THE IMPACT OF OVERALL EQUIPMENT EFFECTIVENESS ON PT ...

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THE IMPACT OF OVERALL EQUIPMENT EFFECTIVENESS ON PT FRAMAS INDONESIA PRODUCTION LOSSES ANALYSIS Yuli Suryandari 21 Desember 2016

Abstract: OEE is one of the most popular method in evaluate production performance to have a knowledge how much production losses caused by machine and production equipment. For this purpose, PT Framas Indonesia was selected as a case study. PT Framas Indonesia produces shoes outsoles which have several components. The components depend on shoes model. Main component produced by injection machine. Injection machine effectiveness measured with OEE ratio (Overall Equipment Effectiveness). OEE ratio considers available rate, performance rate, and quality rate. PT Framas Indonesia sets different OEE target for each project, the average is 80%. After collect all information related with machine and production equipment. All data will be processed by system which provides Availability, Performance, Quality, and OEE. System also presents information about type of downtime, time wasted caused of downtime, and then a conclusion about which factor most has contribution in not effective machine and production equipment. By this OEE data, also can get information about problem that happened in production process. So, the problem can be studied then management will take an action to find the bottle neck and solve the problem. The result of this study showed that Overall Equipment Effectiveness has significant impact on the reduction of production losses.

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1.

Introduction Effectiveness is very important point in business. Production process which not effective will impact to quality, price, and delivery. A not optimal machine will produce low quality product. That low quality product will make cost of wasted material and other wasted processing cost, and in the end it will delay delivery to customer. By knowing effectiveness level, corporate can analyze how the production process run. The bottle neck of machine and equipment problem also can be known. Effectiveness measurement usually used by manufacturing company is OEE (Overall Equipment Effectiveness). Machine and Equipment ability measurement with OEE method, introduced by Seiichi Nakajima a spare part industry practitioners from Japan. In production process, not optimal production machine and equipment caused by 6 factors: 1. Breakdown, is production loses caused by stopped machine that impact to output. 2. Setup/Adjustment, is production losses caused by setup or adjustment machine and equipment setting when in case of product model change. 3. Small stop, is production loses caused by machine error or machine idle time. 4. Slow running, is production losses caused by machine and equipment run slower. 5. Production defect, is production losses because of product defect and rework. 6. Startup defect, is production losses because of product defect in startup machine. These factors classified to 3 categories of OEE measurement: Availability (Breakdown & Setup/Adjustment), Performance (Small Stop & Slow Running), Quality ( Production & Startup defect).

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2. Literature Review Overall Equipment Effectiveness (OEE) is measurement tools of performance related with availability, production process, and quality. OEE Formula: Availability x Performance x Quality Availability=( (Machine Hours-Down Time)/Machine Hours) x 100% Performance = ((Cycle time x Output) / Machine Hours) x 100 % Quality = (Good Product/Output) X 100%

Note: Cycle time is time needed to produce one item. Pomorski (1997) said, available rate measure machine and equipment maintenance in running condition. Performance rate measure how effective production machine and equipment. And quality rate measured production process effectiveness to minimize scrap, rework and yield loss A study titled “ OEE and equipment effectiveness: an evaluation” authored by A.J. de Ron and J.E. Rooda, purposed to evaluate OEE and the difference with E (Equipment). The result of study is OEE is machine and equipment effectiveness measurement together with effect of before and after machine run. It means OEE not only oversee the status of machine but also the impact of before and after when machine and other equipment run or used. Instead of E only measure the machine effectiveness. (A.J. de Ron and J.E. Rooda, 2005). In another study analyze more general topic that is TPM titled ““Improving Overall Equipment Effectiveness by Implementing Total Productive Maintenance in Auto Industry” written by Prof. A. Bangar, Hemlata Sahu, and Jagmohan Batham. The conclusion is TPM can solve 80% production issues and increase OEE. TPM not only increases production effectiveness but also organization effectiveness related with productivity, quality, cost, delivery, safety and ethics. (Prof. A. Bangar, Hemlata sahu, Jagmohan batham, 2013).

