Some Other Important Total Quality Tools Introduced

The preceding sections have discussed the statistical tools that have come to be known as “the seven tools.” One should not conclude, however, that these seven are the only tools needed for pursuing world-class performance. These seven are the ones that have been found most useful for the broad­est spectrum of users. Ishikawa referred to them as the “seven indispensable tools for quality control.”⁵ He went on to say that they are useful to everyone from company presidents to line workers and across all kinds of work—not just manu­facturing. These seven probably represent the seven basic methods most useful to all the people in the workplace. We recommend five more as necessary to complete the tool kit of any business enterprise, if not each of the players within the business:

• Five-S
• Flowcharts
• Surveys
• Failure mode and effects analysis (FMEA)
• Design of experiments (DOE)

1. Five-S

Five-S is considered as essential to continual improvement. Its most significant proponent is Hiroyuki Hirano, author of 5 Pillars of the Visual Workplace, who claims that an orga­nization that cannot implement Five-S successfully will be unable to integrate any large-scale change. Hirano holds that Total Quality Management (TQM), Just-in-time/Lean (JIT/ Lean), and Kaizen are supported by the five pillars repre­sented by the five S’s and are probably unattainable without Five-S. The authors heretofore have considered these five S’s to be an integral part of TQM and JIT/Lean, but we have come to believe that they should be recognized as a tool that is separable from TQM but that may serve as an entry point for TQM in many organizations.

The five S’s were originally conceived in Japanese, as represented by five words beginning with the letter s. Translated to English, the words did not, as you might ex­pect, begin with s, so Five-S required some “adjustment” in order to make sense in English. The table below shows the evolution from Japanese to English.

Five-S is a way of doing things that eliminates waste and reduces errors, defects, and injuries. A recurring comment from executives returning from visits to Japanese industrial plants in the seventies and eighties was that the Japanese plants were spotlessly clean and orderly and seemed far less chaotic than corresponding plants in the West. Much of that was the result of Hiroyuki Hirano’s Five-S philosophy. Five things must happen under Five-S, which are as follows:

1. Sort: First, one has to sort through items in the workplace to determine which are useful and which are not. Those that are not are discarded. That might include tools, equipment, inventory of stock, spare parts, documentation-everything in the area. If it is not useful, dispose of it, or at least get it out of the work area. The objectives are the elimination of unnecessary items from the workplace and the elimination of time wasted in continually having to search through or work around clutter in order to do the job.
2. Store: The things remaining, the useful items, must be stored in such a manner that they are visible and immediately available to the workforce. An example is a shadow board with the silhouettes of the tools assigned to a workstation. The silhouette shows where the tool is to be stored when not in use. There has to be an assigned place for everything, and everything should al­ways be kept in its place. The objective is elimination of time wasted looking for tools, parts, and so on by having it easily at hand and visible every time it is needed.

3. Shine: The work area and everything in it must shine; that is, it must be kept clean at all times. An important consideration here is that this cleaning is not left to a “cleaning crew” but is the responsibility of the employ­ees assigned to the work area. Once cleaned, it is kept that way at all times, not just after the workday. While cleanliness is a good thing in its own right, the act of keeping everything clean becomes a form of inspection of machines, tools, and environmental conditions. The objective is reduced errors and defects that result from defective tools and equipment and from contamination.

4. Standardize: Next we must develop the rules and procedures for the work area, standardizing on the best practices (the best known way of doing some­thing). When a best practice for accomplishing a task is adopted, everyone doing that task must do it the same way—until a better way is found through continual improvement. The objective is reduced er­rors and improved consistency and reliability of work, while being alert to discovering or inventing process improvements.

5. Sustain: Then we must establish the discipline nec­essary to follow the rules and practices, improve upon them, and thereby sustain the gains made through Five-S. Sort, Store, Shine, and Standardize are all tan­gible functions. Sustain, however, is intangible from the standpoint of being able to touch it or see it. Sustain, or keeping the Five-S philosophy alive and functioning in an organization, is undoubtedly the most difficult of the S’s and requires the full support and leadership of the top management team and managers all the way down through the organization. Slipping back into old (pre- Five-S) habits must not be allowed, and the expectation for continual improvement must always be understood. The objective of Sustain is to keep Five-S alive, func­tioning, and improving.

