Abstract image of a woman sitting on books and studying on a laptop

Project_report

R
Rohit Rajendran

This document is a project report submitted by Rohit Rajendran to fulfill the requirements for a part time course in Statistical Quality Control. It discusses improving the measurement system and evaluating the process capability at ACE Manufacturing System in Bangalore. The report includes details about the company, the rear axle housing part being studied, the measurement operations and CNC machine used. It describes implementing a Measurement System Analysis to determine the accuracy and precision of the measurement process and collecting initial data from 3 operators measuring 30 parts. The objectives are to analyze the measurement system, collect additional data after improvements, and analyze the process capability.

1 of 31
Download to read offline
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
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 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 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 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 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 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 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 2. Project Study Title: MSA IMPLEMENTATION AND PROCESS CAPABILITY STUDY ON REAR AXLE HOUSING Part: REAR AXLE HOUSING
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 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 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 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 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 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 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 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 Gage R&R for MEASUREMENTS – GRAPH (FROM MINITAB)
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 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 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 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 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 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 2.6.4. Gage R&R for MEASUREMENTS – GRAPH (FROM MINITAB) AFTER IMPROVEMENT:
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 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 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 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 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 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 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

More Related Content

PDF
Design and Analysis of Chute System to obtain World Class OEE
ijsrd.com
 
PDF
HUNAN TIANYOU PRECISION TECHNOLOGY CO., LTD
Chuck Chen
 
PPS
MSI Growth
VanessaLP
 
PDF
To Improve Quality and Reduce Rejection Level through Quality Control
rahulmonikasharma
 
PDF
TIAYO
Chuck Chen
 
PDF
Speed Automation, Pune, Industrial Machinery
IndiaMART InterMESH Limited
 
PDF
Pmt overmolding presentation
Charles Sholtis
 
PPTX
SANTEC GROUP PPT PRESENTATION - LATEST UPLOAD ON 16TH APRIL 2020
SANTEC GROUP
 
Design and Analysis of Chute System to obtain World Class OEE
ijsrd.com
 
HUNAN TIANYOU PRECISION TECHNOLOGY CO., LTD
Chuck Chen
 
MSI Growth
VanessaLP
 
To Improve Quality and Reduce Rejection Level through Quality Control
rahulmonikasharma
 
TIAYO
Chuck Chen
 
Speed Automation, Pune, Industrial Machinery
IndiaMART InterMESH Limited
 
Pmt overmolding presentation
Charles Sholtis
 
SANTEC GROUP PPT PRESENTATION - LATEST UPLOAD ON 16TH APRIL 2020
SANTEC GROUP
 

What's hot (19)

PPTX
Checkweigher ipc shubham automation
shubhamautomation
 
PDF
CORPORATE_PROFILE-E-(2a)-400(Jul2015)
Pablo Liechti
 
PPS
Tooling
rebecca210
 
DOC
Yes Yes Technologies
Point Scale
 
PDF
IRJET- Six Axis Pneumatic Materials Handling Robotic Arm
IRJET Journal
 
PPTX
Bluestar profile 2013
Huy Dickens
 
PDF
Study of Total Productive Maintenance & It’s Implementation Approach in Steel...
IRJET Journal
 
PDF
N. R. Enterprises, Pune, Digital Controller
IndiaMART InterMESH Limited
 
PDF
Perfect engineers-ghaziabad
Perfect Engineers, Ghaziabad
 
PDF
A STUDY OF ENQUIRY RESPONSE LEAD TIME AND CAPACITY UTILIZATION AT PEEKAY STEE...
Muhammed Anaz PK
 
PDF
Implementing 5 s methodology as tool for improving efficiency
Laukik Raut
 
PDF
Beta Blowers Catalogue
BetaBlowers1
 
PPTX
Capabilities brochure 2008
Mark Netherland
 
PDF
Application of industrial engineering in garments sewing floor
Rakibul Hasan
 
PDF
Profile ptc-final
PTRANSANDCONTROLS
 
PPT
Milk Money - Using ISA-95 Integration
Steven Muñoz
 
PDF
Application of Lean Concepts in Molding Department
IRJET Journal
 
PPTX
Servo Stabilizer Manufacturers in India- Purevolt
Purevolt Products Pvt. Ltd
 
PDF
Introducing Automation In Manufacturing Business PowerPoint Presentation Slides
SlideTeam
 
Checkweigher ipc shubham automation
shubhamautomation
 
CORPORATE_PROFILE-E-(2a)-400(Jul2015)
Pablo Liechti
 
Tooling
rebecca210
 
Yes Yes Technologies
Point Scale
 
IRJET- Six Axis Pneumatic Materials Handling Robotic Arm
IRJET Journal
 
Bluestar profile 2013
Huy Dickens
 
Study of Total Productive Maintenance & It’s Implementation Approach in Steel...
IRJET Journal
 
N. R. Enterprises, Pune, Digital Controller
IndiaMART InterMESH Limited
 
Perfect engineers-ghaziabad
Perfect Engineers, Ghaziabad
 
A STUDY OF ENQUIRY RESPONSE LEAD TIME AND CAPACITY UTILIZATION AT PEEKAY STEE...
Muhammed Anaz PK
 
Implementing 5 s methodology as tool for improving efficiency
Laukik Raut
 
Beta Blowers Catalogue
BetaBlowers1
 
Capabilities brochure 2008
Mark Netherland
 
Application of industrial engineering in garments sewing floor
Rakibul Hasan
 
Profile ptc-final
PTRANSANDCONTROLS
 
Milk Money - Using ISA-95 Integration
Steven Muñoz
 
Application of Lean Concepts in Molding Department
IRJET Journal
 
Servo Stabilizer Manufacturers in India- Purevolt
Purevolt Products Pvt. Ltd
 
Introducing Automation In Manufacturing Business PowerPoint Presentation Slides
SlideTeam
 
