Benchmarking and Its Types

What is a Benchmark?

A benchmark is a point of reference against which things are measured.

• Benchmarking is the process of comparing the cost, cycle time, productivity, or quality of a specific process or method to another that is widely considered to be an industry standard or best practice.Benchmarking is a systematic method by which organizations can measure themselves against the best industry practice.

• Benchmarking is the process of measuring an organization's internal processes then identifying, understanding, and adapting outstanding practices from other organizations considered to be best-in-class.

Most business processes are common throughout industries. For example; NASA has the same basic Human Resources requirements for hiring and developing employees as does American Express. British Telecom has the same Customer Satisfaction Survey process as Brooklyn Union Gas. These processes, albeit from different industries, are all common and can be benchmarked very effectively. It's called "getting out of the box".

 Levels of Benchmarking

•  Internal Benchmarking
• Competitive Benchmarking
• Non – Competitive Benchmarking
• World – Class Benchmarking

Types of Benchmarking 

• Process benchmarking: billing, order etc
• Performance benchmarking : features, quality
• Product benchmarking: dimensions
• Strategic benchmarking competitive adv

Ishikawa Diagrams or Cause & Effect Diagrams

Ishikawa Diagrams Definition

Ishikawa diagrams (also called fishbone diagrams, cause-and-effect diagrams orFishikawa) are diagrams that show the causes of a certain event -- created by Kaoru Ishikawa (1990). Common uses of the Ishikawa diagram are product design and quality defect prevention, to identify potential factors causing an overall effect. Each cause or reason for imperfection is a source of variation. Causes are usually grouped into major categories to identify these sources of variation. The categories typically include:

• People: Anyone involved with the process
• Methods: How the process is performed and the specific requirements for doing it, such as policies, procedures, rules, regulations and laws
• Machines: Any equipment, computers, tools etc. required to accomplish the job
• Materials: Raw materials, parts, pens, paper, etc. used to produce the final product
• Measurements: Data generated from the process that are used to evaluate its quality
• Environment: The conditions, such as location, time, temperature, and culture in which the process operates

Fig:-Fishbone Diagram

Cause & Effect Diagrams Definition

•  The Cause & Effect (CE) diagram, also sometimes called the ‘fishbone’ diagram, is a tool for discovering all the possible causes for a particular effect. The effect being examined is normally some troublesome aspect of product or service quality, such as ‘a machined part not to specification’, ‘delivery times varying too widely’, ‘excessive number of bugs in software under development’, and so on, but the effect may also relate to internal processes such as ‘high rate of team failures’.

• The major purpose of the CE Diagram is to act as a first step in problem solving by generating a comprehensive list of possible causes. It can lead to immediate identification of major causes and point to the potential remedial actions or, failing this, it may indicate the best potential areas for further exploration and analysis. At a minimum, preparing a CE Diagram will lead to greater understanding of the problem.

• The CE Diagram was invented by Professor Kaoru Ishikawa of Tokyo University, a highly regarded Japanese expert in quality management. He first used it in 1943 to help explain to a group of engineers at Kawasaki Steel Works how a complex set of factors could be related to help understand a problem. CE Diagrams have since become a standard tool of analysis in Japan and in the West in conjunction with other analytical and problem-solving tools and techniques.CE Diagrams are also often called Ishikawa Diagrams, after their inventor, or Fishbone Diagrams because the diagram itself can look like the skeleton of a fish.

Fig:-Cause and Effect Diagram

Run Charts

Run Charts Definition

• A run chart is a line graph of data plotted over time. By collecting and charting data over time, you can find trends or patterns in the process. Because they do not use control limits, run charts cannot tell you if a process is stable. However, they can show you how the process is running. The run chart can be a valuable tool at the beginning of a project, as it reveals important information about a process before you have collected enough data to create reliable control limits.

Fig:-Run Charts

• Run charts (often known as line graphs outside the quality management field) display process performance over time. Upward and downward trends, cycles, and large aberrations may be spotted and investigated further. In a run chart, events, shown on the y axis, are graphed against a time period on the x axis. For example, a run chart in a hospital might plot the number of patient transfer delays against the time of day or day of the week. The results might show that there are more delays at noon than at 3 p.m. Investigating this phenomenon could unearth potential for improvement. Run charts can also be used to track improvements that have been put into place, checking to determine their success. Also, an average line can be added to a run chart to clarify movement of the data away from the average.

