Friday, May 23, 2014

Variation and its categories

One of the axioms, or sayings, of production is that no two objects are ever made exactly alike. In fact , the variation concept is a law of nature because no two natural items in any category are the same. The variation may be quite large and easily noticeable, such as the height of human beings, or the variation may be very small, such as the weights of fiber-tipped pens or the shapes of snowflakes. When variations are very small, it may appear that items are identical; however, precision instruments will show differences. If two items appear to have the same measurement, it is due to the limits of measuring instruments. As measuring instruments have become more refined, variation has continued to exist; only the increment of variation has changed. The ability to measure variation is necessary before it can be controlled. 
            There are three types of variations in piece part production:
  1. Within - piece, variation is illustrated by the surface roughness of a piece, wherein one portion of the surface is rougher than another portion.
  2. Piece to piece variation occurs among pieces produced at the same time. Thus, the light intensity of four consecutive light bulbs produced from a machine will be different.
  3. Time to time variation is illustrated by the difference in product produced at different times of the day. Thus, product produced in the early morning is different from that produced later in the day, or as a cutting tool wears, the cutting characteristics change.
Categories of variation  for other types of processes such as a continuous and batch are not exactly the same; however, the concept is similar.
  1. Variation is present in every process due to a combination of the equipment, materials, environment, and operator. The first source of variation is the equipment. This source includes tool wear, machine vibration, work holding - device positioning, and hydraulic and electrical fluctuations. When all these variations are put together, there is certain capability or precision within which the equipment operates. Even supposedly identical machines will have different capabilities. This fact becomes a very important consideration when scheduling the manufacture of critical parts.
  2. The second source of variations is the material. Because variation occurs in the finished product, it must also occur in the raw material (which was someone else's finished product). Such quality characteristics as tensile strength, ductility, thickness, porosity, and moisture content can be expected to contribute to the overall variation in the final product.
  3. A third source of variation is the environment. Temperature, light, radiation, particle size, pressure, and humidity all can contribute to variation in the product. In order to control environmental variations, products are sometimes manufactured in white rooms. Experiments are conducted in outer space to learn more about the effect of the environment on product variation.
  4. A fourth source is the operator. This source of variation includes the method by which the operator performs the operation. The operator's physical and emotional well-being also contribute to the variation. A cut finger, a twisted ankle, a personal problem, or a headache can make an operator's quality performance vary. An operator's lack of understanding of equipment and material variations due to lack of training may lead to frequent machine adjustments, thereby compounding the variability. As our equipment has become more automated, the operator's effect on variation has lessened.
The preceding four sources account for the true variation. There is also a reported variation, which is due to the inspection activity. Faulty inspection equipment, the incorrect application of quality standard, or too heavy a pressure on a micrometer can be the cause of the incorrect reporting of variation. In general, variation due to inspection should be one-tenth of the four other sources of variations. Note that three of these sources are present in the inspection activity - an inspector or appraiser, inspection equipment, and the environment. Below picture shows hierarchy of varitation categories.

Thursday, May 22, 2014

Statistical process control

To use of statistics in quality control - is the concept of variance.If we would like to summarize the entire field of statistical quality control (also called statistical process control or SPC) in one word, that word would be variance. Shewart, Deming, and others wanted to bring the statistical concept of variance down to the shop floor. If supervisors and production line workers could understand the existence of variance in the production process, then this awareness by itself could be used to help minimize the variance. Furthermore, the variation in the production process comes due to two types of cause : variation due to natural causes and variation due to assignable/special cause. Examples of assignable causes are fatigue of workers and breakdown of components. Variation due to assignable causes is especially undesirable because it is due to something being wrong with the production process, and may result in low quality of the production items. 

"A process is considered in statistical control when it has no assignable causes, only natural variation."

Actually , any kind of variance is undesirable in a production process. Even the natural variance of a process due to purely random causes rather than to assignable causes can be matter of loss to the production. The control chart, however,will detect only  assignable causes. but the use of control charts can go a long way toward improving quality, shown in the below diagram

Monday, May 19, 2014

7 QC Tools : Seven Basic tools of quality

E-Book 7 QC Tools with excel images and commands of construction of tools in excel.

7 QC Tools are the 7 basic tools of quality and very necessary for any quality professional. These 7 tools give an edge to all category of quality professional; Junior, Middle and Senior level. These seven tools were developed by Prof. Kaoru Ishikawa. He was called the father of QCC's(Quality Control Circles).

