SlideShare une entreprise Scribd logo
1  sur  6
Télécharger pour lire hors ligne
Proc. of Int. Conf. on Advances in Mechanical Engineering, AETAME

Productivity Studies of Ultra High Density (UHD)
Stitching Process
M.N Shruthi1, M.N VijayKumar2, Dr. K.N Subramanya3
1

R V College of Engineering, Department of Industrial Engineering and Management, Bangalore, Karnataka, India
Email: shruthimn@rvce.edu.in
Email: vijayakumar@rvce.edu.in /subramanyakn@rvce.edu.in

Abstract—This paper focuses on Ultra High Density (UHD) stitching process of connectors,
where the company relies on 100% manual inspection in UHD connectors. Based on
historical data on production of UHD connectors, typically labour cost involved in
inspection and testing is around 15% of the total manufacturing cost. This poses both
challenges and opportunities for improvement in the bottleneck process, which is the
inspection process. The female connectors quantity produced is on the average of 2000
parts/shift. It takes around 47 sec of visual inspection per connector and around 2.89 sec per
piece for go-gauge inspection. Considering these factors, the objectives of the study was to
understand the whole process in its entirety and then use this knowledge to re-organize the
stages staring from the automatic stitching process. By using process improvement tools of
time study, methods and process mapping, a process re-orientation and re-organization has
been carried out. This resulted in not only reduction of time of inspection and testing of the
connectors, but also the piece inspection process reduced from an average total time of
112.59 sec to 86.15 sec. Overall improvement was also increased from 56% to 79.5%.
Index Terms—Process Mapping, Process Re-engineering, Ultra High Density.

I. INTRODUCTION
With emerging global competition and rising customer expectation, providing lowcost and high quality
products is a winning mantra in the current business scenario.These high expectations can be met through
low cost automation and by keeping lowoperational cost [1]. An automated visual inspection is one way for
detecting all visual defects in a high volume manufacturing industry [2]. Colour image processing can be
used for detecting the missing components or misaligned components. This can also be used for the visual
inspection that results in high false call rate, which then leads to use background subtraction to identify
defects. This feasibility decreases the setup costs by taking into account different types of data positioning,
occlusions andtolerances [3]. New techniques have been proposed to reduce theinspection time using timemotion study.The paper illustrates the process ofinspection carried out in UHD connector [4]. Itwas found
that by carrying out time and method study results in overall improvement of the process. Attribute
agreement analysis can also be used to determine the inconsistencies of the defects in visual inspection of
pass/fail decisions which can be identified and solve the main causes of poor inspection performance [5].The
use of a priori knowledge about a scene to coordinate and control bi-level image segmentation, interpretation,
and shape inspection of different objects in the scene. The approach is composed of two main steps. The first
step consists of proper segmentation and labelling of individual regions in the image for subsequent ease in
interpretation [6]. The common approaches to visual inspection, to consider the specification and analysis of
DOI: 02.AETAME.2013.4.38
© Association of Mechanical and Aeronautical Engineers, 2013
dimensional tolerances and theirinfluence on the inspection task. Recent developments in automated visual
inspection, is the expanded role of computer-aided design (CAD) data in many systems [7].
II. PROCESS STUDY AND MAPPING OF UHD STITCHING PROCESS
Connectors are devices used for transmitting / connecting power and signals invarious fields like consumer
goods, home appliances, communication devices,vehicles, aircraft, marinas etc. These connectors are
essential for the functioning of much electronic equipment. A "connector" transmits electrical power and/or
electronic signals betweentwo devices. It provides the vital link between electrical components with
speed,efficiency and reliability. Connectors are normally produced in masswith many variants depending on
the customer requirement. In fact, it is avolume game, where product cost and its margins will be low, but,
volumes are high. Most of the time,the process is manual, where group of people have to sharethe activities
and should perform the process to obtain a connector.
Connector basically consists of a plastic part that will act as insulator called‘Housing’; metal part which will
connect or transmit power / signal called‘Terminals’. Housing and terminals are made in machines, but,
assemblingthese two parts will be a core activity where more of human intervention is required, which is
called as an ‘Assembly’. This is one of the important areas where an improvement was needed.Ultra High
Density (UHD)connectors is a flexible and upgradeable connector system designed to fit 15 mm (0.6 inch)
slot pitch applications and above. The UHD connector has an extremely high contact density combined with
excellent high-speed signal performance. The UHD connectors are produced using a stitching process. The
production line that is concentrated is the one that makes UHD slim connectors for various customers. The
company relies on 100% manual inspection in UHD connectors.
UHD stitching Process:In this process, the Chiclets is inserted into the housing. This is a completely
automated process and works with a high productivity rate. It takes 15 sec/connector.Continued research and
closelymonitored trials have enabled to make this process an automated one.The stitching process at present
managed by 2 operators and the chiclets feeding,lubrication, bridge-cutting (punch out of mould), carrier
separation, pre-insertion, toplocking,side-locking, laser date coding all in one automated process. The
production line for UHD connectors is optimizedby drastically reducing inspection and testing costs in the
long run.
The following are the major processes involved in the production process of UHD connectors. The flow
process for UHD Connector is shown in the Fig. 1 below.
UHD Stitching
Process

Short Circuit
Testing

Flow of
Current

Visual Inspection

Gap between
Chicklets

Go-Gauge
Inspection

Final Check before
packing

Bent Pins

Housing damage

Extra material

Housing crack

Molding defects

Dust or oil
Fig. 1:Existing UHD stitching process

88

Packing
i.

