Six Sigma: concepts and techniques in Quality Management

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The main objectives of the “Six Sigma” program are to reduce process variability and, consequently, the number of errors made, whether in the manufacture of a part or the delivery time of a product.

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How much can a failure cost? The answer to this question will certainly depend on each case. A failure in the production of low added-value items is very different from a failure in an aircraft or an oil platform. With this reasoning, you may be thinking that, in some cases, seeking to reduce failures to nearly zero may make sense. In other cases, the costs may outweigh the gains provided by the near elimination of failures. These concepts, which we studied when dealing with the “costs of quality,” should be revisited for this lesson.

We agree, then, that the pursuit of perfection, here translated as the elimination of failures, will be interesting for some product or service companies. In this context, “Six Sigma” emerges, which, through a set of practices, seeks process improvement by eliminating failures or defects, thereby increasing companies’ profitability.

Six Sigma history and concepts

In 1987, Bob Galvin, Motorola’s director in the United States, announced a new quality program, which he named “Six Sigma.” According to him, the focus was to increase customer satisfaction and reduce (or even eliminate) defects in the company’s products or services.

The program was developed to be applied throughout the organization and was established as the required capability level to approach the “zero defect” standard. This new standard should be applied in all areas, that is, in products, processes, and services.

For Bob Galvin, products and processes should be designed to be “Six Sigma.” Thus, the results would have reduced variability and higher productivity. Between 1987 and 1992, Motorola achieved significant results with the new program, generating savings of US$ 2.2 billion through process improvement. These results led many companies in the United States and around the world to also adopt the “Six Sigma” program.

Thus, we could define “Six Sigma” as a disciplined and highly quantitative management strategy, characterized by a systemic approach, whose objective is to dramatically increase companies’ profitability through the optimization of products and processes,

with the consequent increase in customer and consumer satisfaction.

It is also a systematic way of managing company activities, reducing costs and process variability, through a methodology focused on statistical measurement and improving efficiency and effectiveness.

Let us now see how the concepts of efficiency apply to “Six Sigma.” Having both concepts in mind, answer: Is it possible to be effective and not be 100% efficient? Certainly, your answer was yes. After all, it is possible to deliver a final product that meets 100% of the customer’s requirements. However, if in order to fully meet them we are forced to spend more resources than planned, we will compromise our projected profitability.

Objective of Six Sigma

The main objectives of the “Six Sigma” program are to reduce process variability and, consequently, the number of errors made, whether in the manufacturing of a part or in the delivery time of a product (when it comes to a service). As a result, there is a natural increase in profitability, as well as an increase in customer satisfaction levels. Imagine that your delivery company never delivered late. In this case, there would be no “error,” and you would always be satisfied with the service provided and ready to hire it again (which would increase the company’s profitability).

“Six Sigma” seeks both things: meeting customer requirements (effectiveness) and reducing costs in the production of a product or service (efficiency). Another very important aspect of the “Six Sigma” program is the connection between quality and financial indicators. Many executives at large companies were convinced to implement the program because they could see dramatic profitability gains in other companies. Gains this “convincing” are rarely seen in ISO 9001, TQM, PNQ, etc. models. In “Six Sigma,” quantifying gains is the main indicator and argument for implementation.

Later on we will study what Six Sigma projects are and examples of them, but at this point we can already say that the selection of priority projects is usually based on financial indicators. In other words, the projects with the best financial return will have priority for resource allocation.

The program’s name itself shows the strong relationship with statistical tools, since sigma is the Greek letter (in our case here, we use the lowercase letter σ) that represents the standard deviation, which in turn is a measure of process variability, which we studied in the lesson on statistical process control (SPC).

For example, in the case of a product, some characteristics are important or even critical to quality — examples of these characteristics would be the diameter of a part, the viscosity of an oil, etc. Therefore, we collect data and measure the defects generated in the process, which arise when the monitored characteristic does not meet specifications. This defect-counting methodology is known as DPMO (defects per million opportunities).

Why 6 Sigmas is important

Thus, if in the production of screws, a quantity of 12,000 screws (out of one million produced) were rejected for not being in accordance with the specification, we say that this process obtained 12,000 DPMO. Thus, the lower the DPMO, the better the process or product.

The objective of “Six Sigma” is to get very close to zero defects — 3.4 defects for every million operations performed, or DPMO. Thus, the methodology is used to measure the level of quality associated with a process, transforming the number of defects per million into a number on the sigma scale. It can also be used as a measure of compliance, since the lower the DPMO, the more compliant the process or product is.

As we will see later, there is a scale of standard deviations (σ), called the sigma scale, which represents the degree of assertiveness one seeks in, for example, a production process or in the provision of a service. The greater the number of deviations (σ), the greater the “perfection” sought in the process.

