1. 1
Project Report on
“IMPROVEMENT OF MEASUREMENT SYSTEM AND EVALUATION OF
PROCESS CAPABILITY”
Submitted in Partial Fulfilment of the Requirement
For
The Award of the Part Time Course
In
Statistical Quality Control
Session: January 2015 –August 2015
Submitted By:
Mr. Rohit Rajendran
Carried out at
INDIAN STATISTICAL INSTITUTE
SQC & OR UNIT

2. 2
Project Report
Submitted in Partial Fulfilment of the Requirement
For
The Award of the Part Time Course
In
Statistical Quality Control
Session: January 2015 –August 2015
Carried out at
INDIAN STATISTICAL INSTITUTE
SQC & OR UNIT
Guided By: Submitted By:
Mr. Boby John Mr. Rohit Rajendran
SQC & OR Unit Bangalore
ISI, Bangalore

3. 3
ACKNOWLEDGEMENT
I would like to thank Mr Boby John, ISI, Bangalore, for guiding to complete this
project successfully.
I am thankful to Mr P.T Maruthesh, Quality Assurance Manager, ACE
MANUFACTURING SYSTEM, who has over years of experience in manufacturing
and quality fields in different organization for guiding me in the factory
throughout the project.
I would like to thank all ACE members for their valuable suggestions and
encouragement during my project work at ACE MANUFACTURING SYSTEM.
I take this opportunity to thank Mr. Sanjit Ray, Course co-ordinator, SQC – OR
Unit, Bangalore, for arranging my project at SQC – OR unit, Bangalore.
I am thankful to all technical officers of the SQC-OR Unit, Bangalore for their
valuable suggestions and sharing industrial experience.
ROHIT RAJENDRAN

4. 4
S.NO CONTENTS PAGE NO.
1. Company profile 05
2. Project study 08
3. Objective 06
4. Data collection 12
5. Measurement system analysis 11
6. Gage R&R study calculation 14
9. Data collection after improvement 18
10 Gage r&r study calculation after improvement 20
11. Process capability 25
12. Conclusion 31

5. 5
INTRODUCTION
Preface:
Many organizations all over the world are facing high level competition for quality
of the product, performance of the product, delivery, price, safety and service. To
improve product quality and reduce variability a systematic study of all processes
are required to be done.
One such process which needs to be controlled is taken up for study and
improvement in Ace Manufacturing System, Bangalore.
1. COMPANY PROFILE – ACE MANUFACTURING SYSTEM
1.1. Introduction
AMS is one of the most preferred names in the automotive industry. AMS
products are used to produce critical parts for passenger vehicles, commercial
vehicles, two wheelers, three wheelers, and farm equipment. AMS is also a single
source supplier of machines to many Indian OEM manufacturers and large size
component manufacturers.
Our machining centers also find applications in the die & mould making industry
to manufacture plastic moulds, large press applications etc. One of the growing
markets in India is the Aerospace component manufacturing where investments
in Indian machining centers is on the rise. Another small but growing market for
AMS is the medical and the dental equipment manufacturers. Many of AMS’s high
accuracy machines find applications in this industry. AMS also caters to the needs
of the engineering industry including power & energy sector, oil & gas equipment
manufacturing, pumps, motors & hydraulic systems, defence and other
government sectors.
The highly productive drill tap machining centers are found to be very suitable for
the electronics industry such as the mobile phone and accessories market.
AMS offers versatile products for diverse applications, ensuring its customers are
catered with unique solutions for every machining needs.

6. 6
1.2. Products Manufactured
AMS is a part of the Ace Micromatic Group companies which is the largest
machine tool group in the country. The group has an expertise in making CNC
turning machines (Ace Designers Ltd.,), CNC grinding machines (Micromatic
Grinding Technologies Ltd.,), CNC machining centers (Ace Manufacturing Systems
Ltd.,) and Automatic tool changers & Turrets (Pragati Automation Ltd.,) for
machining centers and for turning centers respectively. A newer addition to the
group is a software company (Pioneer Computing Technologies Pvt. Ltd.) which
develops productivity monitoring tools for machining centers, turning machines
and grinding machines.
The group also has companies with the expertise in the manufacturing of
precision parts for medical equipment, energy sector, engineering industry, and
specialized gears & transmission components.
The marketing & sales of the products and the servicing of the machines
manufactured by the group are undertaken by Micromatic Machine Tools Pvt.
Ltd. MMT on behalf of AMS does the installation and commissioning of standard
products.
For special products, AMS takes up the responsibility to support MMT to execute
this process. Similarly all the service related queries are first addressed by trained
and certified engineers of MMT.
Complicated issues are immediately elevated to the customer support group of
AMS who analyse & resolve the problem.
OBJECTIVE:
1.3. Vision
Be a global leader in engineering and technology to deliver reliable, cost-effective,
quality products & services through passionate people with inspiring leadership.
1.4. Mission
To enhance our market share by steadily growing year on year to achieve Rs. 1000
Crores revenue by 2018 - 19 through continual improvement in technology,
production capacity, supply chain and skilled manpower.

