MS-96 mba assignment july dec 2010 Question 4

Q4.    List out the conventional seven quality control tools. Explain any two in brief.

Ans.   The Seven Conventional Tools of Quality is a designation given to a fixed set of graphical techniques identified as being most helpful in troubleshooting issues related to quality. They are called conventional/ basic because they are suitable for people with little formal training in statistics and because they can be used to solve the vast majority of quality-related issues.

          Statistical process control involves the use of various methods to measure and analyze a process. The overall objectives of SPC are to:

1. Improve the quality of the process output,

2. Reduce process variability and achieve process stability, and

3. Solve processing problem.

These seven tools are sometimes referred to as the “magnificent seven”. The tools are:

1.    The Control Charts

2.    The Histograms

3.    The Pareto Charts

4.    The Check Sheets

5.    The Scatter Diagrams

6.    The Defect Concentration Diagrams

7.    The Cause and Effect Diagrams

          The designation arose in postwar Japan, inspired by the seven famous weapons of Benkei. At that time, companies that had set about training their workforces in statistical quality control found that the complexity of the subject intimidated the vast majority of their workers and scaled back training to focus primarily on simpler methods which suffice for most quality-related issues anyway.

          CONTROL CHART

          Control chart is a graphical technique in which statistics computed from measured values of a certain process characteristics are plotted over time to determine if the process remains in statistical control. Control charts are widely used in SPC.

          HISTOGRAM

          The histogram is a basic graphical tool in statistics. Histogram is a useful statistical tool for an analyst as it helps him to quickly visualize the features of a complete set of data. It is a graphical display of the frequency distribution of the numerical data.

PARETO CHARTS

          A Pareto Chart provides a graphical display of the tendency for a small proportion of a given population to be more valuable than the much larger majority. This tendency is sometimes referred to as Pareto’s Law, which can be succinctly stated: “the vital few and the trivial many.” The law is often identified as the 80% - 20% rule.

CHECK SHEETS

          The check sheet is a data gathering tool generally used in the preliminary stages of study of a quality problem. Types of check sheets include process distribution check sheet, defective item check sheet, defective location check sheet, defective factor check sheet, etc.

DEFECT CONCENTRATION DIAGRAMS

          The defect concentration diagram is a drawing of the product with all relevant views displayed, onto which have been sketched the various defect types at the locations where they each occurred. By analyzing the defect types and corresponding locations, the underlying causes of the defects can possibly be identified.

SCATTER DIAGRAM

A scatter diagram is simply an x-y plot of the data taken of the two variables in question.

CAUSE AND EFFECT DIAGRAMS

          The cause and effect diagram is a graphical tabular chart used to list and analyze the potential causes of a given problem. The diagram consists of a central stem leading to the effect, with multiple branches coming off the stem listing the various groups of possible causes of the problem.

Let us now describe two of these magnificent tools:

1.    CONTROL CHART

The underlying principle of control charts is that the variations in any process divide into two types:

1. Random variations, which are the only variations present if the process is in statistical control; and

2. Assignable variations, which indicate a departure from statistical control.

          The purpose of control chart is to identify when the process has gone out of statistical control, thus signaling the need for some corrective action to be taken. The philosophy “if it ain’t broke, don’t fix it” is applicable in control charts.

          There are two basic types of control charts:

1. Control charts for variables and

2. Control chart for attributes.

Control chart for variables require a measurement of the quality characteristic of interest. Control charts for attributes simply require a determination of whether a part is defective or how many defects there are in the sample.

          Control charts for variables

          A process that is out of statistical control manifests this condition in the form of significant changes in 1. Process mean and / or 2. Process variability. Corresponding to these possibilities, there are two principal types of control charts for variables:

          1. ­ chart. The  chart is used to plot the average measured value of a certain quality characteristic for each of a series of samples taken from the production process. It indicates how the process mean changes over time.

          2. R chart. The R chart plots the range of each sample, thus monitoring the variability of the process and indicating whether it changes over time.

          Control charts for attributes

          Control charts for attributes monitor the number of defects present in the sample or the fraction defect rate as the plotted statistic. Examples of these kinds of attributes include: number of defects per automobile, fraction of nonconforming parts in a sample, existence or absence of flash in a plastic molding, and number of flaws in a roll of sheet steel.

          The two principal types of control charts for attributes are:

1. The p chart, which plots the fraction defect rate in successive samples, and

2. The c chart, which plots the number of defects, flaws, or other nonconformities per sample.

          When control charts are used to monitor production quality, random samples are drawn from the process of the same size used to construct the charts. A set of indicators that shows a process is likely to be out of statistical control and that corrective action should be taken is listed below:

1.    One point that lies outside upper critical point or lower critical point.

2.    Two out of three consecutive points that lie beyond ± 2σ on one side of centre line of the control chart

3.    Four out of five consecutive points that lie beyond ± 1σ on one side of centre line of the control chart

4.    Eight consecutive points that lie on one side of centre line of the control chart

5.    Six consecutive points in which each point is always higher than its predecessor or Six consecutive points in which each point is always lower than its predecessor.

          Control charts serve as feedback loop in SPC. If the control chart indicates that the process is in statistical control, then no action is taken. However, if the process is identified as being out of statistical control, then the cause of the problem must be identified and corrective action must be taken.

2.    HISTOGRAM

          After the control chart, it is probably the most important member of the SPC tool kit. A histogram is a statistical graph consisting of bars representing different values or ranges of values, in which the length of each bar is proportional to the frequency or the relative frequency of the value or the range.

          Histogram is a useful statistical tool for an analyst as it helps him to quickly visualize the features of a complete set of data:

1. The shape of the distribution

2. Any central tendency exhibited by the distribution

3. Approximations of the mean and mode of the distribution, and

4. The amount of scatter or spread in the data.