ISO 9000 Standard

ISO (International Organization for Standardization) 9000 series standards were first published in 1987, revised in 1994, and re-revised in 2000 by the ISO. The 2000 revision, denoted by ISO 9000:2000, has attracted broad expectations in industry.

 As of the year 2001, more than 300,000 organizations world-wide have been certified to the ISO 9000 series standards. It embodies a consistent pair of standards, ISO 9001:2000 and ISO 9004:2000, both of which have been significantly updated and modernized. The ISO 9001:2000 standard specifies requirements for a quality management system for which third-party certification is possible, whereas ISO 9004:2000 provides guide- lines for a comprehensive quality management system and performance improvement through Self-Assessment.

 The origin and historical development of ISO 9000 and Six Sigma are very different. The genesis of ISO 9000 can be traced back to the standards that the British aviation industry and the U.S. Air Force developed in the 1920s to reduce the need for inspection by approving the conformance of suppliers’ product quality. These standards developed into requirements for suppliers’ quality assurance systems in a number of western countries in the 1970s. In 1987 they were amalgamated into the ISO 9000 series standards.

Independent of ISO 9000, the same year also saw the launch of Six Sigma at Motorola and the launch of Self-Assessment by means of the Malcolm Baldrige National Quality Award in USA. Both Six Sigma and Self-Assessment can be traced back to Walter A. Shewhart and his work on variation and continuous improvement in the 1920s. It was Japanese industry that pioneered a broad application of these ideas from the 1950s through to the 1970s. When variation and continuous improvement caught the attention of some of the American business leaders in the late 1980s, it took the form of the Malcolm Baldrige National Quality Award, on a national level, and of Six Sigma at Motorola.

Some people are wondering if the ISO 9000:2000 series standards make Six Sigma superfluous. They typically refer to clause 8 of ISO 9001: It requires that companies install procedures in operations for the measurement of processes and data analysis using statistical techniques with the demonstration of continuous improvement . They also partly refer to the ISO 9004:2000 standards that embody guidelines and criteria for Self-Assessment similar to the national quality awards.

The ISO 9000 series standards have from their early days been regarded and practiced by industry as a minimum set of requirements for doing business. The new ISO 9000:2000 stan

dards do not represent a significant change to this perspective. Six Sigma on the other hand, aims at world-class performance, based on a pragmatic framework for continuous improvement.

The author believes that Six Sigma is superior in such important areas as rate of improvement, bottom-line and top-line results, customer satisfaction, and top-level management commitment. However, considering the stronghold of ISO 9000 in industry, Six Sigma and ISO 9000 are likely to be applied by the same organization, but for very different purposes.

Six Sigma (s ) is a letter in the Greek alphabet that has become the statistical symbol and metric of process variation. The sigma scale of measure is perfectly correlated to such characteristics as defects-per-unit, parts-per-million defectives, and the probability of a failure. Six is the number of sigma measured in a process, when the variation around the target is such that only 3.4 outputs out of one million are defects under the assumption that the process average may drift over the long term by as much as 1.5 standard deviations.

Six Sigma may be defined in several ways. Tomkins (1997) defines Six Sigma to be “a program aimed at the near-elimination of defects from every product, process and transaction.” Harry (1998) defines Six Sigma to be “a strategic initiative to boost profitability, increase market share and improve customer satisfaction through statistical tools that can lead to breakthrough quantum gains in quality.”

Six Sigma was launched by Motorola in 1987. It was the result of a series of changes in the quality area starting in the late 1970s, with ambitious ten-fold improvement drives. The top-level management along with CEO Robert Galvin developed a concept called Six Sigma. After some internal pilotm implementations, Galvin, in 1987, formulated the goal of

“achieving Six-Sigma capability by 1992” in a memo to all Motorola employees (Bhote, 1989). The results in terms of reduction in process variation were on-track and cost savings totalled US$13 billion and improvement in labor productivity achieved 204% increase over the period 1987–1997 (Losianowycz, 1999). In the wake of successes at Motorola, some leading elec-

tronic companies such as IBM, DEC, and Texas Instruments launched Six Sigma initiatives in early 1990s. However, it was not until 1995 when GE and Allied Signal launched Six Sigma as strategic initiatives that a rapid dissemination took place in non-electronic industries all over the world (Hendricks and Kelbaugh, 1998). In early 1997, the Samsung and LG Groups in Korea began to introduce Six Sigma within their companies. The results were amazingly good in those companies. For instance, Samsung SDI, which is a company under the Samsung Group, reported that the cost savings by Six Sigma projects totalled US$150 million (Samsung SDI, 2000a). At the present time, the number of large companies applying Six Sigma in Korea is growing exponentially, with a strong vertical deployment into many small- and medium-size enterprises as well.

