:: Research Report:: WORKF KFORCE AL ALLOCAT ATIO ION N BA - - PowerPoint PPT Presentation
Industrial Engineering Department Faculty of Industrial Technology Institut Teknologi Sepuluh Nopember Surabaya :: Research Report:: WORKF KFORCE AL ALLOCAT ATIO ION N BA BASE SED ON N TI TIME ST STUD UDY Y AN AND WORK K BA
Edwin Saferian 2510100006
:: BY
Industrial Engineering Department Faculty of Industrial Technology Institut Teknologi Sepuluh Nopember Surabaya
WORKF KFORCE AL ALLOCAT ATIO ION N BA BASE SED ON N TI TIME ST STUD UDY Y AN AND WORK K BA BALAN ANCIN ING (CAS ASE STU TUDY Y : P PT T MAD ADUS USAR ARI I MAS AS – RUN UNGK GKUT UT BR BRAN ANCH) H)
Arief Rahman, S.T., MT
GUIDED AND SUPERVISED BY
:: Research Report::
Source : PPM Riset Manajemen
Percentage of Industries Use Outsourced Worker
Office Support (Cleaning and maintenance) Driver and transportation Private Security PT MADUSARI MAS
Rumahindahdanbersih.blogspot.com
Madusari Needs to Compete
Optimization of productivity can be conducted by distributing the workload in equal measure
“Equalized” workload doesn’t mean that every worker have the same scoring attribute, considering the area in charge, hazard rate of area and other allowances Productivity should be optimized
“How to calculate the workers’ workload and work force allocation in order to increase productivity using work study approach of stopwatch time study and work
equalize the level of workload.”
Determine the number of work force based on capacity need
Optimal workload and manpower in Madusari - Rungkut Branch can be
Providing new assessment mechanism for workload auditing for future reference
Research object is PT Madusari Mas – Rungkut Branch Field study and data gathering are conducted between March 2013 to May 2013 This research is focusing in main activities such as cleaning and facility maintenance Observation is conducted only in two of three shift, the morning shift and the evening shift.
Job description will not be changed during this research Work elements that being identified are the main job (incidental work not included)
Chapter 1 Preface Chapter 2 Literature Review Chapter 3 Research Methodology Chapter 4 Data Gathering and Processing Chapter 5 Data Analysis and Interpretation Chapter 6 Conclusion and Recommendation
Work Measurement Stopwatch Time Study Prod Leveling/Work Balancing Operation Research WORKF KFORCE AL ALLOCAT ATIO ION N BA BASED ON N TI TIME STU TUDY Y AN AND LIN INE BA BALAN ANCIN ING Knapsack Theory
time study is a direct and continuous
a work measurement technique consisting of careful time measurement of the task with a time measuring instrument, adjusted for any observed variance from normal effort or pace and to allow adequate time for such items as foreign elements, unavoidable or machine delays, rest to overcome fatigue, and personal needs
(Groover, 2007) The Industrial Engineering Terminology Standard
Data Uniformity Test
Uniformity test is used to find out if the uniformity of sampled data 𝑀𝐷𝑀 = 𝑌 − 3ơ 𝑉𝐷𝑀 = 𝑌 + 3ơ UCL / LCL = Upper/Lower Classified Level X = Mean of collected data Ơ = Standard deviation obtained
Data Adequacy Test
This test is conducted to find out whether the amount of collected data is adequate or not
2
. . ' k X S Z N
N’ = Number of Observation should be conducted Z = Trust Index (95% ≈ index 2) s = Standard deviation of data = Mean of uniformed data k = level of error (5%)
X