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The table above illustrates the sigma scale with the respective number of DPMO. Observe that a “Two Sigma” process is one that presents about 310,000 defects per million opportunities. In a “Four Sigma” process, the number is reduced to 67,000 DPMO

and, as the number of sigmas increases, the number of defects is reduced until reaching the near perfection of “Six Sigma,” when a process presents only 3.4 DPMO.

Now you may be wondering why discuss such a small difference, since a “Four Sigma” process has about 99.38% conformity and a “Six Sigma” process presents 99.999966% conformity. Compare the table below and say which company you

would like to be served by:

4 sigma (99.38% conforming)6 sigma (99.99966% conforming)
7 hours of power outage per month1 hour of power outage every 34 years
3,000 lost letters for every 300,000 letters mailed1 lost letter for every 300,000 letters mailed
15 minutes of non-potable water supply per day1 minute of non-potable water supply every 7 months
TV channel offline for 1.68 hours per weekTV channel offline for 1.8 seconds per week
1 emergency landing at Guarulhos airport per day1 emergency landing at all airports in Brazil every 5 years

Applying 6 sigma

It is common in industry to have maximum and minimum standards for certain products. For example, in the manufacture of a screw, it may be established that it can have a maximum height of 2.1 cm and a minimum height of 1.9 cm. The limits are already pre-established by industry standards.

In the example above, if you want to maintain the 6 sigma philosophy, your machinery should have an average of 2 cm and may have a maximum standard deviation of 0.1 cm / 6 = 0.01666... cm. Thus, the mean + 6 standard deviations would give 2.1 cm and the mean minus 6 standard deviations would give 1.9 cm; thus remaining compliant.

If the screw factory operated with 0.1/3 = 0.032 standard deviation, it would be operating at 3 sigma; in turn (according to the sigma level table we studied), there is an accuracy level of 93.3% and, on the other hand, 6.7% error or

66,807 DPMO.

After the application of the “Six Sigma” program, only with +/-6σ do we approach the lower and upper limits.

Thus, we can say that the company is at a 6σ level, in which, in turn (according to the sigma level table we studied), there is an accuracy level of 99.9996% and about 3.4 DPMO.

The process of applying 6 sigma is generally called DMAIC (acronym for the terms Define, Measure, Analyse, Improve and Control).

Phase 1 – Define

The “D” (Define) in the DMAIC process focuses on selecting high-impact projects and understanding which metrics will reflect the success of the project. In this DMAIC stage, the problems (or opportunities for improvement, as some prefer to call them) linked to the processes are defined. Here, the project goals and scope are clearly defined.

It is very important to identify the problems quantitatively. The use of indicators (for example, conformity, productivity, cost, customer satisfaction, etc.) will be used throughout the DMAIC process. Therefore, in the first phase, it is necessary to define what the problems of the process to be studied are, understand its purpose and what is expected from it, also stating which improvement in the indicator is expected.

The quantitative goals must be related to solving the problem and usually receive a percentage allocation (e.g.: 3% increase in production) and a set time (e.g.: three months).

Phase 2 – Measure

In measurement, we know and observe how things are going at the present moment. In this stage, you need to identify the potential causes of the problem and analyze the database. This will be done following two paths: a more quantitative path and a more qualitative one. In the quantitative path, we will take the database, select an indicator and study its behavior through some statistical tools that will be mentioned later.

In the qualitative path, we will study the process more deeply, trying to discover where the problem defined in the previous stage occurs. It is important to map the information that is important and that will help us identify the potential causes of the project.

Phase 3 – Analyze

In the measurement phase, the main inputs of the process and the causes and effects were identified. In this phase, statistical cross-checks are performed to determine whether there are cause-and-effect relationships.

It is divided into five analysis stages:

• root-cause analysis;

• process analysis;

• data analysis;

• resource analysis;

• communication analysis;

• conclusion.

Phase 4 – Improvement

In this DMAIC phase, improvements will be applied to the causes of the problems. For this, it is important to work closely with the people who are involved in product and process development.

In the DMAIC improvement phase, the most important document to be prepared by the team is the action plan. It must contain, at a minimum:

a) action to be taken (based on the sources of variation identified

during the analysis phase);

b) person responsible for each action;

c) expected implementation date;

d) document issue date and revision date;

e) if possible, a monitoring indicator for the action.

A good recommendation is the use of the tool known as 5W2H.

Phase 5 – Control

In the final phase of DMAIC, process improvements will be evaluated and it should be verified whether the improvements are occurring as expected and whether the results are continuous. This phase has several objectives; therefore, the project team should:

- Document the changes

- Continuous monitoring

Case studies with Six Sigma

Applying Six Sigma at Motorolalink outside website

Applying Six Sigma in a gymlink outside website

Applying Six Sigma in a hospital to improve patient mealslink outside website

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