Alternatives with run charts:

1. An average line, representing the average of all the y values recorded, can easily be added to a run chart to clarify movement of the data away from the average. An average line runs parallel to the x axis.
2. Several variables may be tracked on a single chart, with each variable having its own line. The chart is then called a multiple run chart.
3. Run charts can also be used to track improvements that have been put into place, checking their success.

Scatter Diagrams

Scatter Diagrams Definition

• Scatter diagrams show the relationship between two sets of variables. By looking at the diagram you can see whether there is a link between variables. Where there is a link it is called correlation. 
• The scatter diagram graphs pairs of numerical data, with one variable on each axis, to look for a relationship between them. If the variables are correlated, the points will fall along a line or curve. The better the correlation, the tighter the points will hug the line.

Fig:-Scatter Diagram

When to Use a Scatter Diagram

• When you have paired numerical data.
• When your dependent variable may have multiple values for each value of your independent variable.
• When trying to determine whether the two variables are related, such as…
• When trying to identify potential root causes of problems.
• After brainstorming causes and effects using a fishbone diagram, to determine objectively whether a particular cause and effect are related.
• When determining whether two effects that appear to be related both occur with the same cause.
• When testing for autocorrelation before constructing a control chart.

Pareto Chart

Definition Pareto Chart (Pareto Diagram)

A Pareto chart is a bar graph. The lengths of the bars represent frequency or cost (time or money), and are arranged with longest bars on the left and the shortest to the right. In this way the chart visually depicts which situations are more significant.

Ex:- Pareto Chart

When to Use a Pareto Chart

• When analyzing data about the frequency of problems or causes in a process.
• When there are many problems or causes and you want to focus on the most significant.
• When analyzing broad causes by looking at their specific components.
• When communicating with others about your data.

How To Make A Pareto Diagram

• STEP #1 - Determine the category classifications that you are going to use to group your defect data by. Use your check sheets to collect the data for the Pareto.

• STEP #2 - Decide on the time period to be used to record your information. One week, a month, etc. It is best to be consistent so that you have a standard to compare to if the data collection exercise is to be repeated again. You can't measure results achieved accurately without consistent measurement periods.

• STEP #3 - From the Check Sheet, total the occurrence of each item for the period measured. Each total will be represented by the length of a vertical bar, much like the Pareto chart example above.

• STEP #4 - (It is easier to keep your scale accuracy correct if you use graph paper). Draw horizontal and vertical axes on graph paper; or if no graph paper available, use a ruler to measure and draw evenly scaled vertical and horizontal lines that meet evenly (see figure 2 below).

 

Figure 2

• STEP #5 - Make your scale units at even multiples, such as 10, 20, etc. so as to have an even scale system (see figure 3 below).

 
Figure 3

• STEP #6 - Draw in the bars that correspond to the total numbers collected from your Check Sheet, starting on the far left, with the most frequent (highest number recorded) defective item. It is recommended that you leave a gap between each item bar for reading clarity. (Note: If you have several defective items with very small quantities, you can group them together in a category called "other", as long as their total is less than the previous bar heighth). Notice the figure 4 below.

 
Figure 4

• STEP #7 - Under the horizontal axis (line), label each of the bars so that you know which defect is represented by which bar.

• STEP #8 - Draw another vertical line and label the percentage scale in the same manner that you did on the left side (see figure 5 below)

 
Figure 5

• STEP #9 - Plot a dot for each item on the graph, starting from the left side, on or above the bar corresponding to the related percentage of defectives for each item. Once each dot is plotted, use a ruler and connect the line graph from dot-to-dot, as shown in the "Pareto example" up above.

• STEP #10 - Title the graph and briefly write the source of the data below the graph, that describes the data and method used to gather. Include all pertinent facts which will define the method of observation (for example, time period, production line, and whether this was before or after any modifications to the line). Recording this data on the bottom of your chart, will help further analysis as well as to provide a record of what was done on this date, for consideration in future studies.

