(4) Productivity Tools.asd

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TOOLS AND FRAMEWORK FOR QUALITY DESIGN AND CONTROL

TQM

THURSDAY (4PM TO 7:00PM)

1ST

SEMESTER SY2012-2013

A REVIEW OF BASIC CONCEPTS

WHAT IS TOTAL QUALITY MANAGEMENT

Total quality management is a management system for a customer focused organization that involves all employees in continual

improvement of all aspects of the organization. TQM uses strategy, data, and effective communication to integrate the quality

principles into the culture and activities of the organization.

PRINCIPLES OF TQM

1. Be Customer focused: Whatever you do for quality improvement, remember that ONLY customers determine the level of quality.

Whatever you do to foster quality improvement, training employees, integrating quality into processes management, ONLY

customers determine whether your efforts were worthwhile.

2. Insure Total Employee Involvement: You must remove fear from work place, then empower employee... you provide the properenvironment.

3. Process Centered: Fundamental part of TQM is to focus on process thinking.

4. Integrated system: All employees must know the business mission and vision. An integrated business system may be modeled

by MBNQA or ISO 9000

5. Strategic and systematic approach: Strategic plan must integrate quality as core component.

6. Continual Improvement: Using analytical, quality tools, and creative thinking to become more efficient and effective.

7. Fact Based Decision Making:Decision making must be ONLY on data, not personal or situational thinking.8. Communication:Communication strategy, method and timeliness must be well defined.
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DATA ANALYSIS TECHNIQUE

When you understand data analysis techniques, you take a big step towards making product and process improvements. How do

you know when you implement a change, that the change was effective?

The Problem

Have you ever encountered a manager who said I just made a change to the way we do things here. Now things are better.? Whenyou review the final outcome, you find things are not improved. In fact the improvements may be counter-productive. Why did the

manager make these statements?

1. The managers ego may prevent him / her from realizing the change was not effective.

2. There may not be any measurements in place to monitor the change.

3. The measurement may be on the wrong item. In this case, your point of view is different than your managers point of view.

4. The data is collected correctly but your manager is not reviewing the data. The data is not being analyzed.

5. The manager does not understand the definition of improvement. When you say improvement what does that mean? How does

data analysis link to improvement?Data Analysis is key to making business decisions about your process or product. To improve the process or product you have to

measure it. Once you have the measurements, you need to quickly interpret the data.

TOTAL QUALITY MANAGEMENT TOOLS

The Seven Classic Quality Tools

1. Pareto Chart

2. Histogram

3. Fish Bone

4. Flow Chart

5. Check Points

6. Scatter Diagram

7. Control Charts

Basic Management & Planning Tools

1. Activity Network Diagram

2. Affinity Diagram

3. Interrelationship Diagram

4. Matrix Diagram

5. Priorities Matrix6. Process Decision

7. Tree Diagram
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THE SEVEN CLASSIC QUALITY TOOLS

A. Pareto Chart

Description

A Pareto chart, also called a Pareto distribution diagram, is a vertical bar graph in which values are plotted in decreasing order of

relative frequency from left to right. Pareto charts are extremely useful for analyzing what problems need attention first because the

taller bars on the chart, which represent frequency, clearly illustrate which variables have the greatest cumulative effect on a given

system.

The Pareto chart gets its name from Vilfredo Pareto, an Italian Economist. In 1906, Pareto noted that 20% of the population in Italy

owned 80% of the property. He proposed that this ratio could be found many places in the physical world and theorized it might be

a natural law, where 80% of the outcomes are determined by 20% of the inputs.

In the 1940s, Paretos theory was advanced by Dr. Joseph Juran, an American electrical engineer who is widely credited with being

the father ofquality control. It was Dr. Juran who decided to call the 80/20 ratio the "The Pareto Principle." Applying the Pareto

Principle to business metrics helps to separate the "vital few" (the 20% that has the most impact) from the "useful many" (the other

80%). The chart illustrates the Pareto Principle by mapping frequency, with the assumption that the more frequently something

happens, the more impact it has on outcome.

A Pareto chart is a bar graph. The lengths of the bars represent frequency or cost (time or money), and are arranged with longestbars on the left and the shortest to the right. In this way the chart visually depicts which situations are more significant. T

he independent variables on the chart are shown on the horizontal axis and the dependent variables are portrayed as the heights of

bars. A point-to-point graph, which shows the cumulative relative frequency, may be superimposed on the bar graph. Because the

values of the statistical variables are placed in order of relative frequency, the graph clearly reveals which factors have the greatest

impact and where attention is likely to yield the greatest benefit.