7. 7
1.5. Values
The key values that are nurtured in every employee is as follows:
 Inspiring Leadership
 Passion
 Ethics
 Integrity
 Humility
 Trust
 Care
 Respect
 Customer focus
1.6. Philosophy
Achieve business excellence by being a dynamic organization with customer
centric and people centric approach and ethical practices.
1.7. Quality Policy
"We are committed to achieve total satisfaction of our customers through
timely delivery, innovation, development and continual improvement of
products, processes, people and suppliers with effective implementation of
quality management systems"
AMS is ISO 9001- 2008 certified for quality management system by TUV-NORD.
All products for export markets are CE certified.

8. 8
2. Project Study
Title: MSA IMPLEMENTATION AND PROCESS CAPABILITY STUDY ON REAR AXLE
HOUSING
Part: REAR AXLE HOUSING

9. 9
2.1. Operations carried out in CNC machine (Machine No: GEMINI MAX )
a) Facing operation
b) Outer diameter Turning operation
c) Drilling operation
d) Boring operation
e) Grooving
f) Facing operation
g) Outer diameter turning operation
h) Drilling operation
2.2. Machines Details
SL.NR NAME OF THE MACHINES YEAR QUANTITY
1) CNC –GEMINI MAX 2015 1

10. 10
Features:
 Twin spindle vertical machining center
 400mm distance between 2 spindles
 BT-50 spindle taper
 Twin arm type tool changing system
 Nearly double the productivity
 40 m/min rapid rate for all three axes
 LM guideways for all three axes
 Ideal for high volume component manufacturing
Model Unit Gemini Max
CAPACITY
Longitudinal travel ( X - Axis) mm 750
Headstock travel ( Y - Axis) mm 500
Cross travel ( Z - Axis) mm 600
Spindle face to table top mm 250-850
Distance between two spindles mm 400
TABLE
Table size mm*mm 1400x520
Max. load on Table kgf 1000
SPINDLE & AXES
Spindle taper 7 / 24 No.50
Spindle speed - Std. rpm 40-4000
Spindle speed - Opt. rpm
Spindle power - Std. kW 15 / 11 (2)
Spindle power - Opt. kW 26 / 22 (2)
Rapid traverse - X / Y / Z m/min 40 / 40 / 40
Feed rate mm/min 1 - 10000
Guideways Type LM
AUTOMATIC TOOL CHANGER
Tool change system Twin Arm
Tool storage capacity - Std. Nos. 20 (2)
Max. tool dia with adjacent pockets full mm 130
Max. tool dia with adjacent pockets empty mm 250
Max. tool length mm 350
Max. tool weight kgf 15
Chip to chip time sec. 6.6
Tool shank type BT - 50/HSK A100
CNC System Std-FANUC 0iMD
Opt.- Siemens
Power supply (Basic Machine) kva 80
Basic machine weight kgf 10500

11. 11
2.3. MEASUREMENT SYSTEM ANALYSIS
Methods to evaluate your measurement system and determine whether you can
trust your data. MSA helps determine how much of the overall process variation
is due to measurement system variation. Measurement system can include your
data collection procedures, gages, and other test equipment. Evaluation of your
measurement system should be done prior to control charting, capability analysis,
or any another analysis to prove that your measurement system is accurate and
precise and your data are trustworthy.
Sometimes, different measuring devices and operators can assess the same part
or sample and generate different results. Many different situations, such as
machine calibration problems or operators following different procedures, may
cause these differences. The more error in the measurements, the more likely you
are to make an error in your decisions based on those measurements.
To ensure measurement system is capable of precise measurement
Measurement System Analysis is an analysis of the measurement process, not an
analysis of the People
• To determine how much error is in the measurement due to the
measurement process itself.
• Quantifies the variability added by the measurement system.
Applicable to attribute data and variable data