Control Charts for Variable and Attributes

Variable Control Charts

Consider that you are evaluating the output from a process.  Conceptually, you could evaluate the products in two basic ways.  In the first way you would simply classify the products as "conforming" or "non conforming."  This produces attribute (discrete) data.  In the second way you could measure a key characteristic using a continuous scale.  This produces variable (continuous) data.

Variables control charts are used to evaluate variation in a process where the measurement is a variable--i.e. the variable can be measured on a continuous scale (e.g. height, weight, length, concentration). There are two main types of variables control charts.  One (e.g. x-bar chart, Delta chart) evaluates variation between samples. Non-random patterns (signals) in the data on these charts would indicate a possible change in central tendency from one sampling period to the next.  One way of thinking about the use of a variables control chart is that you are testing the hypothesis that a particular sample mean came from the population of sample means represented by the control limits of the process.  If the particular sample mean is within the control limits, your concusion is that it does come from that population.  If the particular sample mean is outside the control limits, you conclusion is that it may have come from some other distribution (i.e. a distribution with a mean that is higher or lower than this population mean.  [NOTE:  There are other signals that may indicate an out-of-control signal that will be discussed in the Lesson Six Presentation.]

The other type of variables control chart (e.g. R-chart, S-chart, Moving Range chart) evaluates variation within samples.  Non-random patterns (signals) in the data on these charts would indicate a possible change in the variation within the samples.

Non-random patterns in the data plotted on the control charts provide evidence of the process being in-control (only common cause variation present; predictable) or out-of-control (common cause andassignable cause variation present; unpredictable).  Adjusting a process which is in-control will result in increased variation.  Failing to adjust a process which is out-of-control results in a loss of predictability.  Control charts help a machine operator or manager to decide when it is appropriate to make an adjustment and when it is better to leave the process alone.

                                                 Attribute Control Charts

These charts are applied to data that follow a discrete distribution.

Types of attributes control chart:

p chart

This chart shows the fraction of nonconforming or defective product produced by a

manufacturing process.

It is also called the control chart for fraction nonconforming.

np chart

This chart shows the number of nonconforming. Almost the same as the p chart.

c chart

This shows the number of defects or nonconformities produced by a manufacturing process.

u charts

This chart shows the nonconformities per unit produced by a manufacturing process.

Process Control Chart

Process Control Chart Definition

• The control chart is a graph used to study how a process changes over time. Data are plotted in time order. A control chart always has a central line for the average, an upper line for the upper control limit and a lower line for the lower control limit. These lines are determined from historical data. By comparing current data to these lines, you can draw conclusions about whether the process variation is consistent (in control) or is unpredictable (out of control, affected by special causes of variation).

• Control charts for variable data are used in pairs. The top chart monitors the average, or the centering of the distribution of data from the process. The bottom chart monitors the range, or the width of the distribution. If your data were shots in target practice, the average is where the shots are clustering, and the range is how tightly they are clustered. Control charts for attribute data are used singly

When to Use a Control Chart

• When controlling ongoing processes by finding and correcting problems as they occur.
• When predicting the expected range of outcomes from a process.
• When determining whether a process is stable (in statistical control).
• When analyzing patterns of process variation from special causes (non-routine events) or common causes (built into the process).
• When determining whether your quality improvement project should aim to prevent specific problems or to make fundamental changes to the process.

Elements of a Control Chart

There are three main elements of a control chart are

• A control chart begins with a time series graph.
• A central line (X) is added as a visual reference for detecting shifts or trends – this is also referred to as the process location.
• Upper and lower control limits (UCL and LCL) are computed from available data and placed equidistant from the central line. This is also referred to as process dispersion.

Operations Management

Operations Management Definition

• "The on-going activities of designing, reviewing and using the operating system, to achieve service outputs as determined by the organisation for customers" 

•  The efficient and effective implementation of the policies and tasks necessary to satisfy an organisation’s customers, employees, and management (and stockholders, if a publicly owned company).

