Quality Control Tools


Production environments that utilize modern quality control methods are dependant upon statistical literacy. The tools used therein are called the seven quality control tools. These include:

            


Checksheet       


Pareto Chart 
	    

Flow Chart       

Cause and Effect Diagram 
	    

Histogram        

Scatter Diagram 
            

Control Chart 

Checksheet

The function of a checksheet is to present information in an efficient, graphical format. This may be accomplished with a simple listing of items. However, the utility of the checksheet may be significantly enhanced, in some instances, by incorporating a depiction of the system under analysis into the form.

| QC Tools | Example |


Pareto Chart

Pareto charts are extremely useful because they can be used to identify those factors that have the greatest cumulative effect on the system, and thus screen out the less significant factors in an analysis. Ideally, this allows the user to focus attention on a few important factors in a process.

They are created by plotting the cumulative frequencies of the relative frequency data (event count data), in decending order. When this is done, the most essential factors for the analysis are graphically apparent, and in an orderly format.

| QC Tools | Example |


Flowchart

Flowcharts are pictorial representations of a process. By breaking the process down into its constituent steps, flowcharts can be useful in identifying where errors are likely to be found in the system.

| QC Tools | Example |


Cause and Effect Diagram

This diagram, also called an Ishikawa diagram (or fish bone diagram), is used to associate multiple possible causes with a single effect. Thus, given a particular effect, the diagram is constructed to identify and organize possible causes for it.

The primary branch represents the effect (the quality characteristic that is intended to be improved and controlled) and is typically labelled on the right side of the diagram. Each major branch of the diagram corresponds to a major cause (or class of causes) that directly relates to the effect. Minor branches correspond to more detailed causal factors. This type of diagram is useful in any analysis, as it illustrates the relationship between cause and effect in a rational manner.

| QC Tools Example |


Histogram

Histograms provide a simple, graphical view of accumulated data, including its dispersion and central tendancy. In addition to the ease with which they can be constructed, histograms provide the easiest way to evaluate the distribution of data.

| QC Tools | Example |


Scatter Diagram

Scatter diagrams are graphical tools that attempt to depict the influence that one variable has on another. A common diagram of this type usually displays points representing the observed value of one variable corresponding to the value of another variable.

| QC Tools | Example |


Control Chart

The control chart is the fundamental tool of statistical process control, as it indicates the range of variability that is built into a system (known as common cause variation). Thus, it helps determine whether or not a process is operating consistently or if a special cause has occurred to change the process mean or variance.

The bounds of the control chart are marked by upper and lower control limits that are calculated by applying statistical formulas to data from the process. Data points that fall outside these bounds represent variations due to special causes, which can typically be found and eliminated. On the other hand, improvements in common cause variation require fundamental changes in the process.

| QC Tools | Example |


Summary

The tools listed above are ideally utilized in a particular methodology, which typically involves either reducing the process variability or identifying specific problems in the process. However, other methodologies may need to be developed to allow for sufficient customization to a certain specific process. In any case, the tools should be utilized to ensure that all attempts at process improvement include:

Furthermore, it is important to note that the mere use of the quality control tools does not necessarily constitute a quality program. Thus, to achieve lasting improvements in quality, it is essential to establish a system that will continuously promote quality in all aspects of its operation.


Examples
Pareto Chart Example---- From the following Pareto Chart
it is possible to see that the initial focus in quality improvement should be on reducing edge flaws. Although the print quality is also of some concern, such defects are substantially less numerous than the edge flaws. Remember the "80/20" rule....
80% of your results will be obtained with 20% of your effort.

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Flow Chart Example


By breaking down the process into a series of steps, the flowchart simplifies the analysis and gives some indication as to what event may be adversely impacting the process.

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Checksheet example

A defect location checksheet is a very simple example of how to incorporate graphical information into data collection.

Additional data collection checksheet examples demonstrate the utility of this tool. The data collected will be used in subsequent examples to demonstrate how the individual tools are often interconnected.


Having decided on which problem to focus on, aCause and Effect diagram of the related process is created to help the user see the entire process and all of its components.

In many instances, attempts to find key problem areas in a process can be a hit or miss proposition. In this instance, it was decided to collect data on the curetimes of the material.

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Flowchart example
By breaking down the process into a series of steps, the flowchart simplifies the analysis and gives some indication as to what event may be adversely impacting the process.

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Scatterplot example

Applying curing time test data to create a scatterplot, it is possible to see that there are very few defects in the range of approximately 29.5 to 37.0 minutes. Thus, it is possible to conclude that by establishing a standard curetime within this range, some degree of quality improvement is likely.

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Histograms are effective Q.C. tools which are used in the analysis of data. They are used as a check on specific process parameters to determine where the greatest amount of variation occurs in the process, or to determine if process specifications are exceeded. This statistical method does not prove that a process is in a state of control. Nonetheless, histograms alone have been used to solve many problems in quality control.


Histogram - a vertical bar chart of a frequency distribution of data
The histogram evolved to meet the need for evaluating data that occurs at a certain frequency. This is possible because the histogram allows for a concise portrayal of information in a bar graph format.

The histogram is a powerful engineering tool when routinely and intelligently used. The histogram clearly portrays information on location, spread, and shape that enables the user to perceive subtleties regarding the functioning of the physical process that is generating the data. It can also help suggest both the nature of, and possible improvements for, the physical mechanisms at work in the process.


Creating a Histogram
Now you have a histogram!!


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Control chart example Applying statistical formulas to the data from the curetime tests of base material, it was possible to construct X-bar and R charts to assess its consistency. As a result, we can see that the process is in a state of statistical control.

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