Qc tool developed by an european economist

It is necessary to distinguish, that 5S is not only carrying the activities, related to tidiness and cleanliness, but it is a structured approach to ensure efficiency It's a fact that we all have to make decisions. It's not important if you are a student, parent, entrepreneur, president of a country or if the problem is big or small. What is important is that we approach problem-solving It is a method of questioning that leads to the identification of the root cause or causes of the problem.

Histogram : The most commonly used graph for showing frequency distributions, or how often each different value in a set of data occurs. Pareto chart : A bar graph that shows which factors are more significant. Scatter diagram : Graphs pairs of numerical data, one variable on each axis, to look for a relationship. Stratification : A technique that separates data gathered from a variety of sources so that patterns can be seen some lists replace stratification with flowchart or run chart.

Want more quality tools? Fishbone Diagram: Missed deadline in manufacturing of product. Pareto chart is named after Vilfredo Pareto.

The very purpose of Pareto Chart is to highlight the most important factors that is the reason for major cause of problem or failure. Pareto chart is having bars graphs and line graphs where individual factors are represented by a bar graph in descending order of their impact and the cumulative total is shown by a line graph.

Scatter diagram or scatter plot is basically a statistical tool that depicts dependent variables on Y — Axis and Independent Variable on X — axis plotted as dots on their common intersection points. Very purpose of scatter Diagram is to establish a relationship between problem overall effect and causes that are affecting.

The relationship can be linear, curvilinear, exponential, logarithmic, quadratic, polynomial etc. Stronger the correlation, stronger the relationship will hold true. The variables can be positively or negatively related defined by the slope of equation derived from the scatter diagram. The Procedure to prepare a Histogram consists of the following steps : 1.

Collect data preferably 50 or more observations of an item. Arrange all values in an ascending order. Divide the entire range of values into a convenient number of groups each representing an equal class interval. It is customary to have number of groups equal to or less than the square root of the number of observations.

However one should not be too rigid about this. The reason for this cautionary note will be obvious when we see some examples. Note the number of observations or frequency in each group.

Draw X-axis and Y-axis and decide appropriate scales for the groups on X-axis and the number of observations or the frequency on Y-axis. Draw bars representing the frequency for each of the groups. Provide a suitable title to the Histogram. Study the pattern of distribution and draw conclusion. These variations may be due to two causes ; i. Assignable causes preventable. Control charts was developed by Dr. Walter A. Shewhart during 's while he was with Bell Telephone Laboratories.

These charts separate out assignable causes. Control chart makes possible the diagnosis and correction of many production troubles and brings substantial improvements in the quality of the products and reduction of spoilage and rework. It tells us when to leave a process alone as well as when to take action to correc trouble. Data is of two types : Variable - measured and expressed quantitatively Attribute - quanlitative b. When the subgroup size is larger, s Charts are used instead of R charts where s is the standard deviation of the subgroup.

Control charts for defectives are p and np charts. P charts are used when the sample size is constant and np charts are used when the sample size is variable. In the case where the number of defects is the data available for plotting, c and u charts are used.

If the sample size is constant, c charts are used and u charts are used for variable sample sizes. A relationship may or may not exist between two variables. If a relationship exists, it may be positive or negative, it may be strong or weak and may be simple or complex. A tool to study the relationship between two variables is known as Scatter Diagram. It consists of plotting a series of points representing several observations on a graph in which one variable is on X-axis and the other variable in on Y-axis.

If more than one set of values are identical, requiring more points at the same spot, a small circle is drawn around the original dot to indicate second point with the same values. The way the points lie scattered in the quadrant gives a good indication of the relationship between the two variables. Pictoral representation enables the user or viewer to quickly grasp the meaning of the data.