• Operations management teams design the method of conversion of inputs (materials, labor, proprietary information, etc.) into outputs (goods, services, value-added products, etc.) that is most beneficial to the organization. Operations management teams attempt to balance costs with revenue to achieve the highest net operating profit possible.

• Operations management refers to the administration of business practices to create the highest level of efficiency possible within an organization. Operations management is concerned with converting materials and labor into goods and services as efficiently as possible to maximize the profit of an organization.

• The management of systems or processes that create goods and/or provide services

• Operations management deals with the design and management of products, processes, services and supply chains. It considers the acquisition, development, and utilisation of resources that firms need to deliver the goods and services their clients want.

What do operations managers do?

Strategic (long term) Level

– Responsible for, and decisions about:

o What to make (product development)

o How to make it (process and layout decisions) – or should we buy it?

o Where to make it (site location)

o How much is needed (high level capacity decisions)

Tactical Level (intermediate term)

– Address material and labour resourcing within strategy constraints, for example:

o How many workers are needed and when (labour planning)

o What level of stock is required and when should it be delivered (inventory and replenishment planning)

o How many shifts to work. Whether overtime or subcontractors are required (detailed capacity planning)

Operational Level

– Detailed lower-level (daily/weekly/monthly) planning, execution and control decisions, for example:

o What to process and when (scheduling)

o The order to process requirements (sequencing)

o How work is put on resources (loading)

o Who does the work (assignments)

Total Quality Management Principle and Tools

Total Quality Management Tools

Total Quality Management (TQM) is the optimization and integration of all the functions and processes of a business in order to provide for excited customers through a process of continuous improvement.

Quality Improvement Teams

These are small groups of employees who work on solving specific problems related

to quality and productivity, often with stated targets for improvement. Quality

improvement teams are proving to be highly successful at tracking down the causes of

poor quality as well as taking remedial action.

Benchmarking

This is the process of identifying the best practices and approaches by comparing

productivity in specific areas within ones' own company to other organisations both

within and outside the industry.

Statistical process control

This is a statistical technique that uses periodic random samples taken during actual

production to determine whether acceptable quality levels are being met or whether

production should be stopped in order to take remedial action. Because most

processes produce some variation, statistical process control uses statistical tests to

determine when variations fall outside a narrow range around the acceptable quality

level. The emphasis when using SPC is on defect prevention rather than trying to

inspect the quality into the product.

Commitment

In order for the Eye on the Future Model to be a success, each member in an

organisation must be committed to the change process. It cannot be viewed as the new

flavor of the month, but should rather be regarded as an exciting life changing

process. Too often peoples' enthusiasm wanes when they realize that the change

process in an organisation is not likely to occur overnight People need to pledge their

support to objectively analyzing their job functions and procedures, and seeking new

innovative ways to improve them. If necessary inspirational speakers should be

employed to enthuse staff to a new attitude of commitment. Once again, people are

led by example. If it appears that management is not committed to the change process,

this is the attitude the people will develop. However, if commitment is perceived to

be the attitude of management, then the people are most likely to follow.

Training 

Training must be a part of the organisations succession planning. In today's business

environment any training which is less than visionary will not help the organisation

meet its' future goals and objectives. Training objectives must be supportive of the

company's vision and mission. In order to identify training, the employees must be

involved. System deficiencies including non-conformance reports, customer

complaints and job performance appraisals will highlight the most urgent areas for

development. Training programs must be devised and implemented to help bridge

the gap identified previously. The results of the training must be evaluated to ensure

that effective improvement has been achieved and that employees are competent to

use the skills acquired.

Total Quality Management

Definition Total Quality Management

Total Quality Management (TQM) is the optimisation and integration of all the 
functions and processes of a business in order to provide for excited customers 

through a process of continuous improvement. 

The Primary Elements of TQM

Total quality management can be summarized as a management system for a customer-focused organization that involves all employees in continual improvement. It uses strategy, data, and effective communications to integrate the quality discipline into the culture and activities of the organization.

·         Customer-focused. The customer ultimately determines the level of quality. No matter what an organization does to foster quality improvement—training employees, integrating quality into the design process, upgrading computers or software, or buying new measuring tools—the customer determines whether the efforts were worthwhile.