Determine the Performance Rating and Allowances
Unilever Allowances Standard
Calculating Normal Time
Normal time = Actual time x Performance Rating
Fixed Allowance No Male Female 1 Personal Need 5 6 2 Fatigue 4 4 Total
Variable Allowance Male Female a. Standing 2 4 b. Work Postion Rather Kneel 1 Kneeling 2 3 Lay down 7 7 c. Energy 2,5 kg 1 5 kg 1 2 7,5 kg 2 3 10 kg 3 4 12,5 kg 4 6 15 kg 6 9 17,5 kg 8 12 20 kg 10 15 22,5 kg 12 18 25 kg 14
kg 19
kg 33
kg 58
Lightning Standard
Variable Allowance Male Female a. Standing 2 4 b. Work Postion Rather Kneel 1 Kneeling 2 3 Lay down 7 7 c. Energy 2,5 kg 1 5 kg 1 2 7,5 kg 2 3 10 kg 3 4 12,5 kg 4 6 15 kg 6 9 17,5 kg 8 12 20 kg 10 15 22,5 kg 12 18 25 kg 14
19
33
58
Lightning Standard Below Average 2 2 Above Average 5 5 e. Temperature Fresh Normal 5 5 Hot 5 15 f. Environment Normal Dusty 2 2 Hazardous 5 5 g. Noise Repetitive Randomly 2 2 High Ptched 5 5
Calculating Standard Time
St =
𝑂𝑝𝑠𝑛𝑏𝑚 𝑢𝑗𝑛𝑓𝑦 100% 100%−𝑏𝑚𝑚𝑝𝑥𝑏𝑜𝑑𝑓
Calculating Workload
WL =
𝑇𝑢𝑏𝑜𝑒𝑏𝑠𝑒 𝑢𝑗𝑛𝑓 𝑦 𝐺𝑠𝑓𝑟 𝑦 𝑂𝑝𝑉 𝑈𝑝𝑢𝑏𝑚 𝑋𝑝𝑠𝑙 𝑈𝑗𝑛𝑓
Work Balancing, also known as production leveling or assembly line balancing, is a technique for reducing the work deviation. The assembly line balancing problem is a well-studied problem with many applications, including the automotive industry, consumer electronics, and household items
(Baybar, 1986)
Improvised by Genichi Taguchi, Imperial Navy Engineer and Toyota Corporation Consultan
30 25 20 15 10
1 2 3
5
Takt (25 hrs)
15 30 17
1 2 3
25 25 12
Takt (25 hrs)
30 25 20 15 10 5
Improvised by Genichi Taguchi, Imperial Navy Engineer and Toyota Corporation Consultan
Operations research, or management sciences, is a discipline that deals with the application of advanced analytical methods to help make better decisions. It is often considered to be a sub-field of mathematics
(Wetherbee, 1979)
The knapsack theory problem or rucksack problem is a problem in combinatorial
a mass itself, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit
Knapsack Theory
Also known as burglar theory
Knapsack Theory
Knapsack Capacity Item(s) Weight Maximum-Filled Knapsack
Max Work hour Work(s) time completion Optimal Workload Given
1
2 1
2
3
Takt level = 100%
Morning Shift Area Number of Workforce 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 1 10 1 Total 10
Evening Shift Area Number of Workforce 2 1 4 1 5 1 6 1 7 1 9 1 10 1 Total 7 Night Shift Area Number of Workforce 2 1 4 1 5 1 6 1 7 1 9 1 10 1 Total 7
Work Shifts First half Second half Time Windows
Sub Area : Office Sub Area :Drum Office Cleaning
Second Sterilization
Colouring Room Drum Streilization Liquid Puder Drum Packing SLS Nedel Second Sterilization Drum Box Wash Clean Drum Packing Garbaging Hall Cleaning Waste Chem Treatment Hall Cleaning Hall A Cleaning Hall Cleaning Take Waste Retrieve waste Sub Area : Waste
Work Area 1
Sub Area : Office Sub Area : Waste and Wash Sweeping Teraso Conveyor Mopping Teraso Chalk cleaning Office Cleaning Waste Disposal Washbay Teraso Polish Tube Scrapping Shuttle Door Layer Scraoping Windows Cleaning Walling Piping Washbay Polishing Work Area 2
Sub Area : Relig Building Sub Area ; Office Ablution Water Main Office PC Stainless Fence TPM PC Window List Meeting Room Waste Disposal Packaging Wooden Wall List Office Toilet Bordet Floor PC Lobby Dispensing Stair Trap Musholla Vaccuum Conveyor
Work Area 3