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This study is conducted to learn how much loses caused by not effectiveness production machine and equipment, and which activity has the most impact with production machine and equipment effectiveness in PT Framas Indonesia. This study purposed to explain hypothesis “Overall Equipment Effectiveness has a significant influence on production losses.” 3. Research Method Population in this study contains of all item produced in Fall Winter 2016 and Spring Summer 2017 seasons PT Framas Indonesia, start from August 2016 until November 2016. There are 29 item products in that seasons. Contains of 13 types Heelcounter (3 different machine used), 9 types of outsole, and 7 types of accessories. For each item will be calculated how many output, defect, machine hour, down time, availability, performance, quality, and other factors related with production machine and equipment effectiveness. After all data collected and examined. The next step, calculate whole OEE data. In this step we can make a conclusion how much production losses caused by not effective production machine and equipment and what is the bottle neck. 4. Result and Discussion Based on production data from Augustus 2016 until November 2016 we can get information to calculate Availability below: No

1. 2. 3.

4. 5.

6.

Product Name Heel Counter HC 05091 Engel HC 05091 FCS HN125 HC 2126 FCS AF Hybrid HC 2126 FCS HN125 HC 21391 HC 21391 FCS AF Hybrid HC 21391 FCS HN125 HC A-1004 FCS Engel HC A-1008 Engel HC A-1008 FCS AF Hybrid HC A-1008 FCS HN 125 HC A-2002 FCS AF Hybrid

Machine Hour 9.720 12.180 6.000 21.000 1.200 25.020 48.750 16.440 76.080 43.860 61.620 11.340

Time Loss

1.350 594 510 1.470 0 1.475 1.678 1.570 4.622 1.570 1.785 536

Availability

86.1% 95.1% 91.5% 93% 100% 94.1% 96.6% 90.5% 93.9% 96.4% 97.1% 95.3% 4

7.

8. 9. 10 11.

12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27.

HC A-2002 FCS HN 125 HC A-4001 HC A-4001 FCS AF Hybrid HC A-4001 FCS HN 125 HC Baseball Engel HC Baseball FCS HN 125 HC C-1002 FCS AF Hybrid HC C-1002 FCS HN 125 HC C-2002 FCS AF Hybrid HC C-2002 FCS HN 125 HC C-2004 Engel HC C-2004 FCS AF Hybrid HC C-2004 FCS HN 125 HC C-9003 Engel HC C-9003 FCS HN 125 HC F38 FCS HN 125 Outsole OS 38773 Quick Rugby SG OS 39367 Messi FG Jr OS 40504 2016 X16.3 FG OS 40834 2016 FG OS 41003 2016 P1 ACE 16.1 SG OS 41163 2016 Generic P1 AG OS 41164 2016 Generic P2/P3 AG Men OS 41165 2016 Generic P2/P3 AG Jr OS 41538 ACE17.3 FG Aksesoris Heel Cap AD-42142 Supernova Insole 11028 2012 Nitrocharge Chassis Insole 11034 2016 ACE FG/SG NB Heel Stabilizer NB Shank TPU Shore D M STRO

13.980 840 1.080 9.840 15.360 12.720 2.580 8.820 4.320 8.040 495.960 27.000 21.360 23.520 32.940 12.180

290 60 80 580 1.635 310 90 420 450 825 19.281 1.047 776 2.217 1.220 594

97.9% 92.9% 92.6% 94.1% 89.4% 97.6% 96.5% 95.2% 89.6% 89.7% 96.1% 96.1% 96.4% 90.6% 96.3% 95.1%

86.675 403.625 963.336 32.945 435.360

18.375 45.442 125.608 7.515 76.408

78.8% 88.7% 87% 77.2% 82.5%

138.590 377.375

38.476 37.473

72.7% 90.1%

228.365

31.215

86.3%

1.283.927

103.551

91.9%

130.690 21.765

9.564 4.475

92.7% 79.4%

124.360 58.455 75.610

22.347 6.971 6.695

82% 88.1% 91.1%

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28. 29.

Shoe Horn Torsion Bar AD-42142 Supernova

16.910 64.410

770 2.627

95.4% 95.9%

Information to calculate Performance, we can see in the table below: No

1. 2. 3.