When to Use a Pareto Chart

1. When analyzing data about the frequency of problems or causes in a process.

2. When there are many problems or causes and you want to focus on the most significant.

3. When analyzing broad causes by looking at their specific components.

4. When communicating with others about your data.

Sample Pareto Chart Depiction
http://whatis.techtarget.com/definition/bar-graphhttp://www.qualitydigest.com/feb99/html/body_juran.htmlhttp://www.geocities.com/dfloyd2292/juran.htmlhttp://whatis.techtarget.com/definition/independent-variablehttp://whatis.techtarget.com/definition/dependent-variablehttp://whatis.techtarget.com/definition/dependent-variablehttp://whatis.techtarget.com/definition/independent-variablehttp://www.geocities.com/dfloyd2292/juran.htmlhttp://www.qualitydigest.com/feb99/html/body_juran.htmlhttp://whatis.techtarget.com/definition/bar-graph


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How To Construct A Pareto Chart

A pareto chart can be constructed by segmenting the range of the data into groups (also called segments, bins or categories). For

example, if your business is investigating the delay associated with processing credit card applications, you could group the data into

the following categories:

1. No signature

2. Residential address not valid

3. Non-legible handwriting

4. Already a customer5. Other

The left-side vertical axis of the pareto chart is labeled Frequency (the number of counts for each category), the right-side vertical

axis of the pareto chart is the cumulative percentage, and the horizontal axis of the pareto chart is labeled with the group names of

your response variables.

You then determine the number of data points that reside within each group and construct the pareto chart, but unlike the bar

chart, the pareto chart is ordered in descending frequency magnitude. The groups are defined by the user.

What Questions The Pareto Chart Answers

1. What are the largest issues facing our team or business?

2. What 20% of sources are causing 80% of the problems (80/20 Rule)?

3. Where should we focus our efforts to achieve the greatest improvements?

B. HISTOGRAM

Description

A Histogram is a graphical display of data using bars of different heights. It is similar to a bar chart but a histogram groups numbers

into ranges and you decide what ranges to use.

Example: Dress Shop Survey

You asked customers who bought one of the "Aurora" range of skirts how old they were. The ages were from 5 to 25 years old.

You decide to put the results into groups of 5:

1. The 1 to 5 years old range,

2. The 6 to 10 years old range,

3. etc.

When someone says I am 17, you add 1 to the 16-20 range. And here is the result:

You could see for example that there were

30 customers between 6 and 10 years old.
http://www.isixsigma.com/index.php?option=com_k2&view=item&id=1443:pareto-principle-80/20-rule&Itemid=209http://www.isixsigma.com/index.php?option=com_k2&view=item&id=1443:pareto-principle-80/20-rule&Itemid=209http://www.isixsigma.com/index.php?option=com_k2&view=item&id=1443:pareto-principle-80/20-rule&Itemid=209http://www.isixsigma.com/index.php?option=com_k2&view=item&id=1443:pareto-principle-80/20-rule&Itemid=209


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Histograms are a great way to show results of continuous data, such as:

weight height how much time Etc.

C. FISHBONE

Description

A Cause-and-Effect Diagram is a tool that helps identify, sort, and display possible causes of a specific problem or quality

characteristic (Viewgraph 1). It graphically illustrates the relationship between a given outcome and all the factors that influence

the outcome. This type of diagram is sometimes called an "Ishikawa diagram" because it was invented by Kaoru Ishikawa, or a

"fishbone diagram" because of the way it looks.

When should a team use a Cause-And-Effect Diagram?

Constructing a Cause-and-Effect Diagram can help your team when you need to:

1. Identify the possible root causes, the basic reasons, for a specific effect, problem, or condition.

2. Sort out and relate some of the interactions among the factors affecting a particular process or effect.

3. Analyze existing problems so that corrective action can be taken.

Benefits of Using a Cause-and-Effect Diagram

Helps determine root causes

Encourages group participation Uses an orderly, easy-to-read format

Indicates possible causes of variation

Increases process knowledge

Identifies areas for collecting data

On the next page is a basic lay-out of cause-and-effect diagram.


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Procedure:

1- Agree on the problem (effect). Write it at the center right (Fish Head) of the flipchart or whiteboard. Draw a box around it anddraw a horizontal arrow running to it.

2- Brainstorm the possible major categories of causes of the problem (5M and 1E).

Methods

Machines (equipment)

Manpower (People)

Materials

Measurement

Environment

3- Write the categories of causes as branches from the main arrow.

4- Brainstorm all the possible factors for each of the major categories. Ask: Why does this happen? As each element is given, writeit as a branch from the appropriate category (5M ). Causes can be written in several places if they relate to several categories.

5- Again ask why does this happen? about each branch from step 4. Write sub-causes branching off the causes. Continue to ask

Why? and generate deeper levels of causes. Layers of branches indicate relationships.