Short Circuit Testing: A short circuit (sometimes abbreviated as s/c) is an electrical circuit that allows a
current to travel along an intended path, often where essentially no or a very low electrical impedance is
encountered. The electrical opposite of a short circuit is an open circuit, which is an infinite resistance
between two nodes.Short circuit testing is done as the next process. The connectors are loaded into a tray
that can fit 121 female connectors. When this tray is full, it is transported for short-circuit testing. Only 1
operator is available per batch of 121 connectors.
ii. Visual Inspection: Visual inspection is a process whereby an operator with the help of his/her eyes, with
or without the use of visual aid, inspects a component or product for defects, flaws or abnormalities.
iii. Go-Gauge Inspection: A Go-No Go gauge refers to an inspection tool used to check a work piece against
its allowed tolerances. Its name derives from its use: the gauge has two tests; the check involves the
work piece having to pass one test (Go) and fail the other (No Go).
iv. Packing: The packing is done in polyurethane trays; it is the final step that is undertaken in the facility
before it is shipped out of the facility to the customers. The operator first puts each individual female
connector into jackets provided on the tray. The tray is then covered with one sheet of clear plastic for
every row on the tray. For the female connector, each tray consists of 50 pieces. One box that is shipped
to the customer consists of 5 such trays. Therefore, one box/carton consists of 250 female connectors.
The box is then sealed and shipped.
III. METHODOLOGY OF STUDY
Based on historical data for this type of production, it has been observed that typically labour cost involved in
inspection and testing represents as much as 15% of the total manufacturing cost. Since recently the company
has created an automated UHD stitching machine for the assembly of the UHD connectors observed that the
processes after the assembly process was noticed as being thebottle necks. To analyse this, following
methodology has been adopted for study:
A. Data Collection
The following data collection for numerical computation was done in the following processes:
 Visual Inspection: Visual inspection is a process wherebyan operator with the help of his/her eyes, with or
without the use of visual aid, inspects a component or product for defects, flaws or abnormalities. Table 1
show the time study carried out to know details of each connector being inspected. Table 1 shows the data
gathered by observing 3 inspectors inspecting 20components at a stretch. The time is then averaged to
obtain the time taken to inspect one of such component. This process was repeated 10 times for each of the
threeinspectors. The readings were observed for the same inspector, once inthe morning and once in the
afternoon. The subtle increase in time taken to inspect inthe afternoon is clearly noticed. The overall time
taken per piece was 47.78 sec/piece.
TABLE I: TIME STUDY FOR VISUAL INSPECTION
Days
1
2
3
4
5
6
7
8
9
10

FEMALE PART VISUAL INSPECTION (Average of 20 pieces inspected in seconds)
Operator
Morning
Afternoon
Operator
Morning
Afternoon
Operator
Morning
1
33.2
37.2
2
53.9
59.2
3
43.1
1
34.4
35.7
2
57.3
55
3
45.1
1
38.2
34.4
2
53.1
56.9
3
45.8
1
31.9
40.6
2
58.3
56.4
3
43.1
1
38.6
36.2
2
61.2
61.2
3
51.3
1
33.1
41.1
2
52.4
59.4
3
47.2
1
37.7
43.2
2
58.1
63.1
3
48.8
1
40.1
41.7
2
55.5
55.9
3
49.1
1
43.5
36.6
2
55.2
57.4
3
45.3
1
34
43.5
2
60.3
60.1
3
49
Time taken for 400
754.9s
1149.9s
pieces
Avg time taken/ piece 37.75s/piece
Avg time taken/piece 57.5 /piece
Avg time taken/ iece
Overall time taken per piece

Afternoon
47.7
48.1
46.2
45.5
49.3
53.8
50.3
53.1
48.1
52.1
962s
48.1 s/piece
47.78s/piece

 Go-Gauge Inspection: To gauge how long an operator requires to do a go-gauge for one component, the
time for 100 components was obtained by observing first. It was done for a 2 week period, in which time
for 2000 component’s go-gauge testing was obtained as shown in Table 2. The operator first waits for the
89
full tray (121 components) to be acquired to his station. After which he/she picks up one component at a
time from the tray and tests it using the go-gauge tester resting on the surface of the workstation.From the
Table 3.2, the go gauge total inspection in the morning for 2000pieces was found to be 5722sec and the
average for 100pieces was found to be 286.1sec. Similarly, in the evening, for 2000pieces, the total
inspection time was 5817sec and theaverage for 100pieces was found to be 290.8sec.
TABLE II: E XISTING GO-GAUGE TIME STUDY
Morning

290

289

279

300

298

269

277

278

298

294
Gauge
Testing.
2 week 100
components Afternoon
in sec

280

276

291

287

268

298

287

297

278

288

296
299

Total Morning inspection for 2000 pieces: 5722 s
Average Morning/100 pieces: 286.1 s
305
279
289
283
285
302
312
296
288
277

285
280

297
291

299
295

269
290

Total Evening inspection for 2000 pieces: 5817 s
Average Evening/100 pieced: 290.8 s

B.Data Analysis
After consolidation of the data of inspection process, a brainstorming session was organised among the team
members. The output of the brainstorming session revealed that some of the process in inspection to be revisited and swapped for effectiveness and reduction in inspection time.The following Fig. 2 shows the
revised UHD Stitching process.
UHD Stitching
Process

Go Gauge
Testing

Short Circuit
Testing

Gap between
Chiclets

Visual Inspection

Flow of
Current

Packing

Housing crack

Molding
defects in
housing

Bent Pins

Housing
damage

Dust or oil

Extra material

Fig. 2: Proposed UHD Stitching Process

The UHD Stitching processwas carried out, as earlier. There was no change in thisprocedure, as it is an
automated process. The changes in the go gauge insection were done in the revised process using time study
again. The UHD stitcher produces a batch of 3 connectors. Each connector takes 15 sec to bemade and
therefore a batch of 3 connectors takes 45 sec. The operator collects these connectors and was idle for until
next batch of 3 connectorsare produced (for 45 sec). So assoon as a batch of 3 UHD connectors come out of
the stitching machine, the operatorcollects the parts from the stitching process and test them using a gogauge.The proposed method eliminated the idle time that previously existed in the system and alsoeliminated
time for movement and collections of the parts. The Table 3 below shows the Go gauge testing times for
proposed method.
Although the time for go-gauge testing is not dramatically reduced as shown in Table 3.3, it doeseliminate
the idle time during WIP of the connectors being produced in the UHDstitcher. More importantly, because
the go-gauge testing is re-oriented to happenbefore the visual inspection, the time for visual inspection is cut
by half. The average morning inspection time for 100 pieceswas found to be 285.2 sec and average evening
inspection time for 100 pieces was found to be 289.8 sec. The short circuit testing was carried out, as it was
earlier. There was no change in this procedure.
Table 4 shows the performance rating was done for workers doing the fully manual visual inspection process.
The performance rating was done solelybased on speed and paceof the workers.
90
TABLE III: PROPOSED GO-GAUGE TIME STUDY
Morning

