1. CHECK SHEETS
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What It Is?
Forms specially prepared to enable data to be collected simply by making check marks. Check sheets are very useful in data collection activity.
In early stages of SPC implementation, forms are designed to collect either historical or current operating data about the processes under investigation. Quality Records, forms recording sheets and logbooks are the different forms of the check sheets.

2. CHECK SHEETS Procedure 1 Identify the purpose of selecting data.
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Procedure
1 Identify the purpose of selecting data.
2 Select the data required for the purpose.
3 Determine how data will be further analyzed or processed.
4 Develop a form suitable to the requirements.
5 Include a header in the form to include basic information about the
product lot, inspector, dates, operation etc.
6 Use the form initially for trial run.
7 Review and revise the form, if necessary.

3. Travel Expense Report Errors
RECORDING DATA
Check sheet Example
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Travel Expense Report Errors
CAUSE
COUNT
TOTALS
Missing Receipts
/// 3
Calculation Error
//// / 6
Wrong Information
//// //// //// //// // 22
No Signature
//// //// / 11
Late Report
//// // 7
Other / 1
TOTAL ERRORS 50

4. HISTOGRAM
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What It Is?
To display the variation and capability of a process.
It is vertical bar chart of frequency distribution. It depicts two things, center and amount of variation in the sample of data.
When the frequency distribution is of continuous nature, it is advisable to construct histogram by using a frequency table. It is multiple bar diagram ( bar linked with each other)
The histogram presents a visual display if the data in which one may see three properties.
A) Shape of Histogram
B) Location, or average or centering of Histogram
C) Scatter or spread or width of Histogram

5. HISTOGRAM Procedure Collect the data values.
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Procedure
Collect the data values.
Determine the range (R) of the data by subtracting the smallest data value from the largest.
Determine the number of intervals (bars) in your histogram (often between 6 and 12 and divide the range (R) by the number of intervals.
Mark the horizontal axis with the scale of the data values.
Mark the vertical axis with the frequency scale (number or percent of observations).
Draw the height of each interval equal to the number of data values that fall within that interval.
Vertically draw the specification limits and mark them with Su (Upper limit) and SL (Lower limit).

6.  Formula HISTOGRAM 1. X = X1 + X2 + X3 + ….. Xn N 2. S =  (X – X n)2
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Formula
1. X = X1 + X2 + X3 + ….. Xn N
2. S =  (X – X n)2
n - 1
Central Process one value is zero
3. Cp = Su - SL 6s
Process range
4. Cpk = Su - X or X - SL
3s s
Whichever is lowest out of the two. 

7. PARETO CHART
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What It Is?
The Pareto chart is simply a frequency distribution (or histogram) of attribute data arranged by category.
The cumulative curve is called the Pareto Chart or Pareto Curve.
The Pareto analysis consists of identifying quality costs by category, or by product or by type of defect or nonconformity. The name Pareto chart is derived from Italian economist Vilfredo Pareto ( ), who theorized that in certain economies the majority of the wealth was held by a disproportionately small segment of the population. Quality engineers have observed that defects usually follow a similar Pareto distribution.
To graphically represent quality problems or their associated cost in order of their significance.
It is a method of identifying the vital few.

8. PARETO CHARTS Procedure Select the item to be analyzed.
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Procedure
Select the item to be analyzed.
Select the unit of measurement for analysis, such as number of occurrences
or cost.
Select the time period for the data to be analyzed.
Arrange the data in descending ( ) order.
Construct two vertical axes, one at each end of the horizontal axes.
The left scale should be calibrated in the unit of measurement, and its height
must be equal to the sum of the magnitude of all items.
The right scale must have the same height and is calibrated from

9. PARETO CHARTS Procedure
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Procedure
Plot bar graphs representing the magnitude of each item in descending order.
Construct a cumulative frequency line by summing the magnitudes of each
item from left to right.
Analyze the chart and make comparative analysis of the same quality
characteristic with other time periods and identify items for improvement.

10. SCATTER DIAGRAM What It Is? Typical Applications
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What It Is?
It shows the relationship between paired data and can provide more useful information about the production process.
It is useful tool for identifying a potential relationship between two variables. Data are collected in pairs: the two variables. The shape of scatter diagram often indicates what type of relationship may be occurring between two variables. Keep in mind, the correlation does not necessarily imply causality.
Typical Applications
It is used to study and evaluate the effect of one characteristic on the other like moisture content and elongation of fiber, Bulk and board stiffness, Thickness and board stiffness, Bulk and board density.

11. SCATTER DIAGRAM Procedure
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Procedure
Collect the pair data of two associated characteristics believed to be related.
Label x and y axes with their measurement units.
Find max and min values of (x, y)
Decide scale on both horizontal and vertical axes, approximately equal. (3 to 10 graduations) with the scale of the data values. The variable that is being investigated on the x-axis and the “ effect” variable on the y-axis.
Plot the data on paper. Encircle the concentric ( repeat ) points.
Examine the shape of the cloud of points to discover the types of correlation of strengths from the slopes. .
Enter necessary items.

12. CAUSE AND EFFECT DIAGRAM
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What It Is?
Once a defect, error or problem has been isolated for further study, Fishbone diagram as a formal tool must be used in un-layering potential causes.
The construction of Cause & Effect Diagram as a team experiences teams to get people involved in attacking a problem rather than in affixing blame.
If is used to illustrate the various sources of non-conformities in products & their inter relationships.
It is the diagram which shows the relationship between a quality characteristic and factors. (JIS). We can call it a CE-Diagram, or Tree Diagram or River Diagram or Ishikawa Diagram or Fishbone Diagram or Cause and Effect Diagram.
A graphical tool to find out the reasons for problems and to carry out their root cause analysis.