6 After completion, have the team review the diagram. Identify elements that need to be investigated. Circle those items and assign

investigation action items to the team.


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D. PROCESS FLOW CHART

Description:

A flow chart is a graphical or symbolic representation of a process. Each step in the process is represented by a different symbol and

contains a short description of the process step. The flow chart symbols are linked together with arrows showing the process flow

direction.Use flowcharts to -

Visualize your processes Show step by step details of your current process Overview detail procedures Study processes Provide common reference talking points during a meeting Illustrate a desired flow of a new improved system. Easily identify non value added steps. Quickly train your employees


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Benefits of Flow Charting

One of the first activities of a process improvement effort is constructing a flowchart. It provides the following benefits:1- It give you and everyone a clear understanding of the process.

2- Facilitates teamwork and communication.

3- Helps to identify non-value-added operations.Common Flowchart Symbols

Different flow chart symbols have different meanings. The most common flow chart symbols are:

Terminator: An oval flow chart shape indicating the start or end of the process. Process: A rectangular flow chart shape indicating a normal process flow step. Decision: A diamond flow chart shape indication a branch in the process flow. Connector: A small, labeled, circular flow chart shape used to indicate a jump in the process flow. (Shown as the circle with

the letter A, below.)

Data: A parallelogram that indicates data input or output (I/O) for a process. Document: Used to indicate a document or report (see image in sample flow chart below).A simple flow chart showing the symbols described above can be seen below:


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Study the Current Process

Team members study flowchart samples and make decisions about the simplicity or complexity of your process. The flowcharts

show the number of steps involved in the process. Because the flowchart visually represents the process, team members can

question the validity of each step.

When studying the process ask these questions

Does the flow chart show every step? What step(s) is missing? Does each step belong? Is each step necessary? Can some steps be combine? Are there too many decisions points? Can the flow be rearrange and simplified? Can the flow be change to improve cycle time? Is there missing involvement of key people? Are there too many people involved? Is appropriate data being collected at each step? Is traceability documented at each step?

E. CHECK SHEET

Description

A check sheet is a structured, prepared form for collecting and analyzing data. This is a generic tool that can be adapted for a wide

variety of purposes. Also called defect concentration diagram.

When to Use a Check Sheet

When data can be observed and collected repeatedly by the same person or at the same location. When collecting data on the frequency or patterns of events, problems, defects, defect location, defect causes, etc. When collecting data from a production process.

Check Sheet Procedure

1. Decide what event or problem will be observed. Develop operational definitions.2. Decide when data will be collected and for how long.3. Design the form. Set it up so that data can be recorded simply by making check marks or Xs or similar symbols and so that

data do not have to be recopied for analysis.

4. Label all spaces on the form.5. Test the check sheet for a short trial period to be sure it collects the appropriate data and is easy to use.6. Each time the targeted event or problem occurs, record data on the check sheet.
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Procedure:

1. Collect pairs of data where a relationship is suspected.

2. Draw the scatter diagram with the independent variable on the horizontal axis and the dependent variable on the vertical axis. Fo

each pair of data, put a dot or a symbol where the x-axis value intersects the y-axis value. (If two dots fall together, put them side by

side, touching, so that you can see both.)

3. As in the below graph, Look at the pattern of points for an obvious relationship. If the data clearly form a line or a curve, you maystop. The variables are correlated. You may wish to useregressionor correlation analysis now. Otherwise, complete steps 4 through

7.

4. Divide points on the graph into four quadrants. Let X be the number of points on the graph.

5. Count X/2 points from top to bottom and draw a horizontal line.

6. Count X/2 points from left to right and draw a vertical line.

7. If number of points is odd, draw the line through the middle point.

8. Count the points in each quadrant. Do not count points on a line.

9. Add the diagonally opposite quadrants. Find the smaller sum and the total of points in all quadrants.

10. A = points in upper left + points in lower right

11. B = points in upper right + points in lower left

12. Q = the smaller of A and B

13. N = A + B

14. Look up the limit for N on the below trend test scatter diagram table.
http://www.bexcellence.org/Regression.htmlhttp://www.bexcellence.org/Regression.htmlhttp://www.bexcellence.org/Regression.htmlhttp://www.bexcellence.org/Regression.html


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15. If Q is less than the limit, the two variables are related.

16. If Q is greater than or equal to the limit, the pattern occurred from random chance.

G. CONTROL CHARTS

Description:

Control charts are graphs used to study how a process changes over time.

Data is plotted in time order. A control chart always has a central line for the average, an upper line for the upper control limit and a

lower line for the lower control limit. These three lines are determined from historical data. By comparing current data to these

lines, you can draw conclusions about whether the process variation is consistent (in control) or is unpredictable (out of control,


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(4) Productivity Tools.asd