Sub Area : Hall A Sub Area : Engine Sweeping Epoxy Seeping Bordest Mopping Epoxy Sweeping Epoxy Dusting Wall Mooping Bordest Piping Tank Mopping Epoxy Dusting Piping System Cabinet Waste Disposal Office Desk Sweeping Epoxy Piping Tank Mopping Epoxy Dusting Piping System Dusting Wall Waste Disposal Sub Area : Hall B Work Area 4
Module 1 Module 6 Sweeping Epoxy Sweeping Epoxy Mopping Epoxy Mopping Epoxy Sweeping Teraso Sweeping Teraso Mopping Teraso Mopping Teraso Machining Machining Module 5 Mazanine Sweeping Epoxy Sweeping Epoxy Mopping Epoxy Mopping Epoxy Sweeping Teraso Sweeping Teraso Mopping Teraso Mopping Teraso Machining Machining Work Area 5
Sub Area : Packing Line Sub Area : Cabinet Roo Dispensing Display Rack Control Panel Cabinet filling P3 Domino Waste Speaker Cleaning Stair Bordes Sweeping Epoxy Piping Mopping Epoxy Machining Sweeping Teraso Wall Dusting Mopping Teraso Ceramic Wall Bin Cleaning Wall List Cleaning Work Area 6
Sub Area : Kugler Sub Area : D3 Sweeping Epoxy Sweeping Epoxy Mopping Epoxy Mopping Epoxy Sweeping Teraso Sweeping Teraso Mopping Teraso Mopping Teraso Machining Machining Sub Area : Vega Sub Area : D4 Sweeping Epoxy Sweeping Epoxy Mopping Epoxy Mopping Epoxy Sweeping Teraso Sweeping Teraso Mopping Teraso Mopping Teraso Machining Machining Sweeping Epoxy Mopping Teraso Mopping Epoxy Machining Sweeping Teraso Mopping Teraso Machining Sub Area : D5 Work Area 7
Sub Area : Polishing Sweeping Teraso Sweeping Bordes Polishing Teraso Polishing Bordes Work Area 8
SLS Area Chalking Zone Sweeping Epoxy Sweeping Epoxy Mopping Epoxy Mopping Epoxy Dusting Wal Dusting Wal Dusting Profile Tank Dusting Profile Tank Dusting Piping System Dusting Piping System Dusting Exit Forklift Dusting Exit Forklift Waste Disposal Waste Disposal Dusting Shuttle Door Dusting Shuttle Door Seeping Bordest Dusting Fence Sweeping Epoxy Sterillan Cleaning Mooping Bordesr Dusting Piping System Mopping Epoxy Dusting Exit Forklift Dusting Shuttle Door Waste Disposal Modul 1-7, Mezzanine Work Area 9
Sub Area : Rest RoomSub Area : Entrance Mopping Toilet Bordac Wet Entrance Equipment Maintenan Dry Entrance Washtafel Inner Wash Toilet Cleaning Sweep Entance Urinoir Sub Area : Other Cargo Procuring Glass Cleaning
Work Area 10
Not Included in second half of Morning Shift Evening Shift Polishing Piping Hall A Piping Hall A Piping Hall B
Work Sampling and Uniformity Test
Work Descriptiom Sampling Time 1 2 3 4 5 6 7 8 9 10 11 12 13 Sweeping Teraso 398 347 348 401 565 334 378 342 403 328 385 400 388 Sweeping Bordes 295 275 299 255 256 222 310 298 288 289 298 301 290 Polishing Teraso 2759 2759 2716 2778 2743 2719 2702 2765 2770 2761 2760 2786 2782 Polishing Bordes 1993 1984 1967 1973 1931 2001 1920 1936 1908 1935 1936 1904 1975
Work Sampling and Uniformity Test
Work Descriptiom Sampling Time 1 2 3 4 5 6 7 8 9 10 11 12 13 Sweeping Teraso 398 347 348 401 565 334 378 342 403 328 385 400 388 Sweeping Bordes 295 275 299 255 256 222 310 298 288 289 298 301 290 Polishing Teraso 2759 2759 2716 2778 2743 2719 2702 2765 2770 2761 2760 2786 2782 Polishing Bordes 1993 1984 1967 1973 1931 2001 1920 1936 1908 1935 1936 1904 1975
1 2 3 4 5 6 7 8 9 10 11 12 13 Sweeping Teraso 398 347 348 401 334 378 342 403 328 385 400 388 28,90738 371 9,3 10,0 Sweeping Bordes 295 275 299 255 256 310 298 288 289 298 301 290 17,34586 288 5,6 6,0 Polishing Teraso 2759 2759 2716 2778 2743 2719 2702 2765 2770 2761 2760 2786 2782 119,23 2754 2,9 3,0 Polishing Bordes 1993 1984 1967 1973 1931 2001 1920 1936 1908 1935 1936 1904 1975 144,23 1951 8,4 9,0 N' Sampling Time stdev average