He developed seven fundamental tools which use for process design, data collection, data presentation, data analysis, finding most important most important cause of the problem, calculation of degree of relationship between cause and effect, and to implement control plan


These 7 Basic tools are named as

  1. Process flow chart
  2. Check Sheet
  3. Histogram
  4. Pareto diagram also called 80-20 rule
  5. Cause and effect diagram also called Fishbone diagram or Ishikawa diagram
  6. Scatter Diagram
  7. Control Charts (Mean Chart and Range Chart)
Detailed explanation of all seven tools given below 

Tool No. 1: Process Flow Diagram

Process flow diagram is the pictorial presentation of actual process using symbols. These symbols communicates the activities, stages and decisions in the process. The whole process can be understand by means of symbols. The process flowchart helps to find the trouble spots in the process if occurs any. Process audit, process engineering can also be done with help of process flow chart or diagram.




Tool No. 2: Check Sheet

Check sheet is a simple sheet of paper on which data is collected by adding tally marks against predetermined categories.









Tool No. 3: Histogram

Histogram is the frequency marks of the data represented by adjacent rectangular bars on X-Axis, where as the height is given on the Y-Axis. Histogram tells about the extent of spread of data. if the shape of histogram is symmetrical about the center line i.e.bell shaped then there is no skewness in the data. But if the shape of histogram is not symmetrical then there is skewness in the data and it is presented by asymmetrical shape of histogram.





Tools No. 4: Pareto Diagram

Pareto diagram is the combination of bars and line graph. Pareto analysis the pictorial presentation of causes responsible for a problem in a systematic order of their significance. The bars on the chart are the frequencies of the causes in descending order while the line graph is cumulative percentage of the causes in ascending order. The Pareto chart is very helpful to find which causes should be address first because  it depicts the frequencies of 'vital few' or important causes of a problem , compared with the 'trivial many'. When analyze the chart we able to conclude that only two or three 'vital few' causes has cumulative percentage of 70 or 80. Hence if we kill these two or three cause then it means we able to reduce the effect of the problem by 70 to 80%.
        Hence Pareto diagram is the guiding picture of important causes of a problem which suggests that which causes should be address first rather to work on different causes at the same time and find no result.

Tool No. 5: Cause and Effect diagram


Cause and Effect diagram is a pictorial presentation of the causes for a certain effect by brainstorming method in which the concerned person with problem present their ideas openly. It is a diagram which looks like a fish without flesh. A central arrow heading towards the right. The other arrows moving and look like attached with the central arrow. The effect is put on extreme right or head on the central arrow. The main causes are shown by the branch arrows. The main causes are categories as 5-M+1E. i.e. Man, Method, Machine, Material, and Money + Environment.  Each individual main cause branch may further has sub-causes and further shown by  branch arrows attached with main causes. The diagram also called the Fishbone diagram because of its shape.It is also called Ishikawa diagram , owing to its inventor, Kaoru Ishikawa.

Tool No. 6: Scatter Diagram

Scatter diagram is the possible relationship between two variables; Independent variable and dependent variable. For example fuel for an automobile is dependent on the distance covered by it. More fuel is required to cover more distance. The distance is independent quantity and the fuel to cover the distance is dependent quantity. It may possible to control the dependent variable to adjust the independent variable. The graph between the two paired values; independent and dependent is shown by the scatter diagram. The analysis of this graph can help to confirm or reject the hypothesis about the possible correlation between two variables. The degree of relationship between two variables is given by coefficient of correlation. According to shape of the scatter diagram the correlation between two variables is categories as 
  1. Perfect Positive Correlation
  2. Perfect Negative Correlation
  3. High degree of Positive Correlation
  4. High degree of Negative Correlation
  5. Zero/No Correlation

Tool No. 7: Control Charts


Control Charts are the pictorial presentations of the data variations over a specific period of time. With the help of control charts decisions are made about the process. Control charts are prepared for the data collected over a time between control limits called Upper control limits (UCL) and Lower control limits (LCL). The control limits can be calculated as; 

Mean chart

Upper control limit= mean of means+3Std. dev,  
Lower Control limit= mean of means -3Std. dev

Range Chart

Upper control limit= R+3Std. Dev)

lower control limit is not required for range chart.

If the data points cross the control limits this means there is a urgent requirement of preventive action.

Continuous use of control chart improve the process with in the control limits

These 7 Basic tools of Quality are very much important to learn for data collection, data analysis, data presentation, finding root causes, making quantitative relation between cause and effect and to control the process. The tools are necessary to learn by managers, engineers of quality, production, sales and marketing, design and development, HR and other department of Manufacturing and service organizations.

APQP Training