Chapter 1

Introduction to Quality

Quality as a Field

This chapter provides an overview of the field of quality, the importance of quality in today’s competitive global economy, and statistical process control. The chapter explores these topics and shows how various statistical tools can be used in improving the quality of the products and services.

Quality is a discipline that focuses on product and service excellence. Both manufacturing and service companies have quality programs. Quality is closely related to the variation in both products and processes, and statistics is the tool that allows us to study variation. Most of the quality programs are data driven and almost all data show variation that can be studied using statistics. One of the major objectives of the quality programs is to reduce the variation in the product and process to the extent that the likelihood of producing a defect is virtually nonexistent. This means improving quality and meeting or exceeding customer’s expectations. The improved quality and reliability in products and services lead to higher perceived value and increased market share, thereby, increasing revenue and profitability.

Before discussing various statistical tools and methods that are used to monitor and improve the quality of products and services, we explain the term quality and outline many different ways quality has been defined. Some of the definitions of quality are presented here.

Quality Defined

Quality means different things to different people. Therefore, quality can be defined from several different perspectives. From the perspective of the customer or the end user of the product or service, the quality of a product or service is the customer’s perception of the degree to which the product or service meets his or her expectations. This also means that the quality of a product or service can be determined by the extent to which the product or service satisfies the needs and requirements of the customers. This definition is a customer-driven quality approach that aims at meeting or exceeding customer expectations.

Quality has also been defined from several other perspectives. For example, quality may have a different meaning to the engineer who designs the product, or to the manufacturer involved in the production of a product. Thus quality can be defined from the perspective of the manufacturer or the designer. Quality has a transcendental definition and can also be product based, user based, manufacturing based, and value based (Garvin). Following are some of the other ways quality has been defined:

• Transcendent: Quality is something that is intuitively understood but nearly impossible to communicate, such as beauty or love.
• Product-based: Quality is found in the components and attributes of a product.
• User-based: If the product or service meets or exceeds customer’s expectations, it has good quality.
• Manufacturing-based: If the product conforms to design specifications, it has good quality.
• Value-based: If the product is perceived as providing good value for the price, it has good quality.

Quality has also been defined as:

• Meeting or exceeding customer expectation
• Fitness for intended use
• Conformance to specifications
• Inversely proportional to variation
• Total customer service and satisfaction
• The degree or standard of excellence of something

These definitions of quality show that although we can define quality from many different perspectives, the final judge of the product or service quality is the customer, and therefore, quality is the customer’s perception of the degree to which the product or service meets his or her expectations.

Dimensions of Quality

The dimensions of quality specify the characteristics the product or service should possess in order to be high quality. Garvin has identified eight dimensions of quality described here. These dimensions describe the product quality that is critical to developing high quality products or services. The recognition of these dimensions by the management and the selection of these dimensions along which the business will compete is critical to business success.

1. Performance: Will the product do the job?
2. Features or added features: Does it have features beyond the basic performance characteristics?
3. Reliability: Is it reliable? Will it last a long time?
4. Conformance: Does the product conform to the specifications? Is the product made exactly as the design specified?
5. Serviceability: Can it be fixed easily and cost effectively?
6. Durability: Can the product tolerate stress without failure?
7. Aesthetics: Does it have sensory characteristics such as taste, feel, sound, look, and smell?
8. Perceived quality: What is the customer’s opinion about the product or service? How customers perceive the quality of the product or service?

Importance of Quality

There is a close relationship between quality, profitability, and market share. Quality is achieved through customer’s perception, therefore, organizations must understand customer needs and expectations to meet and exceed them. Customer needs and expectations can be achieved through quality improvement. Quality is important to the consumers. In today’s highly competitive and global economy, a company cannot survive and stay in business unless they are able to provide high quality products and services. Figure 1.1 shows how improving quality can help organizations increase their market share and increase profitability.

Figure 1.1 Quality, profitability, and market share

Costs of Quality and Costs of Poor Quality

Quality is also important because the quality—both good and bad—costs money. There is a cost involved with improving the quality of products and services, because poor quality can significantly affect an organization’s competitiveness and market share. In his book Quality is Free, Phillip Crosby has described quality costs or the costs of quality (COQ) as having two components: (1) costs of good quality (or the cost of conformance) and (2) costs of poor quality (or the cost of nonconformance). These are shown in Figure 1.2.