280 290 289 279 310 298 269 277 278

298

294 280 296 287 268 298 287 297 278

288
Gauge
Total Morning inspection for 2000 pieces: 5704 s
Testing.
Average Morning/100 pieces: 285.2 s
2 week 100
components Afternoon 290 297 299 269 296 310 279 289 289 290
280 291 295 290 299 302 312 296 288 277
in sec
Total Evening inspection for 2000 pieces: 5796 s
Average Evening/100 pieced: 289.8 s

The analysis was done for 20 inspections. Based on observations and averages, and company’s own standard
for inspection, the conclusion was that, for a female connector, the standard rating that is considered to be
100% is 48 seconds/piece. As depicted in the table 3.3, the Inspector 1 takes an average of 37.75 sec/piece
and therefore his performance rating is more than 100.Using the formula 1+ {(|Standard Time– Actual
Time|)/Actual Time} for when actual time is smaller than standard time, then, performance rating is
127.2.Inspector 2 takes an average of 57.5 sec/piece and his performance rating is 83.34 and is less than 100.
Inspector 3 takes an average of 48.1 sec/piece and his performance rating is 99.7 which isclose to 100. As the
go-gauge inspection happens earlier and it eliminates 3 defect parameters, there was a drastic change in the
visual inspection time. Earlier the inspector would look for 6 defect parameters to be inspected for, in the
process. In the proposed system, the person can look for only 3 defect parameters as the other three were
eliminated in the go-gauge inspection. This reduces the time for inspection.
TABLE IV: PERFORMANCE RATING OF INSPECTORS
Inspector 1
Morning
Afternoon
33.2
37.2
34.4
35.7
38.2
34.4
31.9
40.6
38.6
36.2
33.1
41.1
37.7
43.2
40.1
41.7
43.5
36.6
34
43.5
Average=37.75s/piece
Performance rating = 127.2

Inspector 2
Morning
Afternoon
53.9
59.2
57.3
55
53.1
56.9
58.3
56.4
61.2
61.2
52.4
59.4
58.1
63.1
55.5
55.9
55.2
57.4
60.3
60.1
Average=57.5s/piece
Performance rating = 83.34

Inspector 3
Morning
Afternoon
43.1
47.7
45.1
48.1
45.8
46.2
43.1
45.5
51.3
49.3
47.2
53.8
48.8
50.3
49.1
53.1
45.3
48.1
49
52.1
Average=48.1s/piece
Performance rating = 99.7

The table 5 shows the results of the time study for proposed visual inspection, where the overall time
taken/piece is24.25s/piece. This shows an improvement 49.24% in the visual inspection process. The
Packagingprocess was carried out, as earlier.
TABLE V: TIME STUDY FOR PROPOSED VISUAL INSPECTION
FEMALE PART VISUAL INSPECTION (average of 20 pieces inspected in seconds)
Days
Operator
Morning
Afternoon
Operator
Morning
Afternoon
Operator
Morning
1
1
22
21
2
28
28
3
25
2
1
21
18
2
29
29
3
26
3
1
24
19
2
25
24
3
24
4
1
20
20
2
27
28
3
27
5
1
18
21
2
24
27
3
28
6
1
19
25
2
28
30
3
25
7
1
17
22
2
27
25
3
24
8
1
22
22
2
26
29
3
25
9
1
21
27
2
24
28
3
26
10
1
20
17
2
26
34
3
24
Time taken for 400 pieces -Total
416s
Total
546s
Total
Avg time taken/ piece 20.8s/piece
Avg time taken/ piece
27.5
Avg time taken/ piece
s/piece
Overall time taken per piece

91

Afternoon
23
21
26
25
27
22
28
27
21
19
493s
24.65
s/piece
24.25s/piece
IV. SUMMARY OF RESULTS
The analysis of the study revealed that the proposed system of inspection would yield better results and
enhance productivity. The inspection process included the microscopic visual inspection; short-circuit testing
and go-gauge inspection. The visual inspection was observed to take an average of 46.59 s per connector in
the morning (this average was an average of 3 different inspectors). It was observed that this inspection time
increased to an average of 48.96 per piece in the afternoon. The average inspection time was observed to be
47.78/piece. The go gauge testing was done for the pins on top of the chiclets. On an average, go gauge
testing time for female connectors was found to be 2.89 s/piece. With the help of time study, method study
using process mapping, a process re-orientation and re-organization was done. This re-orientation resulted in
a reduction in time for inspection and testing of the connectors.
V. CONCLUSION
The Fig 3 shows comparison of results of present and proposed method of inspection process which reduced
from an average total time of 112.59sec to 86.15sec.

Fig. 3: Comparison of results

Although the go-gauge inspection did not reduce in time, the re-orientation of the go-gauge testing before the
visual inspection, gave the overall improvement which increased from 56% to 79.5%.
ACKNOWLEDGEMENT
This paper is based on the study by a 2013 batch of final year students of department of Industrial
Engineering and & Management, R V College of Engineering, Bangalore. The authors thank Mr.Ameet
Kumar Bumb, Mr.Karan Khanna, Mr.RupinSurana, Mr.SwaraajPrabhusankarfor their effort in the study.
REFERENCES
[1] K. Sundaraj “PCB Inspection for Missing or Misaligned Components using Background Subtraction”, University
Malaysia Perlis School of Mechatronic Engineering 02600 Jejawi – Perlis, MALAYSIA volume 6, No. 5, May
2009.
[2] Robert Sablatnig “A Flexible concept for Automatic Visual Inspection”, Technical University Vienna, Institute of
Automation, Pattern Recognition and Image Processing Group Treitlstr. 3 / 183-2, A-1040 Vienna, Austria, year
1997.
[3] Khalid S Al-Saleh “Productivity Improvement of a Motor Vehicle Inspection Station Using Motion And Time Study
Techniques” Journal of King Saud University - Engineering Sciences, vol 23, no. 1, pp- 33–41, January 2011.
[4] Rathel R. (Dick) Smith, Steven, W. McCrary and R. Neal Callahan “Gauge Repeatability and Reproducibility
Studies and Measurement System Analysis: A Multi method Exploration of the State of Practice” vol 23, No.1,
January 2007 through March 2007.
[5] Louis Johnson “Breakthrough Improvement for Your Inspection Process”. Six Sigma Forum - American Society for
Quality, May 2007.
[6] A.M Darwish, A.K Jain, “A rule-based approach for visual pattern inspection”, IEEE Trans. Pattern
Anal.MachIntell. Vol.10, No.1.pp56-58, 1988.
[7] T.S Newman, A.k.Jain “A Survey of Automated visual inspection” Comput. Vision Graphics, Image Processing.
Vol 61 No.2 pp 231-262, 1995.