Adequacy Test
Basic Time (BT) (minutes) Standard Time (minutes) Speed Area : Polishing Sweeping Teraso 371 6,1833 0,7 4,328333333 5,150716667 Sweeping Bordes 288 4,7972 0,7 3,358055556 3,996086111 Polishing Teraso 2754 45,897 0,7 32,12820513 38,2325641 Polishing Bordes 1951 32,517 0,7 22,76166667 27,08638333 BT + (BT x % Allowance)
OT (sec) OT (min) Work Area 8
Rating Factor (RF) (OT x %RF/100%)
Data Collecting-Standard Time
Basic Time (BT) (minutes) Standard Time(ST) (minutes) % Workload Speed Area : Polishing Sweeping Teraso 6,1833 1 4 0,19 0,7 4,328333333 5,150716667 0,042922639 Sweeping Bordes 4,7972 1 4 0,19 0,7 3,358055556 3,996086111 0,033300718 Polishing Teraso 45,897 1 1 0,19 0,7 32,12820513 38,2325641 0,079651175 Polishing Bordes 32,517 1 1 0,19 0,7 22,76166667 27,08638333 0,056429965 21,23% BT + (BT x % Allowance) (ST x NOU x F)/Total Work Time Total Allowanc e
OT (min) Numbe r of Unit (NOU) Freq (F)
Work Area 8
Rating Factor (RF) (OT x %RF/100%)
8 Hours 480 Minutes Total Workload
No Area Workload 1 1 124,38% 2 2 76,05% 3 3 75,48% 4 4 85,21% 5 5 68,90% 6 6 68,38% 7 7 73,74% 8 8 21,23% 9 9 82,91% 10 10 47,95% 72,42% 0,263 Average Std Dev Morning Shift
No Area Workload 1 2 53,44% 2 4 73,23% 3 5 58,66% 4 6 61,63% 5 7 65,25% 6 9 51,24% 7 10 46,96% 58,63% 0,0898 Evening Shift Std Dev Average
Elemont No i Element Workload (/10000) w Element No i Element Workload (/10000) w 1 Afa_off 1598 15 Kug5 1518 2 Afa_waste 4592 16 kug4 1426 3 Afa_drum 6250 17 kug3 1494 4 Ent_rest 4456 18 Pack_PL 2520 5 Ent_ent 140 19 Pack_Kab 4250 6 Ent_ot 202 20 Mod165_1 1736 7 Slurs_SLS 5062 21 Mod165_5 1716 8 Slurs_chalk 2324 22 Mod165_6 1732 9 Slurs_mod 874 23 Mod165_M 1708 10 Sub_office 2564 24 Roompc_Off 3296 11 Subs_waste 5042 25 Roompc_rel 4254 12 Polish 2123 26 Pipe_A 2351 13 Kug_kug 1648 27 Pipe_B 2932 14 Kug_veg 4190 28 Pipe_E 888
Summary of Major Elements Workload of Morning Shift
SETS: ITEMS / AFACON_OFFICE, AFFACON_WASTE, AFFACON_DRUM, ENTRANCE_REST, ENTRANCE_ENTRANCE, ENTRANCE_OTHER, SLURRY_SLS, SLURRY_CHALK, SLURRY_MOD, SUBS_OFFICE, SUBS_WASTE, POLISHING, KUGGLER_KUGGLER, KUGGLER_VEGA, KUGGLER_5, KUGGLER_4, KUGGLER_3, PACKINGLINE_PL, PACKINGLINE_KABINET, MOD165_1, MOD165_5, MOD165_6, MOD165_M, ROOMPC_OFFICE, ROOMPC_REL, PIPING_A, PIPING_B, PIPING_ENGINE/ : INCLUDE, WEIGHT, RATING; ENDSETS DATA WEIGHT RATING = 799 1 !afacpnoffice; 2296 1 !afawaste; 3125 1 !adadrum; 2228 1 !entrest; 70 1 !entent; 101 1 !entoth; 2531 1 !slursls; 1162 1 !slurchalk; 437 1 !slurmod; 1282 1 !subofice; 2521 1 !subswaste; 2123 1 !polishing; !only once;
824 1 !kugkug; 2095 1 !kugveg; 759 1 !kug5; 713 1 !kug4; 747 1 !kug3; 1260 1 !packPL; 2125 1 !packKab; 868 1 !mod1651; 858 1 !mod1655; 866 1 !mod1656; 854 1 !mod165m; 1648 1 !roompcoff; 2127 1 !roompcrel; 2351 1 !pipeA; !only once; 1466 1 !pipeB; 444 1 !pipeEn; ; WORKER_CAPACITY = 5000; ENDDATA MAX = @SUM( ITEMS: RATING * INCLUDE); @SUM( ITEMS: WEIGHT * INCLUDE) <= WORKER_CAPACITY; @FOR( ITEMS: @BIN( INCLUDE));
1 2 3
“knapsack”/worker capacity Major elements Decision 1 = allocate 0 = not allocate
Translated as : Worker allocated to do elements/activites such as afacon_office, entrance_entrance, entrance_, kugler_kugler, kugler_5, kugler_4, kugler_3 and piping_engine
First Half Second Half
Total Workload : 728.34% Average : 91,04%
Optimized
Data Processing-Evening Shift
