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I.            The Plan–Do–Study–Act Cycle:
The plan–do–study–act (PDSA) cycle describes the activities a company needs to perform in order to incorporate continuous improvement in its operation.

PlanThe first step in the PDSA cycle is to plan. Managers must evaluate the current process and make plans based on any problems they find. They need to document all current procedures, collect data, and identify problems. This information should then be studied and used to develop a plan for improvement as well as specific measures to evaluate performance.

DoThe next step in the cycle is implementing the plan (do). During the implementation process managers should document all changes made and collect data for evaluation.

Study The third step is to study the data collected in the previous phase. The data are evaluated to see whether the plan is achieving the goals established in the plan phase.

ActThe last phase of the cycle is to act on the basis of the results of the first three phases. The best way to accomplish this is to communicate the results to other members in the company and then implement the new procedure if it has been successful. Note that this is a cycle; the next step is to plan again. After we have acted, we need to continue evaluating the process, planning, and repeating the cycle again.1,5

II.            Benchmarking
SimplyBenchmarking Studying the businesspractices of other companies for purposes of comparison.

Another way companies implement continuous improvement is by studying business practices of companies considered “best in class.” This is called benchmarking. The ability to learn and study how others do things is an important part of continuous improvement. The benchmark company does not have to be in the same business, as long as it excels at something that the company doing the study wishes to emulate.

(d). Quality tools:
You can see that TQM places a great deal of responsibility on all workers. If employees are to identify and correct quality problems, they need proper training. They need to understand how to assess quality by using a variety of quality control tools, how to interpret findings, and how to correct problems. In this section we look at seven different quality tools. These are often called the seven tools of quality control. 1

i.            Cause-and-Effect Diagrams
Cause-and-effect diagrams are charts that identifypotential causes for particular quality problems. They are often called fishbone diagrams because they look like the bones of a fish.

The “head” of the fish is the quality problem, such as damaged zippers on a garment or broken valves on a tire. The diagram is drawn so that the “spine” of the fish connects the “head” to the possible cause of the problem. These causes could be related to the machines, workers, measure ment, suppliers, materials, and many other aspects of the production process.

Cause-and-effect diagrams are problem-solving tools commonly used by quality control teams. Specific causes of problems can be explored through brainstorming. The development of a cause-and-effect diagram requires the team to think through all the possible causes of poor quality.

ii.            Flowcharts
A flowchart is a schematic diagram of the sequence of steps involved in an operation or process. It provides a visual tool that is easy to use and understand. By seeing the steps involved in an operation or process, everyone develops a clear picture of how the operation works and where problems could arise.

iii.            Checklists
A checklistis a list of common defects and the number of observed occurrences of these defects. It is a simple yet effective fact-finding tool that allows the worker to collect specific information regarding the defects observed.

if a defect is being observed frequently, a checklist can be developed that measures the number of occurrences per shift, per machine, or per operator. In this fashion we can isolate the location of the particular defect and then focus on correcting the problem.1

iv.            Control Charts
Control charts are a very important quality control tool. These charts are used to evaluate whether a process is operating within expectations relative to some measured value such as weight, width, or volume. For example, we could measure the weight of a sack of flour, the width of a tire, or the volume of a bottle of soft drink. When the production process is operating within expectations, we say that it is “in control.”

To evaluate whether or not a process is in control, we regularly measure the variable of interest and plot it on a control chart. The chart has a line down the center representing the average value of the variable we are measuring. Above and below the center line are two lines, called the upper control limit (UCL) and the lower control limit (LCL). As long as the observed values fall within the upper and lower control limits, the process is in control and there is no problem with quality. When a measured observation falls outside of these limits, there is a problem.

v.            Scatter Diagrams
Scatter diagrams
are graphs that show how two variables are related to one another. They are particularly useful in detecting the amount of correlation, or the degree of linear relationship, between two variables.

The greater the degree of correlation, the more linear are the observations in the scatter diagram. On the other hand, the more scattered the observations in the diagram, the less correlation exists between the variables.1

vi.            Pareto Analysis
Pareto analysis is a technique used to identify quality problems based on their degree of importance. The logic behind Pareto analysis is that only a few quality problems are important, whereas many others are not critical.

One way to use Pareto analysis is to develop a chart that ranks the causes of poor quality in decreasing order based on the percentage of defects each has caused. For example, a tally can be made of the number of defects that result from different causes, such as operator error, defective parts, or inaccurate machine calibrations,1

vii.            Histograms:

A histogram is a chart that shows the frequency distribution of observed values of a variable.We can see from the plot what type of distribution a particular variable displays. such as whether it has a normal distribution and whether the distribution is symmetrical.1

1 .” Toatl Quality Management”
2 . “Concept of Total Quality Management” management/2001/z.zhang/c2.pdf. .
3.  “TQM Consultant - Training Article” training TQM%20 training.pdf. .
5. “Total Quality Management: A Continuous Improvement Process” foundation.phccweb. org/library/article/TQM.pdf. .
6.  “Introduction: TQM Basics and Beyond” /    001552.pdf.
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