This document discusses the implementation of control charts in manufacturing industries. It defines control charts and the different types, including those for attribute and variables data. An example is provided using data from a bottle manufacturing company to create an X-bar control chart to monitor bottle height. The conclusions are that control charts help ensure stable and controlled production by distinguishing common from special causes of variation, and the example analysis found the bottle height process to be in control.

1. Presented to:
Guddu Ali
U.I.D: K10990
Mechanical
IMPLIMENTATION OF “CONTROL CHART” IN
MANUFACTURING INDUSTRY
Presented to
Bhupendra Gehlot
Assistant professor of mechanical department

2. 1. Introduction
2. What is a control chart
3. Types of control chart
4. Methodology
5. Result
6. Control chart
7. Conclusion

3.  A control chart is a statistical tool used to
distinguish between variations in a process
resulting from common causes and variation
resulting from special causes.
 This is common cause variation. Control
Charts differentiate between these two types
of variation.
 A control chart consists of three horizontal
lines called; Upper Control Limit (UCL), Center
Line (CL) and Lower Control Limit (LCL).

4.  A control chart presents a graphic display of
process stability or instability over time.
 Every process has variation.
 This is common cause variation. Control
Charts differentiate between these two types
of variation. One goal of using a Control
Chart is to achieve and maintain process
stability.
 Process stability is defined as a state in which
a process has displayed a certain degree of
consistency in the past and is expected to
continue to do so in the future.

5. CONTROL CHART
DISPLAY
ATTRIBUTE DATA
DISPLAY
VARIABLES DATA
Attribute Data: This category of Control Chart displays data
that result from counting the number of occurrences or items in
a single category of similar items or occurrences. These “count”
data may be expressed as pass/fail, yes/no, or presence/absence
of a defect.
Variables Data: This category of Control Chart displays
values resulting from the measurement of a continuous variable.
Examples of variables data are elapsed time, temperature, and
radiation dose.

6.  In this study we have applied the control chart approach to
the data collected from ACE glass containers pvt-ltd
company. The variable under study is height of the specific
type of bottle. In data set there were 16 batches of 5
observations each shown in Table. The following
approaches based upon the principles of SQC were applied

7.  X bar, Range, S control charts for height of the bottle

8. For X bar chart the LCL=122.335 and UCL= 123.3, Center
line=122.81
X bar chart for height of the bottle

9. 1. Widely used in manufacturing industry. To
stable and controlled manufacturing of te
product.
2. Also used where large amount of
production is to be produced.
3. Also used in automobile industry, for the
control of error generation and for stable
production.

10.  ADVANTAGE:
1. Production of the product produced in
stable and controlled way.
2. Generation of the error is reduced.
3. We can easily see the result on the display
 DIADVANTAGE:
1. Difficult to count a large no of product queue.
2. Difficult to find upper and lower control line from a
large no of product queue.

11.  All through the study of control chart we understand that
how a manufacturing industry run in a control manner.
 In any manufacturing industry monitoring of their key
characteristics is most important.
 The absence of a quality control section may be one cause
of poor quality.
 In this study we have applied the control chart approach to
the data collected from ACE glass containers pvt-ltd
Company.
 In all figures the points are inside the control limits. This
indicates that the process is in control and the assignable
cause does not affect the process