13. CAUSE & EFFECT ANALYSIS
Characteristics
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A graphical representation of cause and effect relationships.
“Fishbone Diagram”
Major Cause Categories
Cause
Cause
Cause
Cause
Cause
Cause
CAUSES
EFFECT
Brainstormed List
Cause
Cause
Effect Statement
Cause
Cause
Cause
Cause
Major Cause Categories
Identification of the most probable cause (s) leads to development
of theory for solution.

14. CAUSE AND EFFECT DIAGRAM
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Procedure
1 Determine quality characteristic and write it on the right-hand side of a sheet of
paper.
2 Find as many causes/factors which are considered to affect the quality
characteristic and write primary causes as big bones enclosed by squares.
3 Write the causes (secondary causes) which affect the big bones (primary causes)
as medium-sized bones and write the causes (tertiary causes) which affect the
medium sized bone as small bones. Go for brain storming sessions.
4 Assign an importance to each factor, and mark particularly important factors
which seem to have a significant effect on quality characteristic.
5 Record any necessary information. Use this diagram as a checklist of probable
causes of any problems and take corrective action accordingly.

15. FISHBONE DIAGRAM ` Be The Best Through Process Improvement METHOD
METHOD
MACHINE
PRESSURE SETTING
WATER ROLLER PROBLEM
INK FORM ROLLER SETTING
GAUGE PROBLEM
MEASUREMENT
INK ON NON-IMAGE AREA `
PLATE PROBLEM
IN-EXPERIENCED PERSONS
NEGLIGENCE
INK PROBLEM
FOUNTAIN SOLUTION
MATERIAL
MAN

16. CONTROL CHARTS What It Is?
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What It Is?
To display variation by a line graph in a time-ordered fashion. A centerline an control limits (based on + 3 standard deviations.) are placed on the graph to help analyze the patterns in the data.
Control Chart is a tool to monitor and control process variation on an on-going basis.
A graph or chart with limit lines is known as a control chart and the lines are called control limits.
Control Chart is composed of sub-groups.
Control Chart shows relationship between changes in production process and movements of points.

17. CONTROL CHARTS Rational Subgroups
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Rational Subgroups
A fundamental idea in the use of control chart is the collection of sample data according to what Shewhart called the rational subgroup concept. Subgroups or samples should be selected so that if assignable causes are present, the chance for differences between subgroups will be maximized, while the chance for differences due to theses assignable causes within subgroups will be minimized.
The points on CC represents arbitrary divisions in the manufacturing process, the data broken into theses divisions are referred to as sub-groups.
X chart minimizes the chance of variability due to assignable causes within a sample and maximizes the chance of variability between samples if assignable causes are present.
Control Chart can be used to determine the stability of common-cause variation in the process (in-control).
Control Chart also enables you to determine if the process output meets the requirements (capability).

18. Types CONTROL CHARTS A. For Variable Data
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Types
A. For Variable Data
x - R Chart _ is used where high volume production occurs, sample size units, diameter of shaft in a machine shop. It is used for controlling and analyzing a process. X represents the average value of a subgroup whereas R represents the range of the sub-group. X-R Chart shows relationship between changes in production process and the change (movement of points) on control chart.
Individual x - Moving Range Chart _ is used for shot run applications where sample size of one is only available, frequency of electricity in power plants measured every moment (say half an hour), viscosity of ink in printing press where one sample is taken after every half an hour.
B. For Attribute Data
p - Chart_ (fraction defective) is used for monitoring defective products, when ratio of defectives is monitored and lot size is not constant, e.g. daily defective pens in pen manufacturing plant.

19. CONTROL CHARTS
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Types
np Chart _ (number of defectives) is used for monitoring defectives products when defectives are monitored in a constant sample size, e.g. defective pens per carton of 1000 pens. It shows number of defectives when a subgroup size is constant.
c Chart _ is used for counting defects on a unit product, e.g. number of scratches on a car, number of pin holes in a specified area, etc. It is used when number of defects which appear in a fixed unit.
u Chart _ is used for counting defects on a lot of product differing in size, i.e. sample size is not constant, e.g. daily defects ratio of varying production, number of printing defects per printing job. Or it is used in dealing with number of defects when material inspected is not constant.

20. REFERENCE GUIDE TO CONTROL CHARTS
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A. FOR VARIABLE DATA
CHART CONTROL LIMITS CONTROL LIMITS SAMPLE SIZE
(For x) (For Range) __
CL = x
UCL = x + A2 R
LCL = x - A2 R =
CL = R
UCL = D1 R
LCL = D3 R
High Volume
Production
Samples per Plot = 3 - 5 __ __ __ =
x-R = __ __ __ __
Individual x-
Moving Range
CL = x
UCL = x +(2.66 x MR)
LCL = x - (2.66 x MR) __
CL = MR =  MR/n
UCL = 3.27 X MR
LCL = NONE __
Short Run Production
Sample per plot = 1 __ __ __
B. FOR ATTRIBUTE DATA
CHART CONTROL LIMITS SAMPLE SIZE TO MONITOR __ __
CL = Total defectives = p
Total Inspected
UCL = p p ( 1 - p ) n
LCL = p p ( 1 - p )
Varying
Defective Products p _ _ _  _ _ _  _ _
CL = pn
UCL = pn pn ( 1 - p )
LCL = pn pn ( 1 - p )
Constant
Defective Products pn _ _ _  _ _ _  _ _
CL = c = A defects
Number of Units
UCL = c c
LCL = c c
One
Defects c _ _  _ _  _ _
CL = u = Number of defects
Number of Units
UCL = u u / n
LCL = u u / n
Varying
Defects u _ _  _ _ 