4. 5.

6. 7.

8. 9. 10 11.

12.

Product Name

Heel Counter HC 05091 Engel HC 05091 FCS HN125 HC 2126 FCS AF Hybrid HC 2126 FCS HN125 HC 21391 HC 21391 FCS AF Hybrid HC 21391 FCS HN125 HC A-1004 FCS Engel HC A-1008 Engel HC A-1008 FCS AF Hybrid HC A-1008 FCS HN 125 HC A-2002 FCS AF Hybrid HC A-2002 FCS HN 125 HC A-4001 HC A-4001 FCS AF Hybrid HC A-4001 FCS HN 125 HC Baseball Engel HC Baseball FCS HN 125 HC C-1002 FCS AF Hybrid HC C-1002 FCS HN 125 HC C-2002 FCS AF Hybrid HC C-2002 FCS HN 125 HC C-2004 Engel HC C-2004 FCS AF Hybrid HC C-2004 FCS HN 125 HC C-9003 Engel HC C-9003 FCS HN 125

Cycle Time (min) 0.07 0.13 0.08 0.09 0.07 0.08 0.09 0.07 0.06 0.07 0.09 0.13 0.09 0.08 0.08 0.09 0.07 0.09 0.08 1.02 0.09 0.10 0.06 0.01 0.10 0.07 0.09

Output

122.109 73.545 60.139 193.363 18.145 221.272 471.483 217.071 937.338 463.619 629.424 73.364 147.964 14.400 10.868 98.099 193.337 144.535 26.299 57.126 45.804 56.176 6.508.887 207.286 210.866 296.364 358.727

Performance

92.4% 79.4% 77.6% 84.2% 113.4% 67.3% 86.4% 87.9% 79.8% 78.1% 89.3% 82.5% 93% 138. 5% 77% 94.1% 85.7% 103.4% 83.4% 66.4% 96.3% 68.2% 83.1% 63% 101.4% 89.8% 100% 6

13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29.

HC F38 FCS HN 125 Outsole OS 38773 Quick Rugby SG OS 39367 Messi FG Jr OS 40504 2016 X16.3 FG OS 40834 2016 FG OS 41003 2016 P1 ACE 16.1 SG OS 41163 2016 Generic P1 AG OS 41164 2016 Generic P2/P3 AG Men OS 41165 2016 Generic P2/P3 AG Jr OS 41538 ACE17.3 FG Aksesoris Heel Cap AD-42142 Supernova Insole 11028 2012 Nitrocharge Chassis Insole 11034 2016 ACE FG/SG NB Heel Stabilizer NB Shank TPU Shore D M STRO Shoe Horn Torsion Bar AD-42142 Supernova

0.13

73.545

79.4%

3.87 1.13 1.25 1.69 1.72 1.92 1.30

19.804 369.574 724.204 13.833 235.938 57.883 323.612

88.4% 103.2% 93.8% 71.1% 93.3% 80.5% 111.1%

1.16 1.09

191.502 1.207.631

97.2% 102.3%

1.08 0.52 0.51 0.31 0.31 0.20 0.31

135.600 45.303 288.826 134.717 196.093 98.488 176.022

112.2% 109.2% 118.3% 71.7% 81.6% 115.3% 84.7%

And to calculate Quality ratio, can used information below: No 1. 2. 3.

4. 5.

6.

Product Name Heel Counter HC 05091 Engel HC 05091 FCS HN125 HC 2126 FCS AF Hybrid HC 2126 FCS HN125 HC 21391 HC 21391 FCS AF Hybrid HC 21391 FCS HN125 HC A-1004 FCS Engel HC A-1008 Engel HC A-1008 FCS AF Hybrid HC A-1008 FCS HN 125 HC A-2002 FCS AF Hybrid

Defect 207 165 87 313 45 422 668 345 1.208 644 764 136

Quality 99.8% 99.8% 99.9% 99.8% 99.8% 99.8% 99.9% 99.8% 99.9% 99.9% 99.9% 99.8% 7

7.

8. 9. 10 11.

12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29.

