FLEET SIZING USING SIMULATION APPROACH AND
PROFITABILITY ANALYSIS ON INVESTMENT OF
I-TROLLEY IN HARD DRIVE MANUFACTURER
A THESIS
Submitted in Partial Fulfillment of the Requirement for the Bachelor Degree of Engineering in Industrial Engineering
RADINAL WIBISONO 12 14 07099
INTERNATIONAL INDUSTRIAL ENGINEERING PROGRAM DEPARTMENT OF INDUSTRIAL ENGINEERING
FACULTY OF INDUSTRIAL TECHNOLOGY UNIVERSITAS ATMA JAYA YOGYAKARTA
iv
ACKNOWLEDGEMENT
The author conducted the research on Fleet Sizing using Simulation Approach
and Profitability Analysis on I-Trolley Investment in Hard Drive Manufacturer to
fulfill partial requirement to earn bachelor degree of Industrial Engineer of
Universitas Atma Jaya Yogyakarta.
The author would like to deliver gratitude and thankfulness to God for such a
kindness a good grace. The author would like to deliver highest appreciation to
Mr. The Jin Ai, D.Eng. and Mrs. Deny Ratna Yuniartha, S.T., M.T. as faculty
supervisor and co-supervisor for the guidance during conducting this research.
Highest appreciation also goes to Mrs. Ririn Diar Astanti, D.Eng. as Coordinator
of International Industrial Engineering for the help during study period in
Universitas Atma Jaya Yogyakarta.
The deepest appreciation for Mr. Hatmarto, Mrs Ermin Widijanti, Mrs. Aninditya
Radini, and Mrs. Radita Angelina for their love and dedication from the beginning
until finishing this research. Great gratitude is given to Mrs. Grace Natalia S.T. for
her support in conducting this research.
Big appreciation goes to author’s family, relatives, and friends especially from Industrial Engineering batch 2012, teaching assistant in work system design lab,
production system lab, and optimization modelling lab for all the supports given to
the author. Last but not least, author is amicable for suggestions that boost the
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1.4. Scope and Limitations of Research 5
2 Literature Review 6
2.1. Automated Material Handling System 6
2.2. Fleet Sizing 7
3.2. Data Collection Stage 18
3.3. Model Development 19
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3.5. Final Project Writing and Presentation 20
5.2. Model Verification and Validation 42
5.3. Simulation Running 44
6 Feasibility Analysis 49
6.1. Payback Period 49
6.2. Internal Rate of Return 51
6.3. Sensitivity Analysis 51
7 Conclusion and Suggestion 54
7.1. Conclusion 54
7.2. Suggestion 55
References 56
vii
LIST OF TABLE
Table 2.1. Material Handling Equipment Based on Layout Type 7
Table 2.2. Summary of Literature Review 16
Table 3.1. Summary of Data Taken 19
Table 4.1. Work Elements in Start Point (Phase One) 25
Table 4.2. Work Elements in End Point (Phase One) 26
Table 4.3. Summary of Data Taken in Phase One 26
Table 4.4. Work Elements in Start Point (Phase Two) 29
Table 4.5. Work Elements in End Point (Phase Two) 29
Table 4.6. Summary of Data Taken in Phase One 30
Table 4.7. Operator Cycle Time 31
Table 4.8. Operator Required on Phase One 31
Table 4.9. Operator Required on Phase Two 32
Table 4.10. Inter-Arrival Time in Backend Stream Station 33
Table 4.11. Cycle Time in Pack 2 34
Table 4.12. Summary of Cost Parameter 36
Table 5.1. Module Used in ARENA Software 38
Table 5.2. Maximum Entities on Each Replication 43
Table 5.3. Overview on Maximum Entities in Simulation Model 44
Table 5.4. Summary Result on Initial Simulation 44
Table 5.5. Summary Result on 80 Replications 45
Table 5.6. Scenario in Simulation of I-Trolley Number 46
Table 6.1. Cost, Investment, and Savings Component 49
Table 6.2. Cash Flow Calculation 50
Table 6.3. Cash Flow Calculation during Eight Year 51
Table 6.4. Cash Flow in Annual Period 51
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LIST OF FIGURES
Figure 1.1. Procedure of I-Trolley Operation 3
Figure 1.2. I-Trolley Planning Phase 4
Figure 1.3. I-Trolley Prototype 4
Figure 2.1. Material Handling Equipment Based on Flow Rate and
Distance Moved
6
Figure 2.2. Overall Fleet Sizing Procedure 9
Figure 2.3. Process in Simulation Study 11
Figure 3.1. Methodology for Final Project 21
Figure 4.1. L-Cart 23
Figure 4.2. Tote Box 23
Figure 4.3. Layout of Phase One 24
Figure 4.4. Kanban Trolley 26
Figure 4.5. Layout of Phase Two 28
Figure 4.6. Time Distribution of Backend Stream Station 33
Figure 4.7