2. Flowcharts

Both W. Edwards Deming⁶ and Joseph Juran⁷ promote the use of flowcharts. A flowchart is a graphic representation of a process. A necessary step in improving a process is to flowchart it. In this way, all parties involved can begin with the same understanding of the process. It may be revealing to start the flowcharting process by asking several different team members who know the process to flowchart it inde­pendently. If their charts are not the same, one significant problem is revealed at the outset; there is not a common un­derstanding of the way the process works. Another strategy is to ask team members to chart how the process actually works and then chart how they think it should work. Comparing the two versions can be an effective way to identify causes of problems and to suggest improvement possibilities. The most commonly used flowcharting method is to have the team, which is made up of the people who work within the process and those who provide input to or take output from the process, develop the chart. It is important to note that to be effective, the completed flowchart must accurately reflect the way the process actually works, not how it should work. After a process has been flowcharted, it can be studied to determine what aspects of it are problematic and where im­provements can be made.

You may already be familiar with the flowchart, at least to the point of recognizing one when you see it. It has been in use for many years and in many ways. The application we have in mind here is for flowcharting the inputs, steps, func­tions, and outflows of a process to more fully understand how the process works, who or what has input to and in­fluence on the process, what its inputs and outputs are, and even what its timing is.

A set of standard flowcharting symbols for communi­cating various actions, inputs, outflows, and so on, is used internationally. These symbols may be universally applied to any process. The most commonly used symbols are
shown in Table 15.1. To illustrate their use, a simple flow­chart using the most common symbol elements is given in Figure 15.33. Flowcharts may be as simple or as complex as you may need. For example, in Figure 15.33 the rectangle labeled “Troubleshoot” represents an entire subprocess that itself can be expanded into a complex flowchart. If an intent of the flowchart had been to provide information on the troubleshooting process, then each troubleshooting step would have to be included. Our purpose for Figure 15.33 was merely to chart the major process steps for receiving and repairing a defective unit from a customer, so we did not require subprocess detail. This is a common starting point. From this high-level flowchart, it may be observed that (a) the customer’s defective unit is received, (b) the problem is located and corrected, and (c) the repaired unit is tested. (d) If the unit fails the test, it is recycled through the repair process until it does pass. (e) Upon passing the test, paperwork is completed. (f) Following that, the cus­tomer is notified, and (g) the unit is returned to the cus­tomer along with a bill for services. With this high-level flowchart as a guide, your next step will be to develop detailed flowcharts of the subprocesses you want to im­prove. Only then can you understand what is really hap­pening inside the process, see which steps add value and which do not, find out where the time is being consumed, identify redundancies, and so on. Once you have a process flowcharted, it is almost always easy to see potential for im­provement and streamlining. Without the flowchart, it may be impossible.

More often than not, people who work directly with a process are amazed to find out how little understand­ing of the process they had before it had been flowcharted. Working with any process day in and day out tends to breed a false sense of familiarity.

We once took over a large manufacturing operation that was having major problems with on-time delivery of systems worth $500,000 to $2 million apiece. Several rea­sons accounted for the difficulty, but a fundamental prob­lem was that we were not getting the input materials on time—even with a 24-month lead time for delivery. One of the first things we did was flowchart the entire material system. We started the chart at the signing of our custom­er’s order and completed it at the point where the material was delivered to the stockroom. The chart showed dozens of people involved, endless loops for approval and check­ing, and flawed subprocesses that consumed time in unbe­lievable dimensions.

When the flowchart was finished, it was clear that the best case from the start of the order cycle until material could be expected in our hands required 55 weeks. The worst case could easily double that. With this knowledge, we attacked the material process and quickly whittled it down to 16 weeks and from there to 12 weeks. The point is this: Here was a process that had grown over the years to the point that it was no longer tolerable, much less ef­ficient. But the individual players in the process didn’t see the problem. They were all working very hard, doing what the process demanded, and fighting the fires that constantly erupted when needed material was not avail­able. The flowchart illuminated the process problems and showed what needed to be done.

