Deming described a system of “profound knowledge.” Deming’s system of profound knowledge consists of four parts: appreciation for a system, knowledge about variation, theory of knowledge, and psychology. A system in a network of interdependent components that work together to accomplish the aim of the system. The system of profound knowledge is itself a system. The parts are interrelated and cannot be completely understood when separated from one another. Systems must be managed, the greater the interdependence of the various system components, the greater the need for management. In addition, systems should be globally optimized; global optimization cannot be achieved by optimizing each component independent of the rest of the system. Systems can be thought of as networks of intentional cause-and-effect relationships. However, most systems also produce unintended effects. Identifying the causes of the effects produced by systems requires understanding of variation — part 2 of Deming’s system of profound knowledge. Without knowledge of variation people are unable to learn from experience. There are two basic mistakes made when dealing with variation: 1) reacting to an outcome as if it were produced by a special cause, when it actually came from a common cause, and 2) reacting to an outcome as if it were produced by a common cause, when it actually came from a special cause. Deming’s theory of profound knowledge is based on the premise that management is prediction. Deming, following the teachings of the philosopher C.I. Lewis, believed that prediction is not possible without theory. Novelist/philosopher Ayn Rand defines theory as “A set of abstract principles purporting to be either a correct description of reality or a set of guidelines for man’s actions. Correspondence to reality is the standard of value by which one estimates a theory.” Deming points out that knowledge is acquired as one makes a rational prediction based on theory, then revises the theory based on comparison of prediction with observation. Knowledge is reflected in the new theory. Without theory, there is nothing to revise, i.e., there can be no new knowledge, no learning. The process of learning is operationalized by Deming’s Plan-Do-Study-Act cycle (a modification of Shewhart’s Plan-Do-Check- Act cycle). It is important to note that information is not knowledge. Mere “facts” in and of themselves are not knowledge. Knowing what the Dow Jones Industrial Average is right now, or what it has been for the last 100 years, is not enough to tell us what it will be tomorrow. Psychology is the science that deals with mental processes and behavior. In Deming’s system of profound knowledge, psychology is important because it provides a theoretical framework for understanding the differences between people, and provides guidance in the proper ways to motivate them.

Improving your ability to bring unwanted products or services to market will not meet customers' demands or needs with any degree of certainty. Rather, identifying customer value and optimizing processes to meet that definition improve a company's ability to service its customers and thus remain profitable in the long term.

Point 11 states "Eliminate numerical quotas for the work force and numerical goals for management".

Although a DPMO of 20,000 equates to (approximately) a 3.5 Sigma Level (Appendix Table 9), the best answer is "all of the above", since the reported Cost of Quality would indicate a much better Sigma Level (Figure 1.3). When the Cost of Quality is underreported, then a Hidden Factory is at work masking those activities. (References from Six Sigma Demystified by Keller).

Successful change agents should be non-confrontational in their approach.

You can't force management to be involved. They must see leading the Six Sigma effort as a natural extension of their responsibilities. Their commitment cannot be verified in training, but should be seen by the results obtained and the effort put forth over a period of time. It is their leadership, not that of Black Belts, that will ensure program success and business success, which are inherently linked.

A Six Sigma level of performance for a key process is an unlikely outcome of the first wave of training. It is more important to involve key high-profile management and a select team for Black Belt and Green Belt training, than to try to train too many participants.

In the first wave of Six Sigma training and deployment, it is most important to select projects with achievable objectives (a high probability of success), whose results will be recognized throughout the organization, such as high profile customer issues. These may or may not be key customer issues, and will most likely not be the projects with the best return to the organization.

Black Belts, not Champions, lead Six Sigma projects.

The Other category is only the highest because of a single month with an exceptionally large non-conformance. This illustrates the inadequacy of Pareto charts alone for highlighting problem areas, since the Pareto cannot determine if the problem area represents a common occurrence (i.e. a common cause) or an anomaly (i.e. a special cause). Special causes of variation may not re-occur, so can't offer the same financial savings as elimination of common causes of variation. The special cause noted in January for Other has yet to be repeated over the course of the year, and may have already been addressed as an operational issue. The Wrong Color category is next highest on the Pareto based on count, so is the best choice for a project based on the information provided. Choice b is inadequate in defining what will be addressed.