92

Contenu connexe

Tendances

Catalogo general general electric geit 10012 en-rev6_final
Catalogo general general electric geit 10012 en-rev6_finalCatalogo general general electric geit 10012 en-rev6_final
Catalogo general general electric geit 10012 en-rev6_final
Pablo Bavarisco
 
Psylotech Final Paper
Psylotech Final PaperPsylotech Final Paper
Psylotech Final Paper
Joycelyn Dong
 
Itab innovative assessement tool
Itab innovative assessement toolItab innovative assessement tool
Itab innovative assessement tool
Martin J Ippel
 

Tendances (9)

Inline Quality Inspection Chechup – Optimierung von Produktionsprozessen mit ...
Inline Quality Inspection Chechup – Optimierung von Produktionsprozessen mit ...Inline Quality Inspection Chechup – Optimierung von Produktionsprozessen mit ...
Inline Quality Inspection Chechup – Optimierung von Produktionsprozessen mit ...
 
Catalogo general general electric geit 10012 en-rev6_final
Catalogo general general electric geit 10012 en-rev6_finalCatalogo general general electric geit 10012 en-rev6_final
Catalogo general general electric geit 10012 en-rev6_final
 
Regulatory and Quality Affairs: Answers to FDA and ISO Gray Areas
Regulatory and Quality Affairs: Answers to FDA and ISO Gray AreasRegulatory and Quality Affairs: Answers to FDA and ISO Gray Areas
Regulatory and Quality Affairs: Answers to FDA and ISO Gray Areas
 
What is the IPC-JSTD-001 Certification Program
What is the IPC-JSTD-001 Certification ProgramWhat is the IPC-JSTD-001 Certification Program
What is the IPC-JSTD-001 Certification Program
 
J-STD-001, IPC A-610 F to G Differences Webinar
J-STD-001, IPC A-610 F to G Differences WebinarJ-STD-001, IPC A-610 F to G Differences Webinar
J-STD-001, IPC A-610 F to G Differences Webinar
 
Psylotech Final Paper
Psylotech Final PaperPsylotech Final Paper
Psylotech Final Paper
 
Case study of dcs upgrade how to reduce stress during execution
Case study of dcs upgrade how to reduce stress during executionCase study of dcs upgrade how to reduce stress during execution
Case study of dcs upgrade how to reduce stress during execution
 
Cpsia
CpsiaCpsia
Cpsia
 
Itab innovative assessement tool
Itab innovative assessement toolItab innovative assessement tool
Itab innovative assessement tool
 

Similaire à Productivity Studies of Ultra High Density (UHD) Stitching Process

ADVANTAGES AND LIMITATION OF AN AUTOMATED VISUAL INSPECTION SYSTEM
ADVANTAGES AND LIMITATION OF AN AUTOMATED VISUAL INSPECTION SYSTEMADVANTAGES AND LIMITATION OF AN AUTOMATED VISUAL INSPECTION SYSTEM
ADVANTAGES AND LIMITATION OF AN AUTOMATED VISUAL INSPECTION SYSTEM
anil badiger
 
Whitepaper fluke
Whitepaper flukeWhitepaper fluke
Whitepaper fluke
Clair Kirby
 
Introduction To manage electronics they must be monitored.pdf
Introduction To manage electronics they must be monitored.pdfIntroduction To manage electronics they must be monitored.pdf
Introduction To manage electronics they must be monitored.pdf
bkbk37
 
Project Proposal for Predictive Maintenance Power Plant
Project Proposal for Predictive Maintenance Power PlantProject Proposal for Predictive Maintenance Power Plant
Project Proposal for Predictive Maintenance Power Plant
Ferdous Kabir
 

Similaire à Productivity Studies of Ultra High Density (UHD) Stitching Process (20)

ADVANTAGES AND LIMITATION OF AN AUTOMATED VISUAL INSPECTION SYSTEM
ADVANTAGES AND LIMITATION OF AN AUTOMATED VISUAL INSPECTION SYSTEMADVANTAGES AND LIMITATION OF AN AUTOMATED VISUAL INSPECTION SYSTEM
ADVANTAGES AND LIMITATION OF AN AUTOMATED VISUAL INSPECTION SYSTEM
 
Whitepaper fluke
Whitepaper flukeWhitepaper fluke
Whitepaper fluke
 
Implementation of Customised SCADA for Cartoner Packaging machine for Cost Ef...
Implementation of Customised SCADA for Cartoner Packaging machine for Cost Ef...Implementation of Customised SCADA for Cartoner Packaging machine for Cost Ef...
Implementation of Customised SCADA for Cartoner Packaging machine for Cost Ef...
 
Formal Verification Of An Intellectual Property In a Field Programmable Gate ...
Formal Verification Of An Intellectual Property In a Field Programmable Gate ...Formal Verification Of An Intellectual Property In a Field Programmable Gate ...
Formal Verification Of An Intellectual Property In a Field Programmable Gate ...
 
