaving in its wake confusion, grief and death. 2020 was beginning of Covid-19; 1831, Cholera. [Read more…]
If you’ve worked around the fields of reliability or quality for any length of time, you’ve certainly encountered and have likely assembled the humble yet mighty histogram. This specialized bar graph is one of the most common starting points for analyzing continuous data. It not only portrays the frequency of numerical data across its range of values, but also provides hints at the data’s underlying probability distribution. [Read more…]
My limited formal training about America’s Industrial Revolution came in tenth grade history class. And my few remaining recollections of my studies from that era include characters like James Watt and Alfred Nobel, and their inventions, the steam engine and dynamite. Oh, and how could I forget Eli Whitney and his cotton gin?
Now 40 years later, my interest in manufacturing has grown far beyond these elementary school lessons, and the Industrial Revolution continues to intrigue me. Yes, this era was rife with its inventors and their inventions. But the enduring gains from this era were the philosophies of manufacturing that transcended the specific inventions. [Read more…]
Consider the following two targets:
Shooter #1 and Shooter #2 both fired 15 rounds into their respective targets. Who is the better marksman? [Read more…]
The “D” is 8D stands for “disciplines”, and the 8D process is a problem-solving methodology employing eight sequential disciplines or steps that can be applied to a wide range of industries, situations, and disciplines.
The 8D process was developed in the late 1980’s by the Ford Motor Company to give its engineers a standardized method for dealing with design and manufacturing problems. Ford’s predecessor to 8D was called “TOPS”, Team Oriented Problem Solving. This is a fitting name to the methodology since it strongly emphasizes a team-based approach. In fact, the first of the eight D’s is “Assemble the Team”. [Read more…]
No discussion of root cause analysis is complete without a review of 5 Why Analysis. This brainstorming technique was developed by Japanese industrialist and founder of the Toyota Motor Corporation, Sakichi Toyoda, and used throughout Toyota since the 1930’s. As the wave of continuous improvement moved through the aviation industry in the 1970’s, the auto industry in the 1980’s, and the healthcare industry in the 1990’s, 5 Why Analysis moved along with it. The tool’s simplicity is what makes it so adaptable in the safety, quality, engineering and production disciplines. [Read more…]
One excellent starting point of the investigation phase of a root cause analysis is the comparison of the product measurements to the available process data. With an effective traceability system, you can define a relatively short time range in which the defective parts were manufactured. Once these “fence posts” are identified, use them to examine the available process data such as the recorded pressures, temperatures, times, and speeds. [Read more…]
Anyone who has worked around the fields of reliability or quality has certainly bumped into “standard deviation” – a statistic that measures the dispersion within a group of data. [Read more…]
Anyone who knows me knows I love hearing from the students who take my online classes. One reason is that they ask the most challenging questions. Here’s a recent question from a student taking my “Process Capability Analysis” class: [Read more…]
I remember the feeling I had as child when I first heard about Rudolf. I was certain that Santa had eight reindeer. Then suddenly one day, I was wrong. Somehow a ninth reindeer had appeared on the scene and forever altered my view of St. Nick’s tiny sleigh. This feeling of cognitive dissonance recurred years later when I first heard about Cpm – the “Rudolf” of capability indices. I knew about Cp and Cpk. I knew about Pp and Ppk. And I thought that was it. But once again, the mental rug was yanked from beneath me when abruptly I realized there was more. [Read more…]
Several years ago, I was trying to fill a quality engineer’s position within my department. One person’s resume caught my attention. Under a section titled “Areas of Expertise”, it read “Quality Engineering Statistics”. “My gosh”, I thought, “We’ve got to call this guy for an interview. [Read more…]
I recently read the results of a AAA survey where Americans were asked to rate their own driving abilities. 73% of those surveyed considered themselves “better-than-average” drivers. Obviously only 50% of the drivers can actually be better than average. So it follows that at least 23% of those surveyed are mis-estimating their own skills.
This over-confidence in one’s abilities seems to find its way into all sorts of areas … including process capability analysis. Everyone who’s been around manufacturing for any length of time has certainly heard of Cp and Cpk. Most of them know that “higher is better” when it comes to these indices. And many will nod their heads and smile when you suggest that Cpk and Ppk account for centeredness, whereas Cp and Pp do not. But only a small percentage of manufacturing professionals can cogently answer the question, “What is Process Capability analysis?” [Read more…]