If you set out to control or improve any process, it is es­sential that you fully understand the process and why it is what it is. Don’t make the assumption that you already know, or that the people working in the process know, because chances are good that you don’t, and they don’t. Work with the people who are directly involved, and flowchart the pro­cess as a first step in the journey to world-class performance. Not only will you better understand how the processes work, but also you will spot unnecessary functions or weaknesses and be able to establish logical points in the process for con­trol chart application. Use of the other tools will be suggested by the flowchart as well.

3. Surveys

At first glance, the survey may not seem to be indispens­able. When you think about it, though, all of the tools are designed to present information—information that is per­tinent, easily understood by all, and valuable for anyone attempting to improve a process or enhance the performance of some work function. The purpose of a survey is to obtain relevant information from sources that otherwise would not be heard from—at least not in the context of providing help­ful data. Because you design your own survey, you can tailor it to your needs. We believe that the survey meets the test of being a total quality tool. Experience has shown that the survey can be very useful.

Surveys can be conducted internally as a kind of em­ployee feedback on problem areas or as internal customer feedback on products or services. They can also be con­ducted with external customers, your business customers, to gain information about how your products or services rate in the customers’ eyes. The customer (internal or external) orientation of the survey is important because the customer, after all is said and done, is the only authority on the quality of your goods and services. Some companies conduct annual customer satisfaction surveys. These firms use the input from customers to focus their improvement efforts.

Surveys are increasingly being used with suppliers as well. We have finally come to the realization that having a huge supplier base is not the good thing we used to think it was. The tendency today is to cut back drastically on the number of suppliers utilized, retaining those that offer the best value (not best price, which is meaningless) and that are willing to enter into partnership arrangements. If a company goes this route, it had better know how satisfied the suppli­ers are with the past and present working relationship and what they think of future prospects. The survey is one tool for determining this. It is possibly the best initial method for starting a supplier reduction/supplier partnership program.

Even if you are not planning to eliminate suppliers, it is vital to know what your suppliers are doing. It would make little sense for you to go to the trouble of implementing total quality if your suppliers continue to do business as usual. As you improve your processes and your services and products, you cannot afford to be hamstrung by poor quality from your suppliers. Surveys are the least expensive way of deter­mining where suppliers stand on total quality and what their plans are for the future. The survey can also be a not-too- subtle message to the suppliers that they had better “get on the bandwagon.”

A typical department in any organization has both in­ternal suppliers and internal customers. Using the same customer-oriented point of view in a survey has proven to be a powerful tool for opening communications among de­partments and getting them to work together for the com­mon goal rather than for department glory—usually at the expense of the overall company.

The downside of surveys is that the right questions have to be asked, and asked in ways that are unambiguous and de­signed for short answers. A survey questionnaire should be thoroughly thought out and tested before it is put into use. Remember that you will be imposing on the respondents’ time, so make it easy and keep it simple.

4. Failure Mode and Effects Analysis

Failure mode and effects analysis (FMEA) tries to identify all possible potential failures of a product or process, priori­tize them according to their risk, and set in motion action to eliminate or reduce the probability of their occurrence. FMEA cannot by itself bring about this happy ending, since it is an an­alytical tool, not a problem solver. But it will point to the prob­lems that must be solved through the use of the other tools.

Failure mode and effects analysis—the name itself is enough to scare off the unfamiliar. So you don’t give up on FMEA before we get into it, let’s simplify the concept. FMEA just tries to identify all the possible types (modes) of failures that could happen to a product or a process before they hap­pen. Once the possible “failure modes” have been identified, the “effects analysis” kicks in and studies the potential con­sequences of those failures. Next, the consequences of each potential failure are ranked by

• Seriousness/Criticality to the customer
• Probability of the fault’s occurrence
• Probability of the fault’s detection by the systems re­sponsible for defect prevention or detection