HC A-2002 FCS HN 125 HC A-4001 HC A-4001 FCS AF Hybrid HC A-4001 FCS HN 125 HC Baseball Engel HC Baseball FCS HN 125 HC C-1002 FCS AF Hybrid HC C-1002 FCS HN 125 HC C-2002 FCS AF Hybrid HC C-2002 FCS HN 125 HC C-2004 Engel HC C-2004 FCS AF Hybrid HC C-2004 FCS HN 125 HC C-9003 Engel HC C-9003 FCS HN 125 HC F38 FCS HN 125 Outsole OS 38773 Quick Rugby SG OS 39367 Messi FG Jr OS 40504 2016 X16.3 FG OS 40834 2016 FG OS 41003 2016 P1 ACE 16.1 SG OS 41163 2016 Generic P1 AG OS 41164 2016 Generic P2/P3 AG Men OS 41165 2016 Generic P2/P3 AG Jr OS 41538 ACE17.3 FG Aksesoris Heel Cap AD-42142 Supernova Insole 11028 2012 Nitrocharge Chassis Insole 11034 2016 ACE FG/SG NB Heel Stabilizer NB Shank TPU Shore D M STRO Shoe Horn Torsion Bar AD-42142 Supernova

174 50 18 169 248 175 30 126 106 176 6.290 361 266 446 396 165

99.9% 99.7% 99.8% 99.8% 99.9% 99.9% 99.9% 99.8% 99.8% 99.7% 99.9% 99.8% 99.9% 99.8% 99.9% 99.8%

1.236 13.434 46.400 1.150 15.285 5.518 10.521 7.366 56.826

97% 96.4% 93.6% 91.7% 93.5% 90.5% 96.7% 96.2% 95.3%

9.958 663 1.729 5.222 1.806 10 163

92.7% 98.5% 99.4% 96.1% 99.1% 100% 99.9%

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So, OEE ratio for each item: No 1. 2. 3.

4. 5.

6. 7.

8. 9. 10 11.

12. 13. 14. 15. 16. 17.

Product Name Heel Counter HC 05091 Engel HC 05091 FCS HN125 HC 2126 FCS AF Hybrid HC 2126 FCS HN125 HC 21391 HC 21391 FCS AF Hybrid HC 21391 FCS HN125 HC A-1004 FCS Engel HC A-1008 Engel HC A-1008 FCS AF Hybrid HC A-1008 FCS HN 125 HC A-2002 FCS AF Hybrid HC A-2002 FCS HN 125 HC A-4001 HC A-4001 FCS AF Hybrid HC A-4001 FCS HN 125 HC Baseball Engel HC Baseball FCS HN 125 HC C-1002 FCS AF Hybrid HC C-1002 FCS HN 125 HC C-2002 FCS AF Hybrid HC C-2002 FCS HN 125 HC C-2004 Engel HC C-2004 FCS AF Hybrid HC C-2004 FCS HN 125 HC C-9003 Engel HC C-9003 FCS HN 125 HC F38 FCS HN 125 Outsole OS 38773 Quick Rugby SG OS 39367 Messi FG Jr OS 40504 2016 X16.3 FG OS 40834 2016 FG

OEE 79% 75% 71% 78% 113% 63% 83% 79% 75% 75% 87% 78% 91% 128% 71% 88% 77% 101% 80% 63% 86% 61% 80% 60% 98% 81% 96% 75% 68% 88% 76% 50% 9

18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29.

OS 41003 2016 P1 ACE 16.1 SG OS 41163 2016 Generic P1 AG OS 41164 2016 Generic P2/P3 AG Men OS 41165 2016 Generic P2/P3 AG Jr OS 41538 ACE17.3 FG Aksesoris Heel Cap AD-42142 Supernova Insole 11028 2012 Nitrocharge Chassis Insole 11034 2016 ACE FG/SG NB Heel Stabilizer NB Shank TPU Shore D M STRO Shoe Horn Torsion Bar AD-42142 Supernova

72% 53% 97% 81% 90% 96% 85% 96% 61% 74% 110% 81%

OEE ratio for whole production shown in table below: O

Plant Complete O/s Shift 1 Shift 2 Shift 3 Shift 1( 5 Hrs) Shift 2( 5 Hrs) Shift 3 ( 5 Hrs )

