The document discusses the importance of statistical quality control (SQC) in manufacturing to maintain consistent product quality amidst high production volumes. It outlines various types of variations, SQC categories such as descriptive statistics and statistical process control (SPC), and methods like acceptance sampling and control charts for monitoring and ensuring quality. It also highlights the advantages of SQC, including improved product quality and reduced rejection rates, while acknowledging its limitations and the need for careful application.

1. INTRODUCTION-
Today’s market is very competitive. So it is necessary for the manufacturers to maintain
consistent quality for their product. In order to ensure and maintain consistent quality,
they have to check each and every product they produce.
But it is not possible due to very large amount of production. Thus, to maintain the
consistent and uniform quality of their product they have to know about the statistical
quality control technique.
SQC consist three words: statistical, quality and control.
STATISTICAL- Statistical is related to the use of statistics.
statistics refers to the collection ,classification ,summarising and presentation of quantitative
data.
QUALITY- Quality refers to the distinctive attributes possessed by something which is free
from defects, deficiencies, and significant variations.
CONTROL- Control refers to the process of finding variations by comparing with standards
and taking corrective action.
Father of statistical quality control
Walter Andrew Shewhart (1891-1967)
us physicist and statistician
CHARACTERISTICS OF SQC –
•It is designed to control the quality standard of goods produced for marketing.
•It is exercise by the producers during the production process.
•It is carried out with the help of certain statistical tools.
•It is designed to determine the variations in quality of the goods.
•It aims to ascertain whether the production process is in control or not, and whether the products
are of specified quality.
•It is an economical measure of assessing the quality standard of goods through statistical
experiment without checking every product in detail.

2. VARIATION IN QUALITY-
No two items are exactly alike.
Some sort of variations in the two items is bound to be there. In fact it is an integral part of any
manufacturing process.
This difference in characteristics known as variation.
This variation may be due to substandard quality of raw material, carelessness on the part of
operator, fault in machinery system etc..
TYPES OF VARIATIONS-
Variation due to ‘CHANCE CAUSES’
Variation due to ‘ASSIGNABLE
CAUSES’
Variation due to chance causes/common causes-
Variation occurred due to chance.
This variation is not due to defect in machine, raw material or any other factors.
Behave in “random manner”.
Negligible but inevitable.
The process is said to be under the state of statistical control.
Variation due to assignable causes-
Difference in quality of raw material.
Difference in machines.
Difference in operators.
Difference time.
CATEGORIES OF SQC-
Descriptive statistics
Statistical process control(SPC)
Acceptance sampling
Descriptive statistics-
Descriptive statistics are used to describe quality characteristics and
relationships.
The mean- measure of central tendency.
The range- difference between largest/smallest observation in a set of data.
Standard deviation- measures the amount of data dispersion around mean.

3. Statistical process control-
SPC involves inspecting a random sample of the output from a process and deciding
whether the process is producing products with characteristics that fall within a
predetermined range. SPC answer the question of whether the process is functioning
properly or not.
Extend the use of descriptive statistics to monitor the quality of the product and
process.
SPC help to determine the amount of variation.
To make sure the process is in a state of control.
Acceptance sampling-
Acceptance sampling is an important field of SQC that was popularized by
Dodge and Romig and originally applied by the U.S. military to the testing of
bullets during world war II.
Acceptance sampling is the process of randomly inspecting a sample of goods
and deciding whether to accept the entire lot based on the results.
Acceptance sampling determines whether a batch of goods should be accepted
or rejected.
CONTROL CHARTS-
A control chart is a line graph on which control limit lines are plotted in order to
find out if a process is in a stable condition, or in order to keep it so.
A control chart always has a central line (CL) for the average, an upper line for
the upper control limit (UCL), and a lower line for the lower contrl limit (LCL).
CONTROL CHARTS- PURPOSE AND ADVANTAGES:
A control chart indicates whether the process is in control or out of control.
It determines process variability and detects unusual variation taking place in a process.
It ensures product quality level.
It provides information about the selection of process and setting of tolerance limits.

4. Types of control chart-
Control chart may be grouped under two main heads:
1.Variables
2. Attributes
Variables- variables control charts are used to evaluate variation in a process where the
measurement is a variable-i.e. the variable can be measured on a continuous scale (e.g.
height, weight, length, concentration).
Types: X-bar chart (mean, average)
R- chart (range)
Attributes- an attribute control chart is a way to track the production of
defective items.
The chart does not tell you why the defects happened, but it does give you the
total or average counts per unit.
An attribute is a count or discrete data like conforming/non-conforming,
pass/fail, or yes/no.
Types- p-chart (fraction, proportion)
np-chart (no. of defective)
c-chart (defects)
P- CHART
A p- chart is a commonly used control chart for attributes, whereby the quality
characteristics is counted, rather than measured. This chart is used to control the general
quality of the component parts.
It can be a fraction defective chart or % defective chart.
Each item is classified as good or bad.
Formula

5. Example:

6. Np - chart
Np chart is very similar to the p-chart. Np chart plots the number of items, while p
chart plot the proportion of defective items. In np-chart, number of defectives is plots
on the y-axis and the number of samples on the x-axis.
C- chart
A c-chart is a type of control chart that shows how many defects or
nonconformities are in sample of constant size, taken from a process.

7. X-bar and r-chart
The x-bar and R-chart are quality control charts used to monitor the mean and variation
of a process based on samples taken in a given time. The control limits on both charts
are used to monitor the mean and variation of the process going forward.

9. ADVANTAGES-
It provides a means of detecting error at inspection.
It revels whether the production process is in control or not.
It leads to more uniform quality of production.
It improves the relationships with the customer, reduced customer complaints.
Reduction of scarp.
It reduces the number of rejects and saves the cost of material.
It reduces inspection costs.
It leads to more uniform quality of product.
It leads to a false sense of security in the absence of general quality awareness.
It provides only an information service, and it can not reduce the managers responsibility.
It cannot be applied mechanically to all production process without studying their
peculiar environments.
It involves mathematical and statistical problems in the process of analysis.
LIMITATIONS-