This issue is the first of three consecutive CMSC show-focus issues that highlight the yearly Coordinate Metrology Systems Conference. The CMSC is the largest U.S. trade show focused solely on large-scale 3-D metrology. Attendance has grown each year, with last year reaching nearly 600 attendees. All the key players in large-scale 3-D measurement are there representing every large-scale 3-D measurement technology, including laser scanners, structured-light scanners, laser radar, photogrammetry, theodolites, articulated arms, indoor GPS, and more.

Our CMSC cover story this month focuses on the use of articulated arms (portable coordinate measurement machines) to align collimators at CERN’s Large Hadron Collider in Switzerland. Steering two high-energy beams traveling in opposite directions around a 27 km-circumference accelerator so that they collide head on at a predetermined point requires the most accurate in 3-D metrology equipment. You can read how they did it starting on page 22.

Quality Digest is proud to have been the sole media sponsor for the CMSC show for four years, and we look forward to continuing our coverage of the ever-evolving field of large-scale 3-D metrology.

Eighty-four doctors treated 2,973 patients, and an undesirable incident occurred in 13 of the treatments (11 doctors with one incident and one doctor with two incidents), a rate of 0.437 percent. A p-chart analysis of means (ANOM) for these data is shown in figure 1.

This analysis is dubious. A good rule of thumb: Multiplying the overall average rate by the number of cases for an individual should yield the possibility of at least five cases. Each doctor would need 1,000 cases to even begin to come close to this!

The table in figure 2 uses the technique discussed in last month’s column, “A Handy Technique to Have in Your Back Pocket,” calculating both “uncorrected” and “corrected” chi-square. Similar to the philosophy of ANOM, I take each doctor’s performance out of the aggregate and compare it to those remaining to see whether they are statistically different. For example, in figure 2, during the first doctor’s performance, one patient in the 199 patient treatments had the incident occur. So, I compared his rate of 1/199 to the remaining 12/2,774.

As Davis Balestracci frequently emphasized in his column, “RealWorldSPC,” published in Quality Digest for four years, it is fundamental to understand the context of the data before you begin to do any computations. It is the background for your data that determines how you should organize the data, how you should analyze the data, and how you should interpret the results of your analysis. Once you ignore the context, you’re like a train that has gone off the track, with the inevitable result.

One day a company sent me some data that it had spent more than a month collecting. These data represented the results of an experimental study carried out using production batches. For each of 30 batches the company recorded all sorts of production information, along with the experimental conditions that applied to that batch. At the end of the production process it took 40 items from each batch and measured the property of interest. Thus, it had a total to 1,200 values: 40 values for each of the 30 batches.

Is “Good Enough” Good Enough?

In “Is Three Sigma Good Enough?” (H. James Harrington, “Performance Improvement,” June 2008), the author makes some good points about whether the cost of getting to a Six Sigma level is really justified, but his point is made based on his special set of numbers. I could make up different numbers to prove that going to a Six Sigma level is cost-justified. The point that’s being missed, I feel, is the real cost of poor quality. I believe that Taguchi suggested the measurable cost of poor quality to the customer should be squared to get the real costs. If we square Mr. Harrington’s cost of bad widgets, it presents a very different picture. One can never capture the full cost of a poor product in the marketplace, but it is certainly much more than is presented in this example. As the late Philip Crosby would say, ‘There has never been a case where the cost of repairing a bad product was cheaper than doing it right the first time!’

-- Dennis Sowards