Ripples
Drop a pebble into a pond. Its effects ripple out. But the ripples don’t radiate infinitely across the surface. Nor do they last forever. At sufficient distance from their center they are hardly distinguishable from the surrounding water. A point beyond the reach of the ripples wouldn’t know that a pebble was ever dropped into the pond.
Drop two pebbles into a pond. Each generates ripples that radiate out. If the pebbles were dropped far from each other, their ripples die out before reaching one another. Each unaware the other happened just as before. But if the pebbles were dropped close to each other, their ripples interfere with one another. Some reach through to the centers themselves. Thus making their presence known. “Here I am! I exist!”
We are sources of ripples in this expanse of existence. I cause ripples at every point and instant I am. So do you. But until our ripples interact with one another we cannot know of each other. In ancestral times we were separated far enough from one another for our ripples to ever interact. We were independent. Alone. That space has shrunk to almost nothing in our time. Our ripples constantly collide with one another. Sometimes constructively, sometimes destructively. We are painfully aware of each other without announcement.
We absorb some of the energy from the ripples that bombard us. Not enough to damp them completely. They reflect off of us. We react to counteract their impact on us. And so no ripple ever settles out. Each seems to get an invisible kick and be periodically rejuvenated. By what and from when seems shrouded in mystery. The water’s surface is forever unsettled. This is the chaos that is life. No peace. No quiet.
As we grow in number, as the space between us continues to shrink, the closer we get to one another, the more we are bombarded with original ripples and ripples from interacting ripples. They come at us from all directions. They come at us faster. There is no way to predict and prepare for the next collision with the here and now. There isn’t time to process what it means. There is no thing to thank or to blame. We only experience it. Rich. Momentary. Unique.
Dealing with Nonconforming Product
A particular process makes parts of diameter D. There are 10 parts produced per batch. The batches are sampled periodically and the diameter of all the parts from the sampled batch is measured. Data, representing deviation from the target, for the first 6 sampled batches is shown in Table 1. The graph of the data is shown in Figure 1. Positive numbers indicate the measured diameter was larger than the target while negative numbers indicate the measured diameter was smaller than the target. The upper and lower specification limits for acceptable deviation are given as +/- 3.
Table 1. Data for six batches of 10 parts each. The numbers represent the deviation from the target.
Figure 1. Graph of the data from the table above. The most recent batch, batch number six, shows one part was nonconforming.
The most recent batch, sample batch number six, shows one of the 10 parts having a diameter smaller than the lower specification limit. As such, it is a nonconforming part.
The discovery of a nonconforming product triggers two parallel activities: i) figuring out what to do with the nonconforming product, and ii) addressing the cause of the nonconforming product to inhibit the nonconformance from occurring again.
PRODUCT DISPOSITION
Nonconforming product may be repaired or reworked when possible, but it can always be scrapped. Each one of these three options has its own set of complications and cost.
Repairing a nonconforming product involves additional steps beyond what are usually needed to make the product. This additional processing has the potential to create previously unknown weaknesses in the product e.g. stress concentrations. So repaired product will need to be subjected to testing that verifies it still satisfies its intended use. For this particular case, repairing is not possible. The diameter is smaller than the target. Repair would have been possible if the diameter had been larger than the target.
Reworking a nonconforming product involves undoing the results of the previous process steps, then sending the product through the standard process steps a second time. Undoing the results of the previous process steps involves additional process steps just as were required to repair a nonconforming product. This additional processing has the potential to create previously unknown weaknesses in the product. Reworked product will need to be subjected to testing that verifies it still satisfies its intended use. For this particular case, reworking is not possible.
Scrapping a nonconforming product means to destroy it so that it cannot be accidentally used. For this particular case, scrapping the nonconforming part is the only option available.
ADDRESSING THE CAUSE
In order to determine the cause of the nonconformity we have to first determine the state of the process i.e. whether the process is stable or not. The type of action we take depends on it.
A control chart provides a straightforward way to answer this question. Figure 2. shows an Xbar-R chart for this process. Neither the Xbar chart (top), nor the R chart (bottom) show uncontrolled variation. There is no indication of a special cause affecting the process. This is a stable process in the threshold state. While it is operating on target i.e. its mean is approximately the same as the target, its within-batch variation is more than we would like. Therefore, there is no point trying to hunt down a specific cause for the nonconforming part identified above. It is most likely the product of chance variation that affects this process; a result of the process’s present design.
Figure 2. Xbar-R chart built using the first six sampled batches. Neither the Xbar chart nor the R chart show uncontrolled variation. There is no indication of a special cause affecting the process.
In fact, the process was left alone to collect more data (Figure 3.). The Xbar-R charts do not show any unusual variation that would indicate external disturbances affecting the process. Its behavior is predictable.
Figure 3. More data was collected and the control limits were recalculated using the first 15 sampled batches. The process continues to look stable with no signs of external disturbance.
But, even though the process is stable, it does produce nonconforming parts from time to time. Figure 4. shows that a nonconforming part was produced in sampled batch number 22 and one in sampled batch number 23. Still, it would be wasted effort to hunt down specific causes for the creation of these nonconforming parts. They are the result of chance variation that is a property of the present process design.
Figure 4. Even though the process is stable it still occasionally produces nonconforming parts. Sampled batch number 22 shows a nonconforming part with a larger than tolerable diameter while sampled batch number 23 shows one with a smaller than tolerable diameter.
Because this process is stable, we can estimate the mean and standard deviation of the distribution of individual parts. They were calculated to be -0.0114 and 0.9281. Assuming that the individual parts are normally distributed, we can estimate that this process will produce about 0.12% nonconforming product if left to run as is. Some of these parts will be smaller than the lower specification limit for the diameter. Others will be larger than the upper specification limit for the diameter. That is, about 12 nonconforming pieces will be created per 10,000 parts produced. Is this acceptable?
If the calculated nonconforming rate is not acceptable, then this process must be modified in some fundamental way. This would involves some sort of structured experimentation using methods from design of experiments to reduce variation. New settings for factors like RPM or blade type among others will need to be determined.
A Reflection on Culture
Through the books I’ve recently read I’ve come to see culture as an output, a result or an emergent property of a system. Furthermore, just like all outputs, it cannot be managed directly, as Matthew E. May points out in his post “To Change A Culture, Change The System.” The only way to manage outputs is to change the inputs to the system and/or change the system.
I’ve come to believe that we’re wired to focus on outputs and sort good from bad. And, why not? For most of our evolution we’ve never had any control of our environment. We’ve been a part of the system. In that context it’s perfectly natural for us to comment on culture and sort it into good or bad. However, just as you can’t inspect quality into a product as Harold S. Dodge pointed out, you can’t improve culture by calling out its positive or negative attributes.
In the case of the modern organization, perhaps you can select the type of people to minimize cultural diversity. (Cultural diversity here refers to mindset, drive, focus, etc.) But in my experience, with the way that process (i.e. interviews) works right now, it amounts to shots in the dark. Better to setup a system that is robust to the variation in its human resource to yield a cohesive culture.
System design requires designers (leaders) who have a vision for the system. They must understand the context for their system and then design their system to produce the desired result. These are all skills that can be learned, but so few bother. It’s hard work. There’s no instant pudding. But who’s got the time?
Iterations 