 As a result of consulting experiences with Six Sigma in Korea, it was believed that Six Sigma is a “new strategic paradigm of management innovation for company survival in this 21st century, which implies three things: statistical measurement, management strategy and quality culture.” It tells us how good our products, services and processes really are through statistical measurement of quality level. It is a new management strategy under leadership of top-level management to create quality innovation and total customer satisfaction. It is also a quality culture. It provides a means of doing things right the first time and to work smarter by using data information. It also provides an atmosphere for solving many CTQ (critical-to-quality) problems through team efforts.

 CTQ could be a critical process/product result characteristic to quality, or a critical reason to quality characteristic. The former is termed as CTQy, and the latter CTQx.

Six Sigma has become very popular throughout the whole world. There are several reasons for this popularity. First, it is regarded as a fresh quality management strategy which can replace TQC, TQM and others.

Many companies, which were not quite successful in implementing previous management strategies such as TQC and TQM, are eager to introduce Six Sigma.

Development process of Six Sigma in quality management

Six Sigma is viewed as a systematic, scientific, statistical and smarter (4S) approach for management innovation which is quite suitable for use in a knowledge-based information society.

Second, Six Sigma provides efficient manpower cultivation and utilization. It employs a “belt system” in which the levels of mastery are classified as green belt, black belt, master black belt and champion. As a person in a company obtains certain 

training, he acquires a belt. Usually, a black belt is the leader of a project team and several green belts work together for the project team.

Third, there are many success stories of Six Sigma application in well known world-class companies. As mentioned earlier, Six Sigma was pioneered by Motorola and launched as a strategic initiative in 1987. Since then, and particularly from 1995, an exponentially growing number of prestigious global firms have launched a Six Sigma program. It has been noted that many globally leading companies run Six Sigma programs (see Figure 3), and it has been well known that Motorola, GE, Allied Signal, IBM, DEC, Texas Instruments, Sony, Kodak, Nokia, and Philips Electronics among others have been quite successful in Six Sigma. In Korea, the Samsung, LG, Hyundai groups and Korea Heavy Industries & Construction Company have been quite successful with Six Sigma.

Lastly, Six Sigma provides flexibility in the new millennium of 3Cs, which are:

• Change: Changing society

• Customer: Power is shifted to customer and customer demand is high

• Competition: Competition in quality and productivity

The pace of change during the last decade has been unprecedented, and the speed of change in this new millennium is perhaps faster than ever before. Most notably, the power has shifted from producer to customer. The producer-oriented industrial society is over, and the customer-oriented information society has arrived. The customer has all the rights to order, select and buy goods and services. Especially, in e-business, the customer has all-mighty power.

 Six Sigma with its 4S(systematic, scientific, statistical and smarter) approaches provides flexibility in managing a business unit.

The 7 QC Tools

The Seven Quality Control tools (7QC tools) are graphical and statistical tools which are most often used in QC for continuous improvement. Since they are so widely utilized by almost every level of the company, they have been nicknamed the Magnificent Seven. They are applicable to improvements in all dimensions of the process performance triangle: variation of quality, cycle time and yield of productivity.

 Each one of the 7QC tools had been used separately before 1960. However, in the early 1960s, they were gathered together by a small group of Japanese scientists lead by Kaoru Ishikawa, with the aim of providing the QC Circles with effective and easy-to-use tools. They are, in alphabetical order, cause-and-effect diagram, check sheet, control chart, histogram, Pareto chart, scatter diagram and stratification. In Six Sigma, they are extensively used in all phases of the improvement methodology – define, measure, analyze, improve and control.

(1) Cause-and-effect diagram

An effective tool as part of a problem-solving process is the cause-and-effect diagram, also known as the Ishikawa diagram (after its originator) or fishbone diagram. This technique is useful to trigger ideas and promote a balanced approach in group brainstorming sessions where individuals list the perceived sources (causes) with respect to outcomes (effect).

When constructing a cause-and-effect diagram, it is often appropriate to consider six main causes that can contribute to an outcome response (effect): so-called 5M1E (man, machine, material, method, measurement, and environment).

When preparing a cause-and-effect diagram, the first step is to agree on the specific wording of the effect and then to identify the main causes that can possibly produce the effect. The main causes can often be identified as any of 5M1E, which helps us to get started, but these are by no means exhaustive.