Seriousness of consequence, likelihood of occurrence, and difficulty of detection all work together to determine the criticality of any specific failure mode. Comparing the criticality of all the identified potential failure modes estab­lishes the priority for corrective action. That is the objective of FMEA. FMEA tells the organization where its resources should be applied, and this is very important because all possible failures are not equal and the organization should always deploy its resources to correct the problems that are most critical. Without the benefit of FMEA, it is doubtful that an organization could identify its most critical failure modes very accurately. Remember, usually FMEA addresses prob­lems that have not yet happened. Next time you are cruising at 600 miles per hour at 35,000 feet, consider whether the designers of your airliner should have used FMEA—or the next time you really, really need your brakes to work (Am I going to go over the cliff?) or when you buy that new $2,000 high-definition TV (So much technology—is it going to be reliable?). We might also consider it if we have to go to a hospital—or when we ship our original, no-copy-available manuscript to our publisher by overnight express. Looking at it from another viewpoint, had FMEA been available, could it have prevented the Titanic’s disaster? Given what we now know about the ship’s collision with the iceberg, we are convinced that had FMEA been employed, the Titanic might have plied the seas through most of the twentieth century. Of course, FMEA did not come along until four decades later.

There are several kinds of FMEA. Design FMEA is employed during the design phase of a product or service, hopefully starting at the very beginning of the project. In this way, the designers will be able to develop a design that has fewer potential failures, and those that cannot be avoided can be made less severe. Also, by using FMEA concurrently with the design activity, it is more likely that test and inspec­tion methods will be able to catch the problems before they get to the customer.

A second version is process FMEA. In this case, FMEA is looking at the potential failures (errors, miscues) of a pro­cess. The process might be that of an accounting firm, a hos­pital, a factory, a governmental agency, or any other entity. One can imagine that in a hospital there are many processes that can have lots of failure modes, some probably not too important, but some as severe as they come. One would hope that FMEA is in every hospital’s tool kit.

Ford Motor Company uses FMEA even before it gets to the design stage of a vehicle. As the concept for a new vehicle is being developed, FMEA is employed to make sure that the vehicle will not bring problems related to the concept into the design and production stages.

FMEA can also be used after the fact (as in the case of a product repeatedly failing in the hands of the customer). This may lead to a retrofit or recall of the product if the problem is severe or simply to a design change for future production if the problem is not critical. The procedure is essentially the same for every kind of FMEA.

FMEA is not new, although until recently its use was mainly associated with military and aerospace programs. It was developed by the U.S. military in 1949 and has seen increasing use in industry, especially since the 1980s, its importance being driven by the worldwide quality movement under TQM and ISO 9000 and by litigation in the United States against com­panies whose products are involved in customer injuries or deaths. FMEA is now considered an invaluable quality tool.

The Language of FMEA FMEA has its own unique set of terms. We have captured most of them in the following list:

• Failure mode. The way in which something might fail. For example, a race car’s tire might fail by puncture from a sharp object. It might also fail from a blowout resulting from wear. Puncture and blowout are two (of many) tire failure modes.
• Failure effect. The failure’s consequence in terms of operation, function, or status of the item.
• Effects analysis. Studying the consequences of the various failure modes to determine their severity to the customer. Of the two tire failure modes mentioned earlier, the blowout is likely to have the most serious consequence, since when a tire suddenly explodes, the speeding race car usually goes out of control, often with dire consequences. On the other hand, a puncture usu­ally allows the tire pressure to decrease gradually, allow­ing the driver time to sense the problem before he or she loses control. Neither failure mode is something the driver wants, but of the two, the puncture is preferred. Failure mode analysis (FMA). An analytical tech­nique used to evaluate failure modes with the intent to eliminate the failure mode in future operations.
• Design FMEA. FMEA applied during the design phase of a product or service to ensure that potential failure modes of the new product or service have been addressed.
• Process FMEA. FMEA applied to a process (as in a factory or office) to ensure that potential failure modes of the process have been addressed.

Risk assessment factors.

• Severity (S): A number from 1 to 10, depending on the severity of the potential failure mode’s effect: 1 = no effect, 10 = maximum severity.
• Probability of occurrence (O): A number from 1 to 10, depending on the likelihood of the failure mode’s occur­rence: 1 = very unlikely to occur, 10 = almost certain to occur.
• Probability of detection (D): A number from 1 to 10, depending on how unlikely it is that the fault will be de­tected by the system responsible (design control process, quality testing, etc.): 1 = nearly certain detection, 10 = impossible to detect.
• Risk Priority Number (RPN): The failure mode’s risk is found by the formula RPN = S X O X D. Said another way, RPN = Severity X Probability of Occurrence X Probability of Detection. RPN will be a number between 1 (virtually no risk) and 1,000 (extreme risk). The auto industry considers an RPN of 75 to be ac­ceptable, although in light of some recent manufacturer recalls for safety-related failures, we anticipate that may change.

