Air gauging relies on a law of physics that states flow and pressure are directly proportionate to clearance and react inversely to each other. As clearance increases, air flow also increases, and air pressure decreases proportionately. As clearance decreases, air flow also decreases, and air pressure increases.

This is accomplished by having a regulated air flow that travels through some type of restriction, such as a needle valve or jeweled orifice, and then through the nozzle in the air tool. As the obstruction (i.e., workpiece) is brought closer to the nozzle, air flow is reduced and the back pressure is increased. When the nozzle is completely obstructed, the flow is zero, and the back pressure is equal to the regulated air. Conversely, when the nozzle is open to the atmosphere, air flow is at a maximum, and the back pressure is at a minimum.

Donald J. Wheeler has been awarded the Deming Medal by the American Society for Quality (ASQ) for “the propagation of Dr. Deming’s ideas throughout the world through his numerous books and seminars on quality management and statistical quality improvement.” Here he answers some questions for Quality Digest Daily.

Quality Digest Daily: Please give us a synopsis of your career.

Every once in awhile people will ask me to (discretely) evaluate a kaizen event team’s effectiveness. I don’t necessarily relish doing that when it is intended for the purpose of team comparisons, but it’s not an unfair request from senior leaders.

Someday, I should probably try to pull the mystical sensei thing and ask them first what they think—and why.

The criteria that I apply are less than scientific. I don’t apply weighting between the criteria, and I simply use a 1 to 5 score for each one, with 5 being the highest. The important thing is reflecting upon what’s meaningful—learning and then improving.

My measurement criteria for evaluating the effectiveness of a kaizen event team—which are in no particular order—are as follows (including links to relevant posts):

Waste elimination effectiveness. The notion here is about how well the team identifies, acknowledges, and then eliminates the waste within their target process. Waste elimination effectiveness (WEE) is driven as much by team aggressiveness as technical acumen. (Lean Metric: Waste Elimination Effectiveness)

My first job was in industrial distribution, and with distribution came learning to count inventory. An annual inventory tax was levied, so an accurate count was important. I was given a computer list of items to count. An important lesson I learned was that to get an accurate count, there was a right and wrong method.

Given the computer-printed inventory sheet with item description, bin location, and the inventory count shown in the system, I found myself verifying the sheet rather than counting what was actually on the shelf. This led to a huge disparity in the inventory count.

The reason for the wrong count was that as I read the sheet, I would look for the item on the shelf. If the sheet matched what was on the shelf (e.g., description, quantity), the count was reported as accurate or else adjusted to the appropriate number.

However, items had been misplaced when shipments were received or accidentally moved for a variety of reasons. Items reported missing during the inventory count when counting sheet-to-shelf were actually there in many cases, just not where they were supposed to be.

So the problem for my inventory was counting sheet-to-shelf rather than shelf-to-sheet.

As robots and their control systems become more powerful and flexible, robotics are moving from heavy industrial applications into producing consumer products we all use in our daily lives. Fickle consumers demand products in new forms, which plays to the strength of robotics’ inherent flexibility to change while keeping production local. Vision-enabled robots are also used in warehouse distribution systems and to test consumer goods for quality control.

“Robots are used in a very broad swath of consumer products, from food and beverage, to office supplies, to building materials,” says Dean Elkins, senior general manager at the Motoman Robotics Division of Yaskawa America Inc. “Robots are gaining broad acceptance in the consumer arena, from primary packaging in the food sector through palletizing at the end of the production line.”

The U.S. Army aims to make ill-fitting uniforms and protective gear things of the past when it completes a body-measurement survey next year.

Supply officials ran into difficulty acquiring the correct sizes of chemical gear and body armor for troops at the beginning of the Iraq and Afghanistan wars. “Something was happening, and we didn’t know what or why,” says Cynthia Blackwell, survey program director for the Natick Soldier Research, Development and Engineering Center in Massachusetts, which is spearheading the survey.

Army officials say data from a 1988 survey are still being used to design gear, but that body types have changed significantly since.

A pilot study conducted by Natick in 2007 found the obesity epidemic plaguing the general population was “somewhat reflected in our troops,” notes Blackwell.

The height of active-duty male soldiers in 1988 averaged 69.1 in. (5 ft 9 in.) and weight was 172.7 pounds. By 2007, the average height stayed pretty much the same, but weight shot up to an average of 184.1 lb. Chest, waist, and hip girth all increased, with the average waistline expanding from 34 in. to 36.3 in.

In part one of this article, I explained the technique of root cause analysis (RCA) in an easy-to-understand manner with simple examples. In part two, we looked at some critical success factors to get maximum results from your RCA. In part three, the conclusion to this article, we’ll take a look at the remaining critical success factors. These are based on lessons learned from experience and from mistakes made. As RCA and other quality techniques are relatively more common in manufacturing, several of the examples in this article are drawn from service industries to offer a broader perspective. The article is equally relevant in manufacturing and service businesses as well as government and not-for-profit organizations.

(Click image to enlarge)

Let me begin by saying that I have a great deal of respect for Mike Micklewright’s achievements and contributions in the realms of business, training, and writing. I feel the need, however, to explore the nature of his reasoning in reference to his “Croc of the Month” article published in Quality Digest Daily on March 10, 2011.

In fact, my hackles went up from the first paragraph and little alarm bells rang in my head throughout the entire article.

Micklewright’s disdain for reward systems in general is well known, and though I’ve had reservations concerning his opinion on the subject, I feel that this particular piece unduly “smushes together” several concepts and warrants review.

“Smushed together” stuff

Not exactly a technical term, but helpful in describing a fault in reasoning whereby an explanation combines more than one concept as if the concepts were inextricable from one another. The “smushed” concepts are then used as a singular point of reference for further explanation. The problem with “smushing” is that if one of those concepts is based on faulty assumptions, the logic that follows may also be faulty.

Critical care units at St. Joseph’s Hospital Health Center in Syracuse, New York, were faced with a formidable task. They had applied to receive the Beacon Award for Critical Care Excellence, a distinction given only to the top intensive care units in the United States. One of the components on which they would be judged was how they assessed patients’ pain levels in a critical care environment, and that’s where they hit a snag—until a nursing student stepped in.

“The staff and I were measuring pain levels using a tool that was outdated and not suited to ICU work,” says Christopher Kowal, who in addition to being a full-time staff nurse, was pursuing a master’s degree in Science Nursing Education at American Sentinel University.

Using change-management skills he’d gained from his studies, Kowal was able to identify a more appropriate pain-assessment tool and designed a pilot program to study its effectiveness. The results were remarkable. “I was able to better manage patients’ pain and get them out of the intensive care unit (ICU) more quickly,” Kowal says. “And the new tool improved productivity at the same time.”

Every human being, over time, yearns to put his life in order—to have his expectations met, and to use filters to help him know how a situation will resolve itself. Consequently, we subconsciously strive to put new information into existing categories, based on previous patterns and preset concepts that have been formed during our lifetimes. Our preconceptions may be as innocuous as, “I’m going to watch this actor because she always stars in a romantic comedy, and I enjoy that genre,” or, “It’s the last week of the quarter, so we’re going to be pushed for sales this week; what can we bring in from next quarter, what can we expedite out the door?” or even, “My spouse is going to blow his top when I tell him I want to go away for the weekend with my pals.”

In a work context, preconceptions limit our ability to see what “reality” is, and therefore provide meaningful feedback to our organization about what needs to be addressed. The concepts of lean involve gemba, going to “the actual place” and jidoka, having “respect for people.” Yet, if we walk into an area and have preconceptions about it, or do not have respect for the people we are interacting with, then we thwart the very concept of improvement.