·         Total employee involvement. All employees participate in working toward common goals. Total employee commitment can only be obtained after fear has been driven from the workplace, when empowerment has occurred, and management has provided the proper environment. High-performance work systems integrate continuous improvement efforts with normal business operations. Self-managed work teams are one form of empowerment.

·         Process-centered. A fundamental part of TQM is a focus on process thinking. A process is a series of steps that take inputs from suppliers (internal or external) and transforms them into outputs that are delivered to customers (again, either internal or external). The steps required to carry out the process are defined, and performance measures are continuously monitored in order to detect unexpected variation.

·         Integrated system. Although an organization may consist of many different functional specialties often organized into vertically structured departments, it is the horizontal processes interconnecting these functions that are the focus of TQM.

·         Strategic and systematic approach. A critical part of the management of quality is the strategic and systematic approach to achieving an organization’s vision, mission, and goals. This process, called strategic planning or strategic management, includes the formulation of a strategic plan that integrates quality as a core component.

·         Continual improvement. A major thrust of TQM is continual process improvement. Continual improvement drives an organization to be both analytical and creative in finding ways to become more competitive and more effective at meeting stakeholder expectations.

·         Fact-based decision making. In order to know how well an organization is performing, data on performance measures are necessary. TQM requires that an organization continually collect and analyze data in order to improve decision making accuracy, achieve consensus, and allow prediction based on past history.

·         Communications. During times of organizational change, as well as part of day-to-day operation, effective communications plays a large part in maintaining morale and in motivating employees at all levels. Communications involve strategies, method, and timeliness.

Genichi Taguchi Quality Management Philosophy

Genichi Taguchi Quality Management Philosophy

Taguchi is famous for his pioneering methods of modern quality control and low-cost quality engineering. He is the founder of what has come to be known as the Taguchi method, which seeks to improve product quality at the design stage by integrating quality control into product design, using experiment and statistical analysis. His methods have been said to fundamentally change the philosophy and practice of quality control.

Taguchi methods

Taguchi developed methods for both online (process) and offline (design) quality control. This formed the basis of his approach to total quality control and assurance within a product's development life cycle. His approach emphasised improving the quality of product and process prior to manufacture (that is, at the design stage) rather than the more traditional approach of achieving quality through inspection.

Quality loss function

Taguchi's approach differed from the traditional one of manufacturing a product within a specification based on tolerances equally spaced around a target value. He developed a concept of quality loss occurring as soon as there is a deviation away from the target value, and worked in terms of quality loss rather than just quality. He defined quality loss as 'the loss imparted to society from the time the product is shipped', and this related the loss to society as a whole. Thus, it included both company costs such as reworking, scrapping and maintenance, and any loss to the customer through poor product performance and lowered reliability.

Signal to noise ratio

One of Taguchi's most innovative ideas was to utilise a 'quality' measure called the signal to noise ratio, which was then used by communications engineers to find the strength of an electrical signal. Taguchi applied this measure to everyday products, and used it as a measure to choose control levels that could best cope with changes in operating and environmental conditions, or noise.

Robust quality of design

On the basis of the signal to noise measure, Taguchi was able to develop the concept of robustness, which enables a product to be designed to be less affected by noise. Given normal variations in process operations, the product in question would be less likely to fail acceptable quality criteria.

Invest last not first

Taguchi placed much emphasis on initially optimising the product and process to engineer product quality (parameter design) into the system. Using low cost materials and components was a vital feature of this, and money was spent on higher cost items only when necessary (tolerance design).

Philip Crosby Quality Management Philosophy

Philip Crosby Quality Management Philosophy

Mr. Crosby defined quality as a conformity to certain specifications set forth by management and not some vague concept of "goodness." These specifications are not arbitrary either; they must be set according to customer needs and wants.

With this approach comes the 4 absolutes of Quality:

1. Quality is conformance to requirements

Following the same example, suppose I clean my room with great care. Thinking I have done a great job. However, my mother's idea of a clean room might be different. Leaving her dissatisfied. Thus clarity and agreement about the requirements must be established between the supplier and the customer. I must know what my mother means when she says, "Clean the room." Whether: a. the room has to be swept b. the articles have to be dusted c. the bed cover has to be changed Once I know the requirements, then 'Quality' is meeting the exact requirements without any 'defect'.