Introduction To manage electronics they must be monitored.pdf
Introduction To manage electronics they must be monitored.pdfIntroduction To manage electronics they must be monitored.pdf
Introduction To manage electronics they must be monitored.pdf
 
KD4010 Magnetism And Electronics.docx
KD4010 Magnetism And Electronics.docxKD4010 Magnetism And Electronics.docx
KD4010 Magnetism And Electronics.docx
 
An Automated Machine Learning Approach For Smart Waste Management System
An Automated Machine Learning Approach For Smart Waste Management SystemAn Automated Machine Learning Approach For Smart Waste Management System
An Automated Machine Learning Approach For Smart Waste Management System
 
Innovating Quality Control in the Semiconductor Manufacturing Industry.pptx
Innovating Quality Control in the Semiconductor Manufacturing Industry.pptxInnovating Quality Control in the Semiconductor Manufacturing Industry.pptx
Innovating Quality Control in the Semiconductor Manufacturing Industry.pptx
 
“Development of automatic feeder system in cellular manufacturing to improve ...
“Development of automatic feeder system in cellular manufacturing to improve ...“Development of automatic feeder system in cellular manufacturing to improve ...
“Development of automatic feeder system in cellular manufacturing to improve ...
 
Advanced Verification Methodology for Complex System on Chip Verification
Advanced Verification Methodology for Complex System on Chip VerificationAdvanced Verification Methodology for Complex System on Chip Verification
Advanced Verification Methodology for Complex System on Chip Verification
 
61 programmable
61 programmable61 programmable
61 programmable
 
Controlling interests editors
Controlling interests editorsControlling interests editors
Controlling interests editors
 
Development of PLC based Transdermal Patch Evaluation System
Development of PLC based Transdermal Patch Evaluation SystemDevelopment of PLC based Transdermal Patch Evaluation System
Development of PLC based Transdermal Patch Evaluation System
 
Monitoring and Visualisation Approach for Collaboration Production Line Envir...
Monitoring and Visualisation Approach for Collaboration Production Line Envir...Monitoring and Visualisation Approach for Collaboration Production Line Envir...
Monitoring and Visualisation Approach for Collaboration Production Line Envir...
 
An Introduction to Technical Cleanliness Inspection
An Introduction to Technical Cleanliness InspectionAn Introduction to Technical Cleanliness Inspection
An Introduction to Technical Cleanliness Inspection
 
IRJET- Smart IoT based Bridge Monitoring and Damage Detection using Android App
IRJET- Smart IoT based Bridge Monitoring and Damage Detection using Android AppIRJET- Smart IoT based Bridge Monitoring and Damage Detection using Android App
IRJET- Smart IoT based Bridge Monitoring and Damage Detection using Android App
 
A Survey on Batch Auditing Systems for Cloud Storage
A Survey on Batch Auditing Systems for Cloud StorageA Survey on Batch Auditing Systems for Cloud Storage
A Survey on Batch Auditing Systems for Cloud Storage
 
UVM ARCHITECTURE FOR VERIFICATION
UVM ARCHITECTURE FOR VERIFICATIONUVM ARCHITECTURE FOR VERIFICATION
UVM ARCHITECTURE FOR VERIFICATION
 
Project Proposal for Predictive Maintenance Power Plant
Project Proposal for Predictive Maintenance Power PlantProject Proposal for Predictive Maintenance Power Plant
Project Proposal for Predictive Maintenance Power Plant
 
Automated-test-equipment-Blog-Digilogic Systems
Automated-test-equipment-Blog-Digilogic SystemsAutomated-test-equipment-Blog-Digilogic Systems
Automated-test-equipment-Blog-Digilogic Systems
 

Plus de idescitation

65 113-121
65 113-12165 113-121
65 113-121
idescitation
 
74 136-143
74 136-14374 136-143
74 136-143
idescitation
 
84 11-21
84 11-2184 11-21
84 11-21
idescitation
 
29 88-96
29 88-9629 88-96
29 88-96
idescitation
 

Plus de idescitation (20)

65 113-121
65 113-12165 113-121
65 113-121
 
69 122-128
69 122-12869 122-128
69 122-128
 
71 338-347
71 338-34771 338-347
71 338-347
 
72 129-135
72 129-13572 129-135
72 129-135
 
74 136-143
74 136-14374 136-143
74 136-143
 
80 152-157
80 152-15780 152-157
80 152-157
 
82 348-355
82 348-35582 348-355
82 348-355
 
84 11-21
84 11-2184 11-21
84 11-21
 
62 328-337
62 328-33762 328-337
62 328-337
 
46 102-112
46 102-11246 102-112
46 102-112
 
47 292-298
47 292-29847 292-298
47 292-298
 
49 299-305
49 299-30549 299-305
49 299-305
 
57 306-311
57 306-31157 306-311
57 306-311
 
60 312-318
60 312-31860 312-318
60 312-318
 
5 1-10
5 1-105 1-10
5 1-10
 
11 69-81
11 69-8111 69-81
11 69-81
 
14 284-291
14 284-29114 284-291
14 284-291
 
15 82-87
15 82-8715 82-87
15 82-87
 
29 88-96
29 88-9629 88-96
29 88-96
 
43 97-101
43 97-10143 97-101
43 97-101
 

Dernier

Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Krashi Coaching
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
QucHHunhnh
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptx
heathfieldcps1
 
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
fonyou31
 

Dernier (20)

Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104
 
General AI for Medical Educators April 2024
General AI for Medical Educators April 2024General AI for Medical Educators April 2024
General AI for Medical Educators April 2024
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13
 
APM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAPM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across Sectors
 
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptxINDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impact
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptx
 
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdf
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17
 
Advance Mobile Application Development class 07
Advance Mobile Application Development class 07Advance Mobile Application Development class 07
Advance Mobile Application Development class 07
 
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
 
fourth grading exam for kindergarten in writing
fourth grading exam for kindergarten in writingfourth grading exam for kindergarten in writing
fourth grading exam for kindergarten in writing
 