FMEA Illustration Let’s consider a simplified FMEA to illustrate how the process works. We will assume we manu­facture bicycles and we are designing a new bike that will be made largely of composite materials. Since this is a new technology for our company, we are using design FMEA to make sure we’ve considered all the possible problem areas of the design before we go into production. The FMEA team has listed several potential failure modes, one involving sud­den, unwarned breakage of the front fork. It is obvious that should the fork fail, the effect on the customer could be se­vere. Since the rider will probably have no warning before the fork breaks, we rate the severity a 10 (S = 10).

We then identify possible causes of the fork failure and conclude that the probability of the most likely cause oc­curring is moderate, with five occurrences per thousand bikes. We rate the probability of occurrence a 6 (O = 6). Of course, it is our intention to detect the defective forks and discard them before they are attached to the bicycle frame. After we examine our fork testing methods, we conclude that the probability of detecting the failure mode flaw in the fork is low. We assign it a 6(D = 6).

Plugging these numbers into our equation, RPN = S X O X D, we have

RPN = 10 X 6 X 6 = 360

All other failure modes result in RPNs in the range of 40 to 70, so our focus should be on eliminating, or drastically reducing, this potential fork failure mode. We could redesign the fork so that it is more robust, thereby lowering the occur­rence value (O), or change the test process so that it is much more likely to detect a fork that might fail, thereby lowering the detection value (D).

Notice that if our fork testing process gave us complete assurance of detecting the fault—say, at the D = 1 level— RPN would be 60, and we probably wouldn’t need to put a lot of resources on this fault mode. The same could be said if D remained at 6, but the probability of occurrence of the fault mode turned out to be remote (O = 1).

When to Use FMEA FMEA should be employed at the following points:

• During the design or redesign of a process, product, or service
• When improvements are needed or planned for existing processes, products, or services
• When existing processes, products, or services are to be used in a new way
• During after-the-fact failure analysis
• When safety or health is an issue

This is intended to be a brief introduction to FMEA. Going into it more thoroughly is beyond the scope of this text. Should you find that you need more, the Internet is a good source of information, and there are many books dedi­cated to the subject.

5. Design of Experiments

Design of experiments (DOE) is a very sophisticated method for experimenting with processes with the objective of op­timizing them. If you deal with complicated processes that have multiple factors affecting them, DOE may be the only practical way of bringing about improvement. For example, such a process might be found in a wave soldering machine. Wave solder process factors include the following:

These 10 factors influence the process, often interacting with one another. The traditional way to determine the proper selection or setting was to vary one factor while holding all others fixed. That kind of experimentation led to making hun­dreds of individual runs for even the simplest processes. With that approach, it is unusual to arrive at the optimum setup be­cause a change in one factor frequently requires adjustment of one or more of the other factors for best results.

The DOE method reduces the number of runs from hun­dreds to tens as a rule, or by an order of magnitude. This means
of process experimentation allows multiple factor adjustment simultaneously, shortening the total process, but equally as im­portant, revealing complex interaction among the factors. A well-designed experiment can be concluded on a process such as wave soldering in 30 to 40 runs and will establish the opti­mum setting for each of the adjustable parameters for each of the selected factors. For example, optimal settings for conveyor speed, conveyor angle, wave height, preheat temperature, sol­der temperature, and flux specific gravity will be established for each PC board type, solder alloy, and so on.

DOE also shows which factors are critical and which are not. This information enables you to set up control charts for those factors that matter, while saving the effort that might have been expended on the ones that don’t. While design of experiments is beyond the scope and intent of this book, the DOE work of Deming, Taguchi, and others may be of help to you. Remember that DOE is available as a tool when you start trying to improve a complex process.

Source: Goetsch David L., Davis Stanley B. (2016), Quality Management for organizational excellence introduction to total Quality, Pearson; 8th edition.