12. 12
2.4. DATA COLLECTION FOR MEASUREMENT SYSTEM ANALYSIS
RUN
ORDER
Parts OPERATORS DISTANCE 17
MEASUREMENT
1 N11 Pradeep 16.9928
2 N11 Sukanush 16.9913
3 N11 Santhosh 16.9804
4 N12 Pradeep 16.9882
5 N12 Sukanush 16.9881
6 N12 Santhosh 16.9778
7 N13 Pradeep 16.9864
8 N13 Sukanush 16.9853
9 N13 Santhosh 16.9762
10 N14 Pradeep 16.9858
11 N14 Sukanush 16.9854
12 N14 Santhosh 16.9758
13 N15 Pradeep 16.9881
14 N15 Sukanush 16.9879
15 N15 Santhosh 16.9795
16 N16 Pradeep 16.9890
17 N16 Sukanush 16.9876
18 N16 Santhosh 16.9789
19 N17 Pradeep 16.9820
20 N17 Sukanush 16.9808
21 N17 Santhosh 16.9732
22 N18 Pradeep 16.9801
23 N18 Sukanush 16.9756
24 N18 Santhosh 16.9706
25 N19 Pradeep 16.9722
26 N19 Sukanush 16.9671
27 N19 Santhosh 16.9632
28 N20 Pradeep 16.9742
29 N20 Sukanush 16.9679
30 N20 Santhosh 16.9662
31 N11 Pradeep 16.9924
32 N11 Sukanush 16.9912
33 N11 Santhosh 16.9808

13. 13
34 N12 Pradeep 16.9886
35 N12 Sukanush 16.9883
36 N12 Santhosh 16.9777
37 N13 Pradeep 16.9871
38 N13 Sukanush 16.9847
39 N13 Santhosh 16.9750
40 N14 Pradeep 16.9854
41 N14 Sukanush 16.9852
42 N14 Santhosh 16.9755
43 N15 Pradeep 16.9880
44 N15 Sukanush 16.9883
45 N15 Santhosh 16.9796
46 N16 Pradeep 16.9885
47 N16 Sukanush 16.9872
48 N16 Santhosh 16.9785
49 N17 Pradeep 16.9821
50 N17 Sukanush 16.9797
51 N17 Santhosh 16.9730
52 N18 Pradeep 16.9795
53 N18 Sukanush 16.9748
54 N18 Santhosh 16.9699
55 N19 Pradeep 16.9722
56 N19 Sukanush 16.9669
57 N19 Santhosh 16.9632
58 N20 Pradeep 16.9744
59 N20 Sukanush 16.9684
60 N20 Santhosh 16.9651
61 N11 Pradeep 16.9920
62 N11 Sukanush 16.9908
63 N11 Santhosh 16.9810
64 N12 Pradeep 16.9885
65 N12 Sukanush 16.9877
66 N12 Santhosh 16.9780
67 N13 Pradeep 16.9872
68 N13 Sukanush 16.9850
69 N13 Santhosh 16.9767

14. 14
70 N14 Pradeep 16.9860
71 N14 Sukanush 16.9842
72 N14 Santhosh 16.9750
73 N15 Pradeep 16.9876
74 N15 Sukanush 16.9887
75 N15 Santhosh 16.9785
76 N16 Pradeep 16.9884
77 N16 Sukanush 16.9860
78 N16 Santhosh 16.9777
79 N17 Pradeep 16.9815
80 N17 Sukanush 16.9791
81 N17 Santhosh 16.9727
82 N18 Pradeep 16.9794
83 N18 Sukanush 16.9755
84 N18 Santhosh 16.9701
85 N19 Pradeep 16.9722
86 N19 Sukanush 16.9669
87 N19 Santhosh 16.9637
88 N20 Pradeep 16.9742
89 N20 Sukanush 16.9688
90 N20 Santhosh 16.9657
Gage R&R Study Worksheet
Parts: 10 Operators: 3
Replicates: 3 Total runs: 90
2.5. Gage R&R Study - ANOVA Method (USING MINITAB)
Gage R&R for MEASUREMENTS
Gage name: CMM
Date of study: 03/07/2015
Reported by: P.T MARUTHESH
Tolerance: 16.950 TO 17.050