Productivity Studies of Ultra High Density (UHD) Stitching Process

  • 1. Proc. of Int. Conf. on Advances in Mechanical Engineering, AETAME Productivity Studies of Ultra High Density (UHD) Stitching Process M.N Shruthi1, M.N VijayKumar2, Dr. K.N Subramanya3 1 R V College of Engineering, Department of Industrial Engineering and Management, Bangalore, Karnataka, India Email: shruthimn@rvce.edu.in Email: vijayakumar@rvce.edu.in /subramanyakn@rvce.edu.in Abstract—This paper focuses on Ultra High Density (UHD) stitching process of connectors, where the company relies on 100% manual inspection in UHD connectors. Based on historical data on production of UHD connectors, typically labour cost involved in inspection and testing is around 15% of the total manufacturing cost. This poses both challenges and opportunities for improvement in the bottleneck process, which is the inspection process. The female connectors quantity produced is on the average of 2000 parts/shift. It takes around 47 sec of visual inspection per connector and around 2.89 sec per piece for go-gauge inspection. Considering these factors, the objectives of the study was to understand the whole process in its entirety and then use this knowledge to re-organize the stages staring from the automatic stitching process. By using process improvement tools of time study, methods and process mapping, a process re-orientation and re-organization has been carried out. This resulted in not only reduction of time of inspection and testing of the connectors, but also the piece inspection process reduced from an average total time of 112.59 sec to 86.15 sec. Overall improvement was also increased from 56% to 79.5%. Index Terms—Process Mapping, Process Re-engineering, Ultra High Density. I. INTRODUCTION With emerging global competition and rising customer expectation, providing lowcost and high quality products is a winning mantra in the current business scenario.These high expectations can be met through low cost automation and by keeping lowoperational cost [1]. An automated visual inspection is one way for detecting all visual defects in a high volume manufacturing industry [2]. Colour image processing can be used for detecting the missing components or misaligned components. This can also be used for the visual inspection that results in high false call rate, which then leads to use background subtraction to identify defects. This feasibility decreases the setup costs by taking into account different types of data positioning, occlusions andtolerances [3]. New techniques have been proposed to reduce theinspection time using timemotion study.The paper illustrates the process ofinspection carried out in UHD connector [4]. Itwas found that by carrying out time and method study results in overall improvement of the process. Attribute agreement analysis can also be used to determine the inconsistencies of the defects in visual inspection of pass/fail decisions which can be identified and solve the main causes of poor inspection performance [5].The use of a priori knowledge about a scene to coordinate and control bi-level image segmentation, interpretation, and shape inspection of different objects in the scene. The approach is composed of two main steps. The first step consists of proper segmentation and labelling of individual regions in the image for subsequent ease in interpretation [6]. The common approaches to visual inspection, to consider the specification and analysis of DOI: 02.AETAME.2013.4.38 © Association of Mechanical and Aeronautical Engineers, 2013
  • 2. dimensional tolerances and theirinfluence on the inspection task. Recent developments in automated visual inspection, is the expanded role of computer-aided design (CAD) data in many systems [7]. II. PROCESS STUDY AND MAPPING OF UHD STITCHING PROCESS Connectors are devices used for transmitting / connecting power and signals invarious fields like consumer goods, home appliances, communication devices,vehicles, aircraft, marinas etc. These connectors are essential for the functioning of much electronic equipment. A "connector" transmits electrical power and/or electronic signals betweentwo devices. It provides the vital link between electrical components with speed,efficiency and reliability. Connectors are normally produced in masswith many variants depending on the customer requirement. In fact, it is avolume game, where product cost and its margins will be low, but, volumes are high. Most of the time,the process is manual, where group of people have to sharethe activities and should perform the process to obtain a connector. Connector basically consists of a plastic part that will act as insulator called‘Housing’; metal part which will connect or transmit power / signal called‘Terminals’. Housing and terminals are made in machines, but, assemblingthese two parts will be a core activity where more of human intervention is required, which is called as an ‘Assembly’. This is one of the important areas where an improvement was needed.Ultra High Density (UHD)connectors is a flexible and upgradeable connector system designed to fit 15 mm (0.6 inch) slot pitch applications and above. The UHD connector has an extremely high contact density combined with excellent high-speed signal performance. The UHD connectors are produced using a stitching process. The production line that is concentrated is the one that makes UHD slim connectors for various customers. The company relies on 100% manual inspection in UHD connectors. UHD stitching Process:In this process, the Chiclets is inserted into the housing. This is a completely automated process and works with a high productivity rate. It takes 15 sec/connector.Continued research and closelymonitored trials have enabled to make this process an automated one.The stitching process at present managed by 2 operators and the chiclets feeding,lubrication, bridge-cutting (punch out of mould), carrier separation, pre-insertion, toplocking,side-locking, laser date coding all in one automated process. The production line for UHD connectors is optimizedby drastically reducing inspection and testing costs in the long run. The following are the major processes involved in the production process of UHD connectors. The flow process for UHD Connector is shown in the Fig. 1 below. UHD Stitching Process Short Circuit Testing Flow of Current Visual Inspection Gap between Chicklets Go-Gauge Inspection Final Check before packing Bent Pins Housing damage Extra material Housing crack Molding defects Dust or oil Fig. 1:Existing UHD stitching process 88 Packing