 Using brainstorming techniques, each main cause is analyzed. The aim is to refine the list of causes in greater detail until the root causes of that particular main cause are established. The same procedure is then followed for each of the other main causes. The method is a main cause, the pressure and the temperature are the causes, and “the pressure is low” and “the temperature is too high” are the root causes.

 (2) Check sheet

The check sheet is used for the specific data collection of any desired characteristics of a process or product that is to be improved. It is frequently used in the measure phase of the Six Sigma improvement methodology, DMAIC. For practical purposes, the check sheet is commonly formatted as a table. It is important that the check sheet is kept simple and that its design is aligned to the characteristics that are measured. Consideration should be given as to who should gather the data and what measurement intervals to apply. For example, Figure 4.2 shows a check sheet for defect items in an assembly process of automobile ratios.

(3) Control chart

(a) Introduction

The control chart is a very important tool in the “analyze, improve and control” phases of the Six Sigma improvement methodology. In the “analyze” phase, control charts are applied to judge if the process is predictable; in the “improve” phase, to identify evidence of special causes of variation so that they can be acted on; in the “control” phase, to verify that the performance of the process is under control.

The original concept of the control chart was proposed by Walter A. Shewhart in 1924 and the tool has been used extensively in industry since the Second World War, especially in Japan and the USA after about 1980. Control charts offer the study of variation and its source. They can give process monitoring and control, and can also give direction for improvements. They can separate special from common cause issues of a process. They can give early identification of special causes so that there can be timely resolution before many poor quality products are produced. Shewhart control charts track processes by plotting data over time in the form shown in Figure 4.3. This chart can track either variables or attribute process parameters. The types of variable charts are process mean (x), range (R), standard deviation (s), individual value (x) and moving range (Rs). The attribute types are fraction nonconforming (p), number of nonconforming items (np), number of nonconformities (c), and nonconformities per unit (u).

(4) Histogram

 It is meaningful to present data in a form that visually illustrates the frequency of occurrence of values. In the analysis phase of the Six Sigma improvement methodology, histograms are commonly applied to learn about the distribution of the data within the results Ys and the causes Xs collected in the measure phase and they are also used to obtain an understanding of the potential for improvements.

(5) Pareto chart

 The Pareto chart was introduced in the 1940s by Joseph M.Juran, who named it after the Italian economist and statistician Vilfredo Pareto, 1848–1923. It is applied to distinguish the “vital few from the trivial many” as Juran formulated the purpose of the Pareto chart. It is closely related to the so-called 80/20 rule – “80% of the problems stem from 20% of  the causes,” or in Six Sigma terms “80% of the poor values in Y stem from 20% of the Xs.”

 In the Six Sigma improvement methodology, the Pareto chart has two primary applications. One is for selecting appropriate improvement projects in the define phase. Here it offers a very objective basis for selection, based on, for example, frequency of occurrence, cost saving and improvement potential in process performance.

 The other primary application is in the analyze phase for identifying the vital few causes (Xs) that will constitute the greatest improvement in Y if appropriate measures are taken.

 A procedure to construct a Pareto chart is as follows:

1) Define the problem and process characteristics to use in the diagram.

2) Define the period of time for the diagram – for example, weekly, daily, or shift.

Quality improvements over time can later be made from the information determined within this step.

3) Obtain the total number of times each characteristic occurred.

4) Rank the characteristics according to the totals from

(6) Scatter diagram

 The scatter plot is a useful way to discover the relationship between two factors, X and Y, i.e., the correlation. An important feature of the scatter plot is its visualization of the correlation pattern, through which the relationship can be determined. In the improve phase of the Six Sigma improvement methodology, one often searches the collected data for Xs that have a special influence on Y. Knowing the existence of such relationships, it is possible to identify input variables that 

cause special variation of the result variable. It can then be determined how to set the input variables, if they are controllable, so that the process is improved. When several Xs may influence the values of Y, one scatter plot should be drawn for each combination of the Xs and Y.

(7) Stratification

Stratification is a tool used to split collected data into subgroups in order to determine if any of them contain special cause variation. Hence, data from different sources in a process can be separated and analyzed individually. Stratification is mainly used in the analyze phase to stratify data in the

search for special cause variation in the Six Sigma improvement methodology.

The most important decision in using stratification is to determine the criteria by which to stratify. Examples can be machines, material, suppliers, shifts, day and night, age groups and so on. It is common to stratify into two groups. If the number of observations is large enough, more detailed stratification is also possible.