The focus of many quality programs is to reduce the cost of poor quality. Since the cost of poor quality is significant, reducing this cost will lead to increased revenue and improved productivity. A quality program should be focused on preventing poor quality. A prevention system is focused on preventing the poor quality and is far superior to a detection system that detects the defects and nonconformities in the products after they are produced.

Figure 1.2 Costs of quality

The major components of costs of good quality—prevention costs and appraisal costs, and the costs of poor quality—internal failure and external failure costs, are explained in Table 1.1.

Detection Versus Prevention Quality Systems

Figure 1.3 shows the quality costs under detection and prevention systems (Griffith 2000). The costs under the detection system are similar to the costs that are measured for the first time in a company that has no formal quality prevention system in place. In the detection system, the costs of internal failure (e.g., scrap, rework, repair, and retest) are almost equal to the appraisal costs (e.g., inspection, testing, and auditing). The internal failure and appraisal costs tend to increase simultaneously. Since no or little prevention efforts are in place, more inspection is performed that finds more defects. On the other hand, as more defects are produced, more inspection is required. In a detection system, the external failure costs are small because of high inspection. The prevention costs are also small in a detection system.

A prevention quality system focuses on preventing failures and defects. Several companies have reported significant reduction in cost of poor quality through Six Sigma quality, which is a prevention quality program.

Table 1.1 Quality costs

Figure 1.3 Quality costs: Detection system versus prevention system (a) Quality costs in a detection system, (b) Quality costs in a prevention system

Systems and Processes

The quality methods and tools are applied to the systems and the processes that make the systems. The system and the processes within the system are responsible for creating the products or services. Therefore, it is important to understand the systems and the processes.

Systems

A system usually consists of a group of interacting, interrelated, or interdependent processes forming a complex whole. Thus a system is a collection of processes with a specific mission or purpose. Figure 1.4 shows the model of a basic system. A process can be viewed as a part of a system.

Some examples of systems are electronic manufacturing or food processing companies which produce electronic or food products. Such systems are usually a collection of interacting or interrelated processes; for example, both the electronic manufacturing and food processing plants may consist of a number of departments including manufacturing engineering, marketing, design engineering, sales, transportation, warehousing, finance and accounting, and distribution systems.

All these departments can be viewed as processes. In manufacturing or food processing companies, the raw materials are converted into useful products, which are outputs. Such systems as shown in Figure 1.4 have a feedback through which the companies receive information about their products from the customers and market. This information is helpful in changing or modifying their processes and products to adapt to the needs and requirements of their customers.

Figure 1.4 A basic system

The other types of systems are the service systems. These systems exist to provide various types of services to their customers. Examples of such systems are education institutions, government organizations, technical call centers, health care organizations, hospitals, and insurance companies. These systems also consist of a number of processes and provide services through the collection of processes. The outputs of the service systems are usually intangible.

Processes

In many cases, the focus of statistical analysis has been to draw conclusions or make decisions about the population using the sample data. The other aspect of statistical analysis is to study and reduce the variation in the products or processes studied using data. Statistics and statistical methods enable us to study variation in the processes. Almost all data show variation and controlling or minimizing variation in products and processes lead to improved product quality. The variance in a process is an important measure of the quality of the products and processes. A large variation in any product, process, or both is not desirable and is an indication that the process be improved by finding ways to reduce the process variance. As variation in the products and processes is reduced, the product or the process becomes more consistent. Therefore, one of the major objectives of quality programs like Six Sigma is to reduce variation in product, process, or service.

In this text, we will study how the variations in the processes affect the product quality. To study this, we will explore the relationship between the variation and product quality, and the statistical tools that are used to study, monitor, and control the variation. This area comes under statistical process control.

Since the quality of products and services is related to the variation in products and the processes that create the products, we will first define and study the processes. A process can be a chemical process, or a manufacturing process. The processes in general use the inputs that go through a transformation to produce outputs or useful products.

Any organization, or any of its parts, can be viewed as a process. A process is a transformation of inputs into outputs. Some examples of processes include electronic and appliance manufacturing processes, computer and car assembly lines, and chemical processing plants. A process in its simplest form is shown in Figure 1.5.

Figure 1.5 A process in its simplest form

Figure 1.6 An input-output process

A process usually consists of a sequence or network of activities that depicts the flow of the complete procedure required to transform the inputs into outputs (useful product or service). The transformation is achieved by flows through network of activities that are performed by various resources. Figure 1.6 shows an input output process.