Ad

Viewers also liked (13)

PPTX
Aula de filosofia.
Professorgeninho Araujo
 
PPTX
C for FIRST LESSON
約銘 陳
 
PPTX
Etapa productiva
deisitha27
 
PDF
WightmanThomas_resume2
Thomas Wightman
 
PDF
Payroll admin
Christo Holtzhausen
 
DOCX
marieginax
Gina Aguirre
 
PDF
BOA LineSheet DM
Mike Martin
 
PDF
Governor punjab ka qatal aur janaza
Muhammad Tariq
 
PPTX
ಸುಳ್ಳು ಆಣೆ
FAHIM AKTHAR ULLAL
 
DOCX
laurieresume1
Laurie Stott
 
PPT
Borco Aleksov NHEC QA in HE Cooperation
Borco Aleksov
 
PPT
Tema 1 prehistoria
rebatar
 
PDF
Feefo - The Power of Reviews in Search
Sagittarius
 
Aula de filosofia.
Professorgeninho Araujo
 
C for FIRST LESSON
約銘 陳
 
Etapa productiva
deisitha27
 
WightmanThomas_resume2
Thomas Wightman
 
Payroll admin
Christo Holtzhausen
 
marieginax
Gina Aguirre
 
BOA LineSheet DM
Mike Martin
 
Governor punjab ka qatal aur janaza
Muhammad Tariq
 
ಸುಳ್ಳು ಆಣೆ
FAHIM AKTHAR ULLAL
 
laurieresume1
Laurie Stott
 
Borco Aleksov NHEC QA in HE Cooperation
Borco Aleksov
 
Tema 1 prehistoria
rebatar
 
Feefo - The Power of Reviews in Search
Sagittarius
 
Ad

Similar to Project_report (20)

PDF
Presentation ukay 2014 - ashok 17.02.2014
Ashok Chandak
 
PDF
Study of Fabrication of Multipurpose Tooling Machine
IRJET Journal
 
PDF
IRJET-Production of Hybrid Aluminium Matrix Composite with Welding Slag and F...
IRJET Journal
 
DOCX
INDUSTRIAL TRAINING REPORT
SUYASH TRIVEDI
 
PDF
Internship Report_Jyoti CNC Automation Pvt Ltd
Malay Nasit
 
PDF
Trough External Service Management Improve Quality & Productivity
IJMER
 
PDF
Trough External Service Management Improve Quality & Productivity
IJMER
 
PDF
IRJET- Robotic System for Automatic Pouring of Molten Metal using PLC
IRJET Journal
 
PDF
SMC Pneumatics (India) Pvt. Ltd., Noida, Pneumatic Automation Products
IndiaMART InterMESH Limited
 
PDF
Road map of development for pull system in thailand small and medium automoti...
eSAT Publishing House
 
PPTX
G.I Auto Presentation - company infrastructure
naveenbasavaraju1
 
PDF
Universal Engineers, Ahmedabad, CNC machined part
IndiaMART InterMESH Limited
 
PDF
Automatic Shoe Polisher Prototype Development using the Application of Value ...
IRJET Journal
 
PPT
V.p. arora operations mgmt
Jagdeep Chugh
 
PPTX
TEAM GALILEO | National Management Olympiad Season 4 Quarter Final Stage BCS ...
National Management Olympiad
 
PPTX
Automotive Shifter Manufacturing Process, Machinery Requirements and Project ...
IMARC Group
 
PDF
Root Causes Analysis for Lean Maintenance Using Six Sigma Approach
theijes
 
PDF
Virtual Commissioning of Small to Medium Scale Industry Using the Concepts of...
IJERA Editor
 
PDF
Ajay_Training_Report[1]
AJAY KUMAR
 
PDF
IRJET- Enhance the Capacity of Outer Tube Machining Cell
IRJET Journal
 
Presentation ukay 2014 - ashok 17.02.2014
Ashok Chandak
 
Study of Fabrication of Multipurpose Tooling Machine
IRJET Journal
 
IRJET-Production of Hybrid Aluminium Matrix Composite with Welding Slag and F...
IRJET Journal
 
INDUSTRIAL TRAINING REPORT
SUYASH TRIVEDI
 
Internship Report_Jyoti CNC Automation Pvt Ltd
Malay Nasit
 
Trough External Service Management Improve Quality & Productivity
IJMER
 
Trough External Service Management Improve Quality & Productivity
IJMER
 
IRJET- Robotic System for Automatic Pouring of Molten Metal using PLC
IRJET Journal
 
SMC Pneumatics (India) Pvt. Ltd., Noida, Pneumatic Automation Products
IndiaMART InterMESH Limited
 
Road map of development for pull system in thailand small and medium automoti...
eSAT Publishing House
 
G.I Auto Presentation - company infrastructure
naveenbasavaraju1
 
Universal Engineers, Ahmedabad, CNC machined part
IndiaMART InterMESH Limited
 
Automatic Shoe Polisher Prototype Development using the Application of Value ...
IRJET Journal
 
V.p. arora operations mgmt
Jagdeep Chugh
 
TEAM GALILEO | National Management Olympiad Season 4 Quarter Final Stage BCS ...
National Management Olympiad
 
Automotive Shifter Manufacturing Process, Machinery Requirements and Project ...
IMARC Group
 
Root Causes Analysis for Lean Maintenance Using Six Sigma Approach
theijes
 
Virtual Commissioning of Small to Medium Scale Industry Using the Concepts of...
IJERA Editor
 
Ajay_Training_Report[1]
AJAY KUMAR
 
IRJET- Enhance the Capacity of Outer Tube Machining Cell
IRJET Journal
 

Project_report

  • 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