15. 15
Two-Way ANOVA Table with Interaction
Source DF SS MS F P
Parts 9 0.0039733 0.0004415 65.733 0.000
Operators 2 0.0015830 0.0007915 117.845 0.000
Parts *Operators 18 0.0001209 0.0000067 33.826 0.000
Repeatability 60 0.0000119 0.0000002
Total 89 0.0056891
α to remove interaction term = 0.05
Gage R&R
Source Var Comp %Contribution
(of Var Comp)
Total Gage R&R 0.0000285 37.13
Repeatability 0.0000002 0.26
Reproducibility 0.0000283 36.87
Operators 0.0000262 34.04
Operators*Parts 0.0000022 2.83
Part-To-Part 0.0000483 62.87
Total Variation 0.0000768 100.00
Process tolerance = 1

16. 16
Source StdDev (SD) Study Var
(6 × SD)
%Study Var
(%SV)
Total Gage R&R 0.0053413 0.0320480 60.93
Repeatability 0.0004456 0.0026736 5.08
Reproducibility 0.0053227 0.0319363 60.72
Operators 0.0051146 0.0306874 58.35
Operators*Parts 0.0014740 0.0088438 16.82
Part-To-Part 0.0069503 0.0417020 79.29
Total Variation 0.0087657 0.0525940 100.00

17. 17
Gage R&R for MEASUREMENTS – GRAPH (FROM MINITAB)

18. 18
The measurement system study showed that % study variance is 60.92% much
higher than the upper limit of 30%. Hence the measurement system requires
drastic improvement.
 Red: Above 30% (Not Acceptable)
2.6. To improve the Measurement System Analysis of CMM (Coordinate
Measuring Machine) the following steps are taken into consideration:
 See when the CMM machine was calibrated, if not calibrated according to
the machine company norms, take action to calibrate the machine.
 Train the operator according to the procedures mentioned by the CMM
machine.
 Follow the procedure.
 See the part is placed in the correct position using the particular fixture for
the REAR AXLE HOUSING
 Clean the surface plate and the part using ethanol, free from dust particle
 Keep the part and fixture on the surface plate without any additional sheet
on the surface plate take the measurement on CMM
 Collect the data by following the above mentioned points.
2.6.1. DATA COLLECTION FOR MEASUREMENT SYSTEM ANALYSIS AFTER
IMPROVEMENT:
RUN
ORDER
Parts OPERATORS DISTANCE 17
MEASUREMENT
1 N11 Pradeep 16.9928
2 N11 Sukanush 16.9913
3 N11 Santhosh 16.9904
4 N12 Pradeep 16.9882
5 N12 Sukanush 16.9881
6 N12 Santhosh 16.9880
7 N13 Pradeep 16.9864
8 N13 Sukanush 16.9853
9 N13 Santhosh 16.9858
10 N14 Pradeep 16.9858
11 N14 Sukanush 16.9854

19. 19
12 N14 Santhosh 16.9856
13 N15 Pradeep 16.9881
14 N15 Sukanush 16.9879
15 N15 Santhosh 16.9880
16 N16 Pradeep 16.9890
17 N16 Sukanush 16.9876
18 N16 Santhosh 16.9885
19 N17 Pradeep 16.9820
20 N17 Sukanush 16.9808
21 N17 Santhosh 16.9815
22 N18 Pradeep 16.9801
23 N18 Sukanush 16.9801
24 N18 Santhosh 16.9801
25 N19 Pradeep 16.9722
26 N19 Sukanush 16.9720
27 N19 Santhosh 16.9721
28 N20 Pradeep 16.9742
29 N20 Sukanush 16.9679
30 N20 Santhosh 16.9742
31 N11 Pradeep 16.9924
32 N11 Sukanush 16.9912
33 N11 Santhosh 16.9916
34 N12 Pradeep 16.9886
35 N12 Sukanush 16.9883
36 N12 Santhosh 16.9885
37 N13 Pradeep 16.9871
38 N13 Sukanush 16.9847
39 N13 Santhosh 16.9850
40 N14 Pradeep 16.9854
41 N14 Sukanush 16.9852
42 N14 Santhosh 16.9850
43 N15 Pradeep 16.9880
44 N15 Sukanush 16.9883
45 N15 Santhosh 16.9880
46 N16 Pradeep 16.9885
47 N16 Sukanush 16.9872