  • 3. i. Short Circuit Testing: A short circuit (sometimes abbreviated as s/c) is an electrical circuit that allows a current to travel along an intended path, often where essentially no or a very low electrical impedance is encountered. The electrical opposite of a short circuit is an open circuit, which is an infinite resistance between two nodes.Short circuit testing is done as the next process. The connectors are loaded into a tray that can fit 121 female connectors. When this tray is full, it is transported for short-circuit testing. Only 1 operator is available per batch of 121 connectors. ii. Visual Inspection: Visual inspection is a process whereby an operator with the help of his/her eyes, with or without the use of visual aid, inspects a component or product for defects, flaws or abnormalities. iii. Go-Gauge Inspection: A Go-No Go gauge refers to an inspection tool used to check a work piece against its allowed tolerances. Its name derives from its use: the gauge has two tests; the check involves the work piece having to pass one test (Go) and fail the other (No Go). iv. Packing: The packing is done in polyurethane trays; it is the final step that is undertaken in the facility before it is shipped out of the facility to the customers. The operator first puts each individual female connector into jackets provided on the tray. The tray is then covered with one sheet of clear plastic for every row on the tray. For the female connector, each tray consists of 50 pieces. One box that is shipped to the customer consists of 5 such trays. Therefore, one box/carton consists of 250 female connectors. The box is then sealed and shipped. III. METHODOLOGY OF STUDY Based on historical data for this type of production, it has been observed that typically labour cost involved in inspection and testing represents as much as 15% of the total manufacturing cost. Since recently the company has created an automated UHD stitching machine for the assembly of the UHD connectors observed that the processes after the assembly process was noticed as being thebottle necks. To analyse this, following methodology has been adopted for study: A. Data Collection The following data collection for numerical computation was done in the following processes:  Visual Inspection: Visual inspection is a process wherebyan operator with the help of his/her eyes, with or without the use of visual aid, inspects a component or product for defects, flaws or abnormalities. Table 1 show the time study carried out to know details of each connector being inspected. Table 1 shows the data gathered by observing 3 inspectors inspecting 20components at a stretch. The time is then averaged to obtain the time taken to inspect one of such component. This process was repeated 10 times for each of the threeinspectors. The readings were observed for the same inspector, once inthe morning and once in the afternoon. The subtle increase in time taken to inspect inthe afternoon is clearly noticed. The overall time taken per piece was 47.78 sec/piece. TABLE I: TIME STUDY FOR VISUAL INSPECTION Days 1 2 3 4 5 6 7 8 9 10 FEMALE PART VISUAL INSPECTION (Average of 20 pieces inspected in seconds) Operator Morning Afternoon Operator Morning Afternoon Operator Morning 1 33.2 37.2 2 53.9 59.2 3 43.1 1 34.4 35.7 2 57.3 55 3 45.1 1 38.2 34.4 2 53.1 56.9 3 45.8 1 31.9 40.6 2 58.3 56.4 3 43.1 1 38.6 36.2 2 61.2 61.2 3 51.3 1 33.1 41.1 2 52.4 59.4 3 47.2 1 37.7 43.2 2 58.1 63.1 3 48.8 1 40.1 41.7 2 55.5 55.9 3 49.1 1 43.5 36.6 2 55.2 57.4 3 45.3 1 34 43.5 2 60.3 60.1 3 49 Time taken for 400 754.9s 1149.9s pieces Avg time taken/ piece 37.75s/piece Avg time taken/piece 57.5 /piece Avg time taken/ iece Overall time taken per piece Afternoon 47.7 48.1 46.2 45.5 49.3 53.8 50.3 53.1 48.1 52.1 962s 48.1 s/piece 47.78s/piece  Go-Gauge Inspection: To gauge how long an operator requires to do a go-gauge for one component, the time for 100 components was obtained by observing first. It was done for a 2 week period, in which time for 2000 component’s go-gauge testing was obtained as shown in Table 2. The operator first waits for the 89
  • 4. full tray (121 components) to be acquired to his station. After which he/she picks up one component at a time from the tray and tests it using the go-gauge tester resting on the surface of the workstation.From the Table 3.2, the go gauge total inspection in the morning for 2000pieces was found to be 5722sec and the average for 100pieces was found to be 286.1sec. Similarly, in the evening, for 2000pieces, the total inspection time was 5817sec and theaverage for 100pieces was found to be 290.8sec. TABLE II: E XISTING GO-GAUGE TIME STUDY Morning 290 289 279 300 298 269 277 278 298 294 Gauge Testing. 2 week 100 components Afternoon in sec 280 276 291 287 268 298 287 297 278 288 296 299 Total Morning inspection for 2000 pieces: 5722 s Average Morning/100 pieces: 286.1 s 305 279 289 283 285 302 312 296 288 277 285 280 297 291 299 295 269 290 Total Evening inspection for 2000 pieces: 5817 s Average Evening/100 pieced: 290.8 s B.Data Analysis After consolidation of the data of inspection process, a brainstorming session was organised among the team members. The output of the brainstorming session revealed that some of the process in inspection to be revisited and swapped for effectiveness and reduction in inspection time.The following Fig. 2 shows the revised UHD Stitching process. UHD Stitching Process Go Gauge Testing Short Circuit Testing Gap between Chiclets Visual Inspection Flow of Current Packing Housing crack Molding defects in housing Bent Pins Housing damage Dust or oil Extra material Fig. 2: Proposed UHD Stitching Process The UHD Stitching processwas carried out, as earlier. There was no change in thisprocedure, as it is an automated process. The changes in the go gauge insection were done in the revised process using time study again. The UHD stitcher produces a batch of 3 connectors. Each connector takes 15 sec to bemade and therefore a batch of 3 connectors takes 45 sec. The operator collects these connectors and was idle for until next batch of 3 connectorsare produced (for 45 sec). So assoon as a batch of 3 UHD connectors come out of the stitching machine, the operatorcollects the parts from the stitching process and test them using a gogauge.The proposed method eliminated the idle time that previously existed in the system and alsoeliminated time for movement and collections of the parts. The Table 3 below shows the Go gauge testing times for proposed method. Although the time for go-gauge testing is not dramatically reduced as shown in Table 3.3, it doeseliminate the idle time during WIP of the connectors being produced in the UHDstitcher. More importantly, because the go-gauge testing is re-oriented to happenbefore the visual inspection, the time for visual inspection is cut by half. The average morning inspection time for 100 pieceswas found to be 285.2 sec and average evening inspection time for 100 pieces was found to be 289.8 sec. The short circuit testing was carried out, as it was earlier. There was no change in this procedure. Table 4 shows the performance rating was done for workers doing the fully manual visual inspection process. The performance rating was done solelybased on speed and paceof the workers. 90