2. Quality comes from prevention - not detection

Quality can be established only before the task is performed. After a task is finished only analysis can be done. If while dusting, I keep thinking of my birthday party, I might forget to dust half the articles in the room. I do not have all the time in the world to clean the room as guests will be coming in 15 minutes. Hence I must have expertise with the broom, with the duster napkin and the ability to fold the bed neatly. This comes with practice. Hence at the core of Quality is practice. It takes years of practice before a trapeze artist can test the limits of human ability and perform the impossible. (S)he cannot afford a slip. A student must acquire skills of writing, comprehension and alertness to prepare for the exams beforehand to prevent unsatisfactory grades. Thus we must learn to think prevention. Prevention of defects.

3. The standard for Quality is Zero-Defect

Zero-Defect is not perfection. It is meeting the agreed requirements between the customer and the supplier without any gap. That is why the first step in Quality is to clarify the requirements of the customer and agree to meet them to the exact specifications. So, if I have swept the room, dusted the articles and changed the bedcover, in 15 minutes, I have met the exact requirements of my mother and have delivered zero-defect Quality. It is important to understand that a defect in Quality is always with respect to requirements agreed between the customer and the supplier. Our aim should be doing it right the first time, every time.

4. Quality is measured by the price of non-conformance

Whenever the requirements of the customer are not met, there is a price to pay. In the world of business this price is expressed in terms of money. In other spheres of human interaction, the price takes different forms - extra effort, hassles, de-motivation, lack of recognition, frustration, failure, etc. So, if I have not delivered Quality to my mother in terms of cleaning the room, I invite her anger and pay the price of unpleasant moments.

Joseph Juran Quality Management Philosophy

Joseph Juran Quality Management Philosophy

Juran, like Deming, was invited to Japan in 1954 by the Union of Japanese Scientists and Engineers (JUSE). His lectures introduced the management dimensions of planning, organizing, and controlling and focused on the responsibility of management to achieve quality and the need for setting goals.

Juran defines quality as fitness for use in terms of design, conformance, availability, safety, and field use. Thus, his concept more closely incorporates the viewpoint of customer. He is prepared to measure everything and relies on systems and problem-solving techniques. Unlike Deming, he focuses on top-down management and technical methods  rather than worker pride and satisfaction.

Juran’s 10 steps to quality improvement are:

1. Build awareness of opportunity to improve.
2. Set-goals for improvement.
3. Organize to reach goals.
4. Provide training
5. Carryout projects to solve problems.
6. Report progress.
7. Give recognition.
8. Communicate results.
9. Keep score.
10. Maintain momentum by making annual improvement part of the regular systems and processes of the company.

Juran is founder is the founder of Juran Institute in Wilton, Connecticut. He promoted a concept known as Managing Business Process Quality, which is a technique for executive cross-functional quality improvement. Juran contribution may, over the longer term, may be greater than Deming’s because Juran has broader concept, while Deming’s focus on statistical process control is more technical oriented.

Deming's Philosophy of Quality Management

Deming's 14 Point Philosophy of Quality Management

The need for a working understanding of basic quality management system statistical principles is at the heart of Deming's teaching. While accepting the ASQ's Shewhart Medal in 1955, he commented that "Statistical theory has changed practice in almost everything. Statistical techniques, in their ability to aid the discovery of causes, are creating a science of management and a science of administration." His quality process message, directed primarily at management, is stated succinctly in his famous 14 Points for Management:

1) Create constancy of purpose for improvement of product and service. Inspire the workers to stay competitive in the market and remind about the importance of stability in jobs and new opportunities which may come up in later stages, as inducing a sense of purpose in producing quality products will work as the inspiration to work efficiently.

2) Adopt the new philosophy. The customer demands and taste change very fast and the competition in the market grow at a rapid rate today, and we have to accept new philosophies according to the market trends and technology revolutions.