20. 20
48 N16 Santhosh 16.9875
49 N17 Pradeep 16.9732
50 N17 Sukanush 16.9797
51 N17 Santhosh 16.9730
52 N18 Pradeep 16.9795
53 N18 Sukanush 16.9748
54 N18 Santhosh 16.9770
55 N19 Pradeep 16.9622
56 N19 Sukanush 16.9669
57 N19 Santhosh 16.9632
58 N20 Pradeep 16.9664
59 N20 Sukanush 16.9684
60 N20 Santhosh 16.9651
61 N11 Pradeep 16.9920
62 N11 Sukanush 16.9908
63 N11 Santhosh 16.9910
64 N12 Pradeep 16.9885
65 N12 Sukanush 16.9877
66 N12 Santhosh 16.9880
67 N13 Pradeep 16.9872
68 N13 Sukanush 16.9850
69 N13 Santhosh 16.9867
70 N14 Pradeep 16.9860
71 N14 Sukanush 16.9842
72 N14 Santhosh 16.9850
73 N15 Pradeep 16.9876
74 N15 Sukanush 16.9887
75 N15 Santhosh 16.9885
76 N16 Pradeep 16.9884
77 N16 Sukanush 16.9860
78 N16 Santhosh 16.9877
79 N17 Pradeep 16.9815
80 N17 Sukanush 16.9791
81 N17 Santhosh 16.9727
82 N18 Pradeep 16.9794
83 N18 Sukanush 16.9755

21. 21
84 N18 Santhosh 16.9760
85 N19 Pradeep 16.9622
86 N19 Sukanush 16.9669
87 N19 Santhosh 16.9637
88 N20 Pradeep 16.9642
89 N20 Sukanush 16.9688
90 N20 Santhosh 16.9657
2.6.2. Gage R&R Study Worksheet
Parts: 10 Operators: 3
Replicates: 3 Total runs: 90
2.6.3. Gage R&R Study – ANOVA Method (USING MINITAB)
Gage R&R for MEASUREMENTS
Gage name: CMM
Date of study: 14/08/2015
Reported by: P.T MARUTHESH
Tolerance: 16.950 TO 17.050
Two-Way ANOVA Table with Interaction :
Source DF SS MS F P
Parts 9 0.0060633 0.0006737 197.310 0.000
Operators 2 0.0000096 0.0000048 1.411 0.270
Parts *Operators 18 0.0000615 0.0000034 0.546 0.923
Repeatability 60 0.0003754 0.0000063
Total 89 0.0065098
α to remove interaction term = 0.05

22. 22
Two-Way ANOVA Table without Interaction:
Source DF SS MS F P
Parts 9 0.0060633 0.0006737 120.290 0.000
Operators 2 0.0000096 0.0000048 0.860 0.427
Parts *Operators 78 0.0004369 0.0000056
Total 89 0.0065098
Gage R&R :
Source Var Comp %Contribution
(of Var Comp)
Total Gage R&R 0.0000056 1.42
Repeatability 0.0000056 1.42
Reproducibility 0.0000000 0.00
Operators 0.0000000 0.00
Part-To-Part 0.0000742 5.17
Total Variation 0.0000792 5.36
Process tolerance = 1

23. 23
Source StdDev
(SD)
Study Var
(6 × SD)
%Study Var
(%SV)
Total Gage R&R 0.0023666 0.0141995 26.49
Repeatability 0.0023666 0.0141995 26.49
Reproducibility 0.0000000 0.0000000 0.00
Operators 0.0000000 0.0000000 0.00
Part-To-Part 0.0086159 0.0516954 96.43
Total Variation 0.0089350 0.0536101 100.00

24. 24
2.6.4. Gage R&R for MEASUREMENTS – GRAPH (FROM MINITAB) AFTER
IMPROVEMENT:

25. 25
The measurement system study showed that % study variance is 26.49% is lower
than that of 30%. Hence the measurement system is improved.
 Yellow: Below 30% (Acceptable)
2.7. Process Capability Analysis:
The process capability analysis is carried out on the dimension distance. The
specification on the distance is given below:
LSL 16.95
USL 17.05
The data on distance collected for the capability analysis is given below.
Distance-17 Data
16.98031 16.97074 16.97986 16.9900
16.99197 16.97911 16.97985 16.98169
16.99292 16.9865 16.97973 16.97768
16.98339 16.98434 16.97997 16.98467
16.9796 16.97848 16.98297 16.97736
16.97642 16.98812 16.99152 16.98192
16.99308 16.98389 16.98066 16.97885
16.98228 16.9938 16.98406 16.98647
16.98713 16.98217 16.9878 16.98572
16.9822 16.98575 17.00387 16.98359
16.99491 16.97549 16.98855 16.96163
16.98784 16.97683 16.98206 16.98949
16.99287 16.98827 16.97057 16.96539
16.96963 16.98518 16.96545 16.97903
16.97807 16.99617 16.96505 16.97928
16.97287 16.99001 16.99084 16.98201
16.97601 16.98332 16.98832 16.97688
16.96762 16.98875 16.97127 16.99789
16.98545 16.97142 16.98139 16.97798
16.97825 16.99476 16.98446 16.97154
16.98869 16.98393 16.99483 16.97797
16.96523 16.97457 16.97823 16.97346
16.99486 16.99508 16.97804 16.98153
16.97653 16.98214 16.9768 16.97773
16.97395 16.9838 16.98442 16.97624

26. 26
A normality test is conducted to verify whether the distance follows normal
distribution or not. The normality test output is given below:
Since the p value = 0. 601 > 0.05, it is concluded that distance is normally
distributed.

27. 27
The process capability analysis is carried out using Minitab statistical software.
The Minitab output of capability analysis is given below:
The capability analysis shows that Pp = 2.07 and Ppk = 1.32. Since both Pp & Ppk
are greater than 1, the process is capable and the overall PPM is only 35.95.
The process capability analysis also showed that Ppk < Pp. Hence there is scope for
further improvement. So actions are taken to centre the process at the middle of
the specification. The actions are taken against the following problems faced:
 Improper tool setting
 Improper component setting
 Error in CNC programs
 Initial setting of the machine
 Dust & External particle on the component or CNC cabinet
 Machine assembly fault

28. 28
After actions are taken to shift the mean of the process to the middle of the
specification, data on distance is again collected and is given below:
Distance - After
16.99203 17.0044 17.00078 17.0165
16.99436 17.00082 16.98225 16.99854
16.99804 16.99177 16.99078 16.98902
16.9897 16.98581 16.99988 17.00919
17.00953 17.01838 16.99869 17.00522
17.00909 16.98836 16.98254 16.99951
17.00371 16.99425 17.00201 17.01268
16.9863 16.99706 16.99726 17.0022
17.00468 17.01293 17.01383 16.97561
16.997 16.99618 17.0067 17.0017
17.00961 16.99917 16.99666 17.00216
16.99481 16.99467 17.00049 17.00517
17.00565 17.0073 16.99667 16.99708
17.0095 16.9826 16.99926 16.9923
17.00503 16.99662 16.98833 16.99106
16.99602 17.00392 17.01425 17.00227
16.99663 16.9965 16.99584 16.99789
16.99776 17.00368 17.00114 16.99469
17.0082 16.99005 16.99041 16.99415
16.99292 17.01033 17.00165 16.99594
16.99628 17.00119 16.99344 17.00753
16.98913 17.00442 17.00979 16.99723
17.00166 17.00821 17.00481 16.99561
17.00473 17.00503 16.99918 17.00188
17.00302 17.00225 16.98898 17.01316

29. 29
The normality test results are given below.
Since the p value = 0.903 > 0.05, it is concluded that the quality characteristic
distance is normally distributed. The process capability output is given below:

30. 30
2.7.1. Conclusion For Process Capability:
 The process capability analysis showed that the mean has shifted to
16.9995 and Ppk has become 2.05 very close to the Pp value of 2.07.
Moreover the PPM also reduce to almost nil from around 35.
 The process has become highly capable capable since both Pp and Ppk are
greater than 2.

31. 31
2.8. Conclusion
 The Gage R&R of the REAR AXLE HOUSING is reduced from 60.93% to
26.49% which shows that the measurement system is acceptable after
improvement in the procedure.
 The Process has become highly capable with Pp=2.07 and Ppk=12.05
 The Process capability analysis showed that it has centered to the mean
after actions are taken to the machine.
 Hence the Measurement system is improved and the process capability of
the machine is improved and centered.
2.9. KNOWLEDGE GAINED FROM THIS PROJECT:
 Importance of project
 Project charter
 Statistical tool usage
– MSA
– Normality test
– Capability analysis