Outputs of Processes and Variation

The processes, as discussed earlier, take inputs and convert them into outputs using some type of transformation process. Systems, on the other hand, may consist of a number of processes. It is important to note the following characteristics of the system outputs and the outputs produced by the processes of the system:

1. The outputs of the process always vary.
2. The products produced by the same processes are different. This means that no two products are identical and the measured quality characteristic of products vary. For example, the volumes of two beverage cans labeled 16 oz. are not exactly the same; the two tires that are 13.0 inches in radius are not both exactly the same radius. Figure 1.7 shows the measurements of the diameters of a 13.0-inch radius tires that are manufactured by the same process. The radius in this case is a critical quality characteristic of the product or the output. Notice how the measured radius varies from product to product (the last block in Figure 1.7 that shows the measured values of several products). Similarly, the computers and calculators made by the same processes are not exactly the same. Although the products look alike, they always vary in critical quality characteristics. The variation in many cases is not noticeable. The variations in product characteristic do not affect the functionality as long as the variation is within a certain limit.
3. Variation is an inherent characteristic in products and processes.

Figure 1.7 Variation in quality characteristic (diameters of tires)

As long as the variation in products and processes that produce these products is within certain limit, the product is acceptable. When the variation increases beyond the desired or set limits, the product quality, functionality, and reliability are affected. This is the reason why the variation in the products and processes must be monitored and controlled. The variation in the products and processes can be studied using statistical tools.

Sources of Variation in Products and Processes

The major sources of variation in the products and processes are attributed to the following factors:

1. Materials
2. Men (Operator)
3. Machines
4. Methods
5. Measurement
6. Environment

These sources of variation are shown in Figure 1.8(a) and (b) where (a) shows the general categories that are common sources of variation and (b) shows the details. Note that all categories may not apply to all products or services.

Figure 1.8(a) Sources of variation in products and processes

Figure 1.8(b) Sources of variation in products and processes

In the rest of the chapter, we will see how the variation in the products and processes are studied, measured, and controlled.

Measuring Variation

The variation in the data is measured using the variance and standard deviation. The Greek letter σ² (read as sigma-squared) represents the variance of a population data and σ represents the standard deviation. The corresponding symbols for the variance and standard deviation of a sample data are s² and s. The standard deviation σ is a measure of spread or deviation around the mean as shown in Figure 1.8(c). We may have two or more sets of data all having the same average, but their spread or variability may be different. This is shown in Figure 1.8(d). It can be seen from this figure that the data sets A and B have the same mean but different variations—curve B has less spread or variability than curve A. The more variation the data has, the more spread out the curve will be. We may also have a case where two sets of data have the same variation but different mean.

Figure 1.8(c) The measure of variation—standard deviation

Figure 1.8(d) Data sets A and B with same mean but different variation

Figure 1.8(e) Plot showing the variation in assembly time

The variation in the data can also be plotted using a graph. Suppose that the average time to assemble a product is 4.0 minutes. The average assembly time for all the products is not going to be exactly 4.0 minutes. This means that the assembly time will vary from product to product. The variation in the assembly time can be studied using a graph that is shown in Figure 1.8(e). This graph shows the assembly time of a sample of 30 products. Note how the assembly time varies around the average of 4.0 minutes.

Summary

This chapter provided an overview of the field of quality, various ways quality has been defined, and the importance of quality in today’s competitive global economy. Quality is a discipline that focuses on product and service excellence. Both manufacturing and service companies have quality programs. Quality is closely related to the variation in both products and processes, and statistics is the tool that allows us to study variation. Most of the quality programs are data driven and almost all data show variation. One of the major objectives of the quality programs is to reduce the variation in the product and process to the extent that the likelihood of producing a defect is virtually nonexistent. This means improving quality and meeting or exceeding customer’s expectations. The chapter described the dimensions of product quality. These are the characteristics that the product and service should possess in order to be of high quality. The COQ were also discussed. Cost of poor quality is a significant percent of the sales dollars in companies. Reducing these costs leads to improved quality, higher perceived value by the customer, and increased market share. The chapter emphasized on the importance of prevention quality programs like Six Sigma and Lean Six Sigma quality programs. These programs have been applied with tremendous success in a large number of companies. The tools of quality are applied to systems and processes within the systems. These systems and processes are responsible for creating goods and services. The chapter provided an overview of the systems and processes. Finally, the sources of variation in products and processes were discussed and it was shown that there is always a variation when we measure the critical quality dimensions. No two products are exactly the same. There is always some degree of variation in them. Quality is all about studying, reducing, and controlling the variations to improve product or service quality.