The cost to the company for the year given was as follows:

      Cracked= 145 * 428.25 = $62,096.25
      Chipped: = 130 * 252.15 = $32,779.50
      Off Color= 176 * 275.33 = $48,458.08
      Wrong Color= 243 * 117.53 = $28,559.79

Cracks represent a better financial payback (in the absence of data comparing the cost to deploy the different improvement projects, and assuming a constant percentage of defect reduction across all projects)

A useful metric for determining the preferred project is the Pareto Priority Index (PPI), calculated as follows:

The DPO is calculated as:

The traditional yield calculation defined above ignores the Hidden Factory rework and waste, and does not consider the number and severity of defect types.

The Normalized Yield is:

The appropriate measurement base varies with the cost category and the audience.

The basic objective of a quality cost program is profit improvement. A discussion of the relationship of quality costs and profits is given in Pyzdek, T., “The Impact of Quality Cost Reduction on Profits,” Quality Progress, Oct. 1976.

In estimating the cost of a project, obtaining highly accurate cost estimates for all project expenses is neither crucial or practical.

In establishing a base line for a project it is important to involve the accounting and finance department when financial metrics are developed.

The affected department is one of the stakeholders that should have been identified and included in the problem solving, if not the team itself. Involving the Sponsor should be a last resort. The team needs to satisfy the department's legitimate concerns, and help them understand why the proposed solution is the best course (if in fact it is, given the department's concerns).

Choice c best represents the concept of consensus decision making, which is preferable to voting or mandating decisions.

The manager needs to conduct him or herself within the acceptable rules of conduct. Ground rules such as mentioned in Choice b are typical, as is a rule that employees' rank in the organization should not influence the team dynamics. A public reminder of the ground rules, done quickly and respectfully, shows the team that no one is above these rules. By addressing this concern immediately, the chance of future instances is reduced.

Conflict is necessary for ideas to be generated and discussed and should not be discouraged. Voting is not a preferred way to settle conflict. Conflicts should be resolved using consensus.

Projects should be broken down to manageable projects lasting three to six months. Projects lasting longer than this are likely to lose support and team members, greatly reducing their chance of success.

The scope as stated is too poorly focused to develop a plan, assemble a team of knowledgeable personnel, or understand the potential savings of implementation. The reasons for scrap, and the resulting costs, need to be more clearly understood so that a realistic plan can be developed for the project.

A Pareto Analysis is a graphical tool often used to help identify opportunities for improvement.

Reasonable criteria, used by General Electric for establishing goals for Six Sigma projects, are:

Step 1a will remain on the critical path. The effect of moving Step 2b0 to run concurrent with Step 2a is to move it off the critical path, so the cycle time for the critical path is reduced by one day.

Customer satisfaction is a value judgment made by a customer regarding their total experience with your product or service. Quality is an absence of defects and the presence of desirable product or service features. Quality is one of many factors evaluated by customers when arriving at a satisfaction judgment.

The Kano model shows that there is a basic level of quality that customers assume the product will have. For example, all automobiles have windows and tires. If asked, customers don’t even mention the basic quality items, they take them for granted. However, if this quality level isn’t met the customer will be dissatisfied; note that the entire “Basic Quality” curve lies in the lower half of the chart, which represents dissatisfaction. However, providing basic quality isn’t enough to create a satisfied customer. The expected quality line represents those expectations which customers explicitly consider. For example, the length of time spent waiting in line at a checkout counter. The model shows that customers will be dissatisfied if their quality expectations are not met; satisfaction increases as more expectations are met. The Kano model is shown below.

It will have no effect on “satisfaction.” The Kano model indicates that basic quality features, if not present, lead to dissatisfaction. The entire basic quality curve lies in the dissatisfaction region.

All of these are customer contact worker (CCW) positions encountered in everyday life.

The Kano model is shown in the figure below.

The figure, based on the Kano Model, describes a situation of dynamic customer perceptions which are influenced by many factors, including the competition. Studies of customer satisfaction have demonstrated convincingly that customer satisfaction is not solely determined by the manufacturer’s perception of the quality of the product or service; conformance to engineering requirements is an inadequate standard of quality. As the figure demonstrates, competitive pressure will make today’s wow features tomorrow’s must have features. Customer expectations tend to increase steadily over time.