84.2% 77.6% 82.2% 85.4% 84.8% 85.5% 89.0% 86.8%

A

89.3% 86.2% 87.6% 89.7% 90.4% 88.4% 94.7% 93.5%

P

P lanned P ro d T ime

Q

95.3% 97.9% 95.2% 96.2% 94.5% 97.4% 97.2% 94.9%

98.9% 92.0% 98.6% 98.9% 99.1% 99.2% 96.7% 97.8%

5,770,628 2,005,415 1,782,922 1,940,168 2,035,508 4,500 4,140 3,390

T ime Lo ss

# C ell

Out put

Good

615,737 18,172,457 17,974,036 276,838 1,547,354 1,423,014 220,756 3,702.2 4,618,358 4,551,557 199,486 4,030.2 6,162,911 6,096,779 194,535 4,229.0 7,374,216 7,309,075 520 6.2 6,399 6,350 220 5.8 5,855 5,659 220 4.7 4,718 4,616

Quality Lo ss (prs) D e fect

198,421 124,340 66,801 66,132 65,141 49 196 102

R atio

1.09% 8.04% 1.45% 1.07% 0.88% 0.77% 3.35% 2.16%

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Down Time Information: DOWNTIME LOSS DT Name Code Break PB Mold Change PM Shortage Component PC Setting PP Color Change CC Mold repair MR Broken Runner MRU Screw Cleaning with Material PS Machine Failure TF Clogged Nozzle Mampet CCN Waiting for enough component PC1 Waiting for Mold PM1 Mold Cleaning PM2 Low temperature PT Hopper cleaning PH Nozzle Cleaning PN Charging problem 1 PCP1 Mold Off Centered POC Barrel Screw Clean TS Unplanned Power cut TP Shortage of Material CS Color Variation CV Charging problem 2 PCP2 Connecting mold water pipe PMW Shortage Operator PO Water leakage PW Mold Failure MF Drying Material CD Broken Mold Clamp PMC Heater Replace TR Test material PTM Quality Approval QA Chiller failure TC Left Right matching PLRM Waiting for base mold MB Mold Test MT Screw Damage TSD Wrong Material WMT Insert logo ISB PL Extra Component PE Base mold adjustment MBA

TL (mi) 156,038 90,829 68,626 60,655 35,104 31,919 27,345 27,050 24,970 12,267 11,819 8,808 6,181 5,800 5,470 5,407 4,898 4,686 4,581 3,845 3,709 2,804 1,933 1,802 1,220 1,203 1,195 1,183 1,034 905 758 673 480 130 100 50 35 30 25 25 20

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5. Conclussion Based on data shown in this study which related with Overall Equipment Effectiveness and production loses in PT Framas Indonesia. Hypothesis “Overall Equipment Effectiveness has a significant influence on production losses.” accepted. This statement based on data that shown low OEE ratio impact to material losses caused of defect. By OEE system we can know what the problem that make production machine and equipment not effective. The big five problem of not effective production machine and equipment are: break , mold change, shortage component, setting, and color change. In my point of view to reduce not effective production machine and equipment production, factory better make an investment of automatic machine and equipment to make a shorter mold application time. And another suggestion is maintenance department must always do a periodical maintain to optimize machine and equipment.

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Refference: L. Hassani, G. Hashemzadeh (2015). The Impact of Overall Equipment Effectiveness on Production Losses in Moghan Cable & Wire Manufacturing. International Journal for Quality Research 9(4) 565-576 ISSN 1800-6450. http://www.ijqr.net/journal/v9n4/2.pdf A.J. de Ron and J.E. Rooda (2005). OEE and Equipment Effectiveness: an Evaluation. International Journal of Production Research. https://hal.archives-ouvertes.fr/hal00512884/document Web Refference http://www.pitoyo.com/catatanpitoyo/index.php/oee/97-sejarah-oee http://ilmumanajemenindustri.com/cara-menghitung-oee-overall-equipmenteffectiveness-tpm/ https://eriskusnadi.wordpress.com/2011/09/24/tentang-overall-equipmenteffectiveness/

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