3) Cease dependence on mass inspection. Instead of inspecting the product for quality after production, infuse quality at the beginning itself with production quality control, as this will ensure no raw materials are wasted for the sake of quality.

4) End the practice of awarding business on price tag alone. Instead, minimize total cost - move towards a single supplier for any item, on trust.

5) Constantly and forever improve the system of production and service. Enterprise systems and services must keep growing indefinitely in order to catch up with the competitive market.

6) Institute modern methods of training on the job. A trained worker has more productivity and quality than an untrained one, so giving training sessions will drastically improve the quality of the person and directly it helps in better product quality performance.

7) Institute modern methods of supervision. A company can display stunning growth if potential leaders are identified and encouraged.

8) Drive out fear. Creating a fearful impression in the employees does not give more quality and productivity to work. If a person is not working willingly with satisfaction then he can never do a work perfectly even if he has the intention to be perfect in conscious mind, so driving out fear is essential.

9) Break down barriers between staff areas. The workers in design, sales, and production must work together to face problems and resolve them, which takes the company to better quality assurance management and also other profit with better planning.

10) Eliminate numerical goals for the work force. Slogans or exhortations call for more quantity in production than focusing on  quality control in manufacturing, which will severely damage the quality management process. Employees should have a calm and quiet quality atmosphere in the company.

11) Eliminate work standards and numerical quotas. This focuses on quantity rather than quality of product.

12) Remove barriers that hinder the hourly worker. Supervisor responsibility must be focused on quality, not numbers. Abolish annual or merit rating and MBO completely.

13) Institute a vigorous program of education and training. A person must grow after joining a company, and letting them learn new technology and techniques will increase employee longevity.

14) Create a situation in top management that will push every day on the above points. Just like products and services, every employee in a company must work to accomplish the transformation.

Quality Cost

Cost of Quality (COQ)

• Cost of quality is the amount of money a business loses because its product or service was not done right in the first place. From fixing a warped piece on the assembly line to having to deal with a lawsuit because of a malfunctioning machine or a badly performed service, businesses lose money every day due to poor quality. For most businesses, this can run from 15 to 30 percent of their total costs.

• The "cost of quality" isn't the price of creating a quality product or service. It's the cost of NOT creating a quality product or service.

Every time work is redone, the cost of quality increases. Obvious examples include:

• The reworking of a manufactured item.
• The retesting of an assembly.
• The rebuilding of a tool.
• The correction of a bank statement.
• The reworking of a service, such as the reprocessing of a loan operation or the replacement of a food order in a restaurant.

In short, any cost that would not have been expended if quality were perfect contributes to the cost of quality.

Total Quality Costs

As the figure below shows, quality costs are the total of the cost incurred by:

• Investing in the prevention of nonconformance to requirements.
• Appraising a product or service for conformance to requirements.
• Failing to meet requirements.

Quality Costs—general description

Prevention Costs

The costs of all activities specifically designed to prevent poor quality in products or services.

Examples are the costs of:

• New product review
• Quality planning
• Supplier capability surveys
• Process capability evaluations
• Quality improvement team meetings
• Quality improvement projects
• Quality education and training

Appraisal Costs

The costs associated with measuring, evaluating or auditing products or services to assure conformance to quality standards and performance requirements.

These include the costs of:

• Incoming and source inspection/test of purchased material
• In-process and final inspection/test
• Product, process or service audits
• Calibration of measuring and test equipment
• Associated supplies and materials

Failure Costs

The costs resulting from products or services not conforming to requirements or customer/user needs. Failure costs are divided into internal and external failure categories.

Internal Failure Costs

Failure costs occurring prior to delivery or shipment of the product, or the furnishing of a service, to the customer.

Examples are the costs of:

• Scrap
• Rework
• Re-inspection
• Re-testing
• Material review
• Downgrading

External Failure Costs

Failure costs occurring after delivery or shipment of the product — and during or after furnishing of a service — to the customer.

Examples are the costs of:

• Processing customer complaints
• Customer returns
• Warranty claims
• Product recalls

Total Quality Costs:

The sum of the above costs. This represents the difference between the actual cost of a product or service and what the reduced cost would be if there were no possibility of substandard service, failure of products or defects in their manufacture.