Total Workload : 204,99% Average : 51,24% Total Workload : 172,19% Average : 43,047%
First Half Second Half
Data Processing-Evening Shift
Optimized
Average : 94.30%
Pre Optimized Morning Shift
Problem : Overload Work Underload Work
Total Area : 10 Average Workload : 72,24% Leads to
Very High Workload Deviation : 0,263
Pre Optimized EveningShift
Problem : Too many underload Work
Total Area : 7 Average Workload : 58,63% Workload Deviation : 0,0898 Leads to
Very low workload given in total
No Area Workload 1 3 80,16% 2 8 84,50% 3 5 90,48% 4 2 92,16% 5 7 92,32% 6 6 95,36% 7 4 95,48% 8 1 97,88% 91,04% 0,146 Average Optimized Morning Shift Std Dev d No Area Workload 1 1 90,62% 2 2 90,90% 3 3 96,96% 4 4 98,70% 94,30% 0,041 Optimized Evening Shift Average Std Dev
Total Area : 8 Average Workload : 91,04% Workload Deviation : 0,146 Total Area : 4 Average Workload : 94,30% Workload Deviation : 0,041
Total Worker 10 Average Workload 71,42% Workload Deviation 0,263 Total Worker 7 Average Workload 58,63& Workload Deviation 0,0898 Pre Optimized Morning Evening Total Worker 8 Average Workload 91,04 Workload Deviation 0,146 Total Worker 4 Average Workload 94,30% Workload Deviation 0,041 Optimized morning Evening
Based on the analysis, the final conclusion to answer the research objective can be stated as below :
workload is 72,42% with the workload deviation of 0,263. The evening shift has the initial total workload of 410,41% for 7 workers which the average workload is 58,63% with the workload deviation of 0,0898.
significant workload deviation.
morning shift the initial average workload of 72,42% is increased to 91,04%, while the workload deviation reduced from 0,263 to 0,146, and the number of workforce is reduced from 10 workers to 8 workers. As for the evening shift the initial average workload of 58,63% is increased to 94,30%, while the workload deviation reduced from 0,0898 to 0,041, and the number of workforce is reduced from 7 workers to 4 workers.
As for the recommendation for this research can be stated as :
needed per shift.
capture the entire working shift, regarding this research is only capture morning shift and evening shift while the night shift can’t be captured due to permittal problem. If the night shift can be captured, all of the traits of each shift can be identified and analyzed, regarding the two shift that been captured has unique anomalies and problems on their
Beer, S. (1967). Management Science: The Business Use of Operations Research. Chuda Basnet, E. P. (1998). A Manpower Planning Decision Support System for MQM Meat Services. Hamilton: Dept of Management System University of Waikato. Deming, E. (1993). The New Economics: For Industry, Government, Education. MIT Press. Freeman, R. (2008). Labour Productivity Indicator. OECD Statistic Directorate. Groover, M. P. (2007). Work Systems: The Methods, Measurement & Management of Work. Prentice Hall.
Jex, S. M. (1998). Stress and job performance: Theory, research, and implications for managerial practice. California: Thousand Oaks. Johnson, P. (2009). HRM in changing organizational contexts. Human resource management: A critical approach, 19-37.
Melik, R. (2010). Rise of the Project Workforce, Chapter 9: Workforce Planning. PM Hut. Stramler, J. (1993). The Dictionary of Human Factor/Ergonomic. Boca Raton, FL: CRC Press Inc.
Wild, B. &. (1993). Manpower Capacity Planning . A Hierarchical Approach, 30-31, 95-106.