Prevention is the focus, rather than detection. Understanding customer needs is critical to this effort.

Complaints are not prevented, but detected at this point. There may be many other problems that customers don't bother to report.

The specifications are often incomplete in addressing important customer issues, especially those related to service issues, such as delivery time. The specifications are often defined without regard to process optimization. In many cases, customers would prefer tighter restrictions on the process, so specifications are not useful for controlling processes. In addition, you'll learn in the Measure stage that the process should be controlled based on its statistical capabilities, rather than the specifications.

A reasonable criteria, used by General Electric for establishing goals for Six Sigma projects, is: Sigma Level < 3 Sigma: 10 x reduction in defects Sigma Level > 3 Sigma: 50% reduction in defects. Choices b through d are not generally realistic in a single short term project.

Selecting the proper control chart for a particular data set is a simple matter if approached properly. The proper approach is illustrated in the figure below.

Selecting the proper control chart for a particular data set is a simple matter if approached properly. The proper approach is illustrated in the figure below.

C charts are statistical tools used to evaluate the number of occurrences-per-unit produced by a process. C charts can be applied to any variable where the appropriate performance measure is a count of how often a particular event occurs and samples of constant size are used. C charts answer the question “Has a special cause of variation caused the central tendency of this process to produce an abnormally large or small number of occurrences over the time period observed?”

X-bar and R charts use variables data, the other charts use attributes data. Thus, X-bar and R charts are more sensitive to measurement variation.

While it is true that instituting 100% inspection will not improve the quality produced, it will improve the quality delivered to the customer.

Walter Shewhart’s main reason for inventing the control chart technique was to detect assignable causes of variation in the process.

Shewhart (1931, 1980) defined control as follows:

Subgroups larger that one would include samples taken over too long a period, increasing the chance of including special causes.

When the subgroup size is between 2 and 9, either a Range or Sigma chart may be used to estimate process variation for the X bar chart. The s chart is more accurate, but the range chart is easier to plot. The s chart can always be used in place of the range chart, but the range chart begins to lose accuracy as the sample size exceeds 5, and should not be used if the sample size is greater than 10.

The Range chart should not be used for subgroup sizes ten or larger.

Using two sigma limits in place of three sigma limits results in process tampering, which increases process variation.

A control chart will not detect all process shifts. Very small process shifts may never be detected. They are designed to have a very low false alarm rate.

When the cost of collecting data is not an issue, a variables control chart of a critical process parameter provides a much better control method than an attribute chart of the failure of the metric to fall within requirements. While the attribute chart provides an estimate of the error rate, the variables chart allows a more accurate prediction of longer-term error rates even when no errors have been observed.

In estimating mortality for the surgical procedure, we should use the binomial distribution, since each sample (i.e. each patient) either lives or does not live. Since the number of samples each month varies, the p chart is the appropriate control chart.

Since each patient can have multiple pain incidents, the Poisson distribution is the appropriate one to use. If the number of surgical procedures varies each month, then the u chart is best.

We need sufficient resolution of the data to estimate the statistical properties of the process. A good rule of thumb is that we need an average count of 5 or more in each sample. If we observe less than that, then larger sample sizes are needed to estimate meaningful process statistics.

Adjustments based on customer requirements is known as process tampering. The most recent sample provides insufficient information, and it should be assumed the process has some level of variation. Confidence intervals are appropriate for population estimates, not processes. Choice d refers to statistical control limits based on prior data.

The histogram of samples from a process does not provide evidence of statistical process control, and is misleading if the process is out of statistical control. Outliers from a sample may be representative of a process shift, and unless 100% inspection results from finding these outliers (which is not indicated by the question), the remainder of the shipment may contain additional outliers. Removing the outliers provides a misleading representation of the process sample to the customer.

Cycle Time = 5.25 * (6) + 4.3 = 31.5 + 4.3 = 35.8

Womack and Jones offer each of these as types of waste.

Systems work best when input for the design is received by all users of the system.