Total Quality Management

September 21, 2008

Management of Process Quality

What is the difference between QA and QC?

If you ask people doing jobs in “production” or “quality control” departments,  you would be surprised to learn that confusion about these terminologies exist in their minds also. This assertion sounds weird, yet this is a reality.

Why so many people and organizations are confused about the difference between quality assurance (QA) and quality control (QC) is the result of  lack of training about basics of quality related concepts. Both QA and QC are closely related, but they are different concepts.

Quality Assurance is a set of activities designed to ensure that the development and/or maintenance process is adequate to ensure a system will meet its objectives. It is also described as feed-forward system. Feed-forward system attempts to prevent the defect from happening. In other words it requires to be proactive rather than reactive.

Quality Control is a set of activities designed to evaluate a developed work product. It is based on traditional product inspection system in which a product is checked for quality when it is already completed or manufactured.

In this case a variation or defect is already occurred and nothing could be done to correct it. This also known as feedback quality control system.

Define process?

A process is a set of causes and conditions and a set of steps comprising an activity that transform inputs into outputs. For example consider the number of processes involved in airline industry: the process of taking and confirming a reservation, baggage handling, loading of passengers, of meal services, etc.

What are the characteristics of a process?

The process is any set of people, equipment, procedures, and conditions that work together to produce a result -an output. It is expected to add value to the inputs in or to produce an output. The ratio of output to input is called productivity and the objectives are:

To increase the ratio of output to input, and reduce the variation in the output of the process.
If the variation is too small or insignificant to have any effect on the  usefulness of the product or service, the output is said to be within tolerance.

Should the output fall outside the desired tolerance, the process can be improved and returned to tolerance by defining cause of the change (the problem) and taking action to make sure that cause does not recur.

Define Statistical Process Control?

One of the best technical tools for improving product and service quality is statistical Process Control. It involves the use of statistical techniques to analyze a work process or its output. The data can be used to identify variations and to take countermeasures to improve the capability of the process.

The term statistical process control can be misleading because it is so frequently confined to manufacturing processes whereas the method can be useful for improving results in other non-manufacturing areas such as sales and staff activities.

The statistical process control is equally applicable in many of the activities and functions of service industry.

What is the basic approach to Statistical Quality Control?

Statistical process control were initially developed in the United States in the 1930s and 1940s by W.A. Shewhart, W.E. Deming and J.M. Juran and others. The basic approach contains the following steps:

  • Awareness that a problem exists
  • Determine the specific problem to be solved
  • Diagnose the causes of the problem
  • Determine and implement remedies to solve the problem
  • Implement controls to hold the gains achieved by solving the problem.

Describe Seven QC Tools.

One of the technical tools for improving product and service quality is Statistical Process Control (SPC). There are 7 basic techniques. Since first four techniques are not really statistical, the word statistical is somewhat of a misnomer. This technical tool not only controls the process but has the capability to improve it as well. These tools are listed below:

1. Pareto Diagram
2. Process Flow Chart
3. Cause-and-Effect Diagram
4. Check Sheet
5. Histograms
6. Control Chart
7. Scatter Diagram


Alfred Pareto

Alfred Pareto

In 1879, the famous Italian economist Alfred Pareto, noticed that 80% of Italy’s wealth was controlled by 20% of the population. This concept is known as Pareto’s law or Pareto’s rule or Principle of imbalance or simply 80/20 rule.

Subsequently, people in various disciplines and professions noticed that this same 80/20 applied, in a broad way, to a wide range of phenomena. Dr. Joseph Juran also recognized this concept as universal that could be applied to many fields. He coined the term vital few and useful many.

When and why Pareto Chart is used in the Statistical Quality Control?

Pareto chart is a powerful quality tool and is used to identify the most important problem and the measurement of progress.

Pareto Chart

Construction of Pareto Chart

Construction of Pareto Chart is simple. There are five steps:

  1. Determine the method of classifying data: by problem, cause, non-conformity, and so forth.
  2. Decide if Money (Rs), frequency, or both are to be used to rank the characteristics.
  3. Collect data for an appropriate time interval or use historical data.
  4. Summarize the data and rank order categories from largest to smallest.
  5. Construct the diagram and find vital few.

Process Flow Diagram

A flow chart is a pictorial representation showing all the steps and processes involve in the operation.
The diagram makes it easy to visualize the entire system, identify potential trouble spots, and locate control activities. It answers the question, “Who is the next customer?”. Improvements can be accomplished by changing, reducing, combining, or eliminating steps.



What are the benefits of using Flow Chart in improving quality?