  • 5. TABLE III: PROPOSED GO-GAUGE TIME STUDY Morning 280 290 289 279 310 298 269 277 278 298 294 280 296 287 268 298 287 297 278 288 Gauge Total Morning inspection for 2000 pieces: 5704 s Testing. Average Morning/100 pieces: 285.2 s 2 week 100 components Afternoon 290 297 299 269 296 310 279 289 289 290 280 291 295 290 299 302 312 296 288 277 in sec Total Evening inspection for 2000 pieces: 5796 s Average Evening/100 pieced: 289.8 s The analysis was done for 20 inspections. Based on observations and averages, and company’s own standard for inspection, the conclusion was that, for a female connector, the standard rating that is considered to be 100% is 48 seconds/piece. As depicted in the table 3.3, the Inspector 1 takes an average of 37.75 sec/piece and therefore his performance rating is more than 100.Using the formula 1+ {(|Standard Time– Actual Time|)/Actual Time} for when actual time is smaller than standard time, then, performance rating is 127.2.Inspector 2 takes an average of 57.5 sec/piece and his performance rating is 83.34 and is less than 100. Inspector 3 takes an average of 48.1 sec/piece and his performance rating is 99.7 which isclose to 100. As the go-gauge inspection happens earlier and it eliminates 3 defect parameters, there was a drastic change in the visual inspection time. Earlier the inspector would look for 6 defect parameters to be inspected for, in the process. In the proposed system, the person can look for only 3 defect parameters as the other three were eliminated in the go-gauge inspection. This reduces the time for inspection. TABLE IV: PERFORMANCE RATING OF INSPECTORS Inspector 1 Morning Afternoon 33.2 37.2 34.4 35.7 38.2 34.4 31.9 40.6 38.6 36.2 33.1 41.1 37.7 43.2 40.1 41.7 43.5 36.6 34 43.5 Average=37.75s/piece Performance rating = 127.2 Inspector 2 Morning Afternoon 53.9 59.2 57.3 55 53.1 56.9 58.3 56.4 61.2 61.2 52.4 59.4 58.1 63.1 55.5 55.9 55.2 57.4 60.3 60.1 Average=57.5s/piece Performance rating = 83.34 Inspector 3 Morning Afternoon 43.1 47.7 45.1 48.1 45.8 46.2 43.1 45.5 51.3 49.3 47.2 53.8 48.8 50.3 49.1 53.1 45.3 48.1 49 52.1 Average=48.1s/piece Performance rating = 99.7 The table 5 shows the results of the time study for proposed visual inspection, where the overall time taken/piece is24.25s/piece. This shows an improvement 49.24% in the visual inspection process. The Packagingprocess was carried out, as earlier. TABLE V: TIME STUDY FOR PROPOSED VISUAL INSPECTION FEMALE PART VISUAL INSPECTION (average of 20 pieces inspected in seconds) Days Operator Morning Afternoon Operator Morning Afternoon Operator Morning 1 1 22 21 2 28 28 3 25 2 1 21 18 2 29 29 3 26 3 1 24 19 2 25 24 3 24 4 1 20 20 2 27 28 3 27 5 1 18 21 2 24 27 3 28 6 1 19 25 2 28 30 3 25 7 1 17 22 2 27 25 3 24 8 1 22 22 2 26 29 3 25 9 1 21 27 2 24 28 3 26 10 1 20 17 2 26 34 3 24 Time taken for 400 pieces -Total 416s Total 546s Total Avg time taken/ piece 20.8s/piece Avg time taken/ piece 27.5 Avg time taken/ piece s/piece Overall time taken per piece 91 Afternoon 23 21 26 25 27 22 28 27 21 19 493s 24.65 s/piece 24.25s/piece
  • 6. IV. SUMMARY OF RESULTS The analysis of the study revealed that the proposed system of inspection would yield better results and enhance productivity. The inspection process included the microscopic visual inspection; short-circuit testing and go-gauge inspection. The visual inspection was observed to take an average of 46.59 s per connector in the morning (this average was an average of 3 different inspectors). It was observed that this inspection time increased to an average of 48.96 per piece in the afternoon. The average inspection time was observed to be 47.78/piece. The go gauge testing was done for the pins on top of the chiclets. On an average, go gauge testing time for female connectors was found to be 2.89 s/piece. With the help of time study, method study using process mapping, a process re-orientation and re-organization was done. This re-orientation resulted in a reduction in time for inspection and testing of the connectors. V. CONCLUSION The Fig 3 shows comparison of results of present and proposed method of inspection process which reduced from an average total time of 112.59sec to 86.15sec. Fig. 3: Comparison of results Although the go-gauge inspection did not reduce in time, the re-orientation of the go-gauge testing before the visual inspection, gave the overall improvement which increased from 56% to 79.5%. ACKNOWLEDGEMENT This paper is based on the study by a 2013 batch of final year students of department of Industrial Engineering and & Management, R V College of Engineering, Bangalore. The authors thank Mr.Ameet Kumar Bumb, Mr.Karan Khanna, Mr.RupinSurana, Mr.SwaraajPrabhusankarfor their effort in the study. REFERENCES [1] K. Sundaraj “PCB Inspection for Missing or Misaligned Components using Background Subtraction”, University Malaysia Perlis School of Mechatronic Engineering 02600 Jejawi – Perlis, MALAYSIA volume 6, No. 5, May 2009. [2] Robert Sablatnig “A Flexible concept for Automatic Visual Inspection”, Technical University Vienna, Institute of Automation, Pattern Recognition and Image Processing Group Treitlstr. 3 / 183-2, A-1040 Vienna, Austria, year 1997. [3] Khalid S Al-Saleh “Productivity Improvement of a Motor Vehicle Inspection Station Using Motion And Time Study Techniques” Journal of King Saud University - Engineering Sciences, vol 23, no. 1, pp- 33–41, January 2011. [4] Rathel R. (Dick) Smith, Steven, W. McCrary and R. Neal Callahan “Gauge Repeatability and Reproducibility Studies and Measurement System Analysis: A Multi method Exploration of the State of Practice” vol 23, No.1, January 2007 through March 2007. [5] Louis Johnson “Breakthrough Improvement for Your Inspection Process”. Six Sigma Forum - American Society for Quality, May 2007. [6] A.M Darwish, A.K Jain, “A rule-based approach for visual pattern inspection”, IEEE Trans. Pattern Anal.MachIntell. Vol.10, No.1.pp56-58, 1988. [7] T.S Newman, A.k.Jain “A Survey of Automated visual inspection” Comput. Vision Graphics, Image Processing. Vol 61 No.2 pp 231-262, 1995. 92