Following items can be analyzed to improve system in the organization:

  • Time-per-event (reducing cycle time)
  • What are the benefits of using Flow Chart in improving quality?
  • Process repeats (preventing rework)
  • Duplication of effort (identifying and eliminating duplicated tasks)
  • Unnecessary tasks (eliminating tasks that are in the process for no apparent reason)
  • Value-added versus non-value-added tasks


A cause-and-effect (C&E) diagram is basically a brainstorming tool. It is designed to represent a meaningful relationship between effect and its causes. It was developed by Dr. Kaoru Ishikawa and is sometimes refer to as an Ishikawa diagram or a fishbone diagram because of its shape. C&E diagrams are used to investigate either a “bad” effect or problem and to correct the causes or a “good” effect and to learn those causes that are responsible.

The C&E diagrams has nearly unlimited application in research, manufacturing, marketing, office operations, services, etc.


Selection of Causes for Cause-and-Effects Diagram

Causes in a typical diagram are normally arranged into categories, the main ones of which are:

  • The 6 Ms (Recommended for manufacturing industry)
    Machine, Method, Materials, Measurement, Man and Mother Nature (Environment)
  • The 8 Ps (Recommended for administration and service industry)
    Price, Promotion, People, Processes, Place / Plant, Policies, Procedures & Product (or Service)
  • The 4 Ss (Recommended for service industry)
    Surroundings, Suppliers, Systems, Skills

Golden rules for Constructing an Effective Cause-and-Effects Diagram

As stated earlier,  it’s a brainstorming or idea generating technique and usually done by a project team. It uses the creative thinking capacity of team. Attention should be give to the following elements for more accurate and usable results:

  1. Participation by every member of team is facilitated by each member taking a turn giving one idea at a time. If a member cannot think of minor cause, he or she passes that round. Another idea may occur at later round. Following this procedure prevents one or two individuals from dominating the brain storming session.
  2. Quantity of ideas, rather than quality, is encouraged. One person’s idea will trigger someone else’s idea, and a chain reaction occurs. Frequently, a trivial, or “dumb,” idea will lead to the best solution.
  3. Criticism of an idea is not allowed. All ideas are placed on diagram. Evaluation of ideas occurs at a later time.
  4. Visibility of the diagram is a primary factor of participation. In order to have space for all minor causes, a 2-foot by 3-foot piece of paper is recommended. It should be taped to a wall for maximum visibility. Whiteboards can be used for the same purpose also.
  5. Create a solution-oriented atmosphere and not a gripe session. Focus on solving a problem rather than discussing how it began. The team leader should ask questions using the why, what, where, when, who, and how techniques.
  6. Let the ideas incubate for a period of time (at least overnight) and then have another brainstorming session. Provide team members with a copy of ideas after the first session. When no more ideas are generated, the brainstorming activity is terminated.


The check sheet also called defect concentration diagram is a simple document that is used for collecting data in real-time and at the location where the data is generated. The main purpose of check sheets is to ensure that the data is collected carefully and accurately by operating personnel.

The data should be collected in such a way that it should be quickly and easily used and analyzed.

A defining characteristic of a check sheet is that data is recorded by making marks (“checks”) on it.

Check sheets have no standard format. It is based on the creativity of data collector and it design depends on the requirement, recording and marking of data.


When to use a checksheet

  • When data can be observed and collected repeatedly by the same person or at the same location.
  • When collecting data on the frequency or patterns of events, problems, defects, defect location, defect causes, etc.
  • When collecting data from a production process.


A histogram is a graphical display of tabulated frequencies. A histogram is the graphical version of a table which shows what proportion of cases fall into each of several or many specified categories.
It differs from a bar chart in that it is the area of the bar that denotes the value, not the height, a crucial distinction when the categories are not of uniform width.


Histograms can give sufficient information about a quality problem to provide a basis for decision making without further analysis. A histogram is like a snapshot of process showing the variation.
Histograms can determine the process capability, compare with specifications, suggest the shape of population, and indicate discrepancies in data such as gaps.

When to use histograms

When the data are numerical.

When you want to see the shape of the data’s distribution, especially when determining whether the output of a process is distributed approximately normally.

  • When analyzing whether a process can meet the customer’s requirements.
  • When analyzing what the output from a supplier’s process looks like.
  • When seeing whether a process change has occurred from one time period to another.
  • When determining whether the outputs of two or more processes are different.
  • When you wish to communicate the distribution of data quickly and easily to others


The control chart, also known as the ‘Shewhart chart’ or ‘process-behavior chart’ is a statistical tool intended to help assess the nature of variation in a process and to facilitate forecasting and management.  Variations occur in a process due to many sources such as equipment, materials, environment, and operator.


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.


Scatter diagram is the simplest way to determine the cause-and-effect relationship between two variables. Examples of cause-and-effect relationships are:

  • Cutting speed and tool life
  • Temperature and lipstick hardness
  • Training and errors
  • Breakdowns and equipment age
  • Accidents and years with the organization.
  • Dr. Juran and Dr. Kaoru Ishikawa popularize the use of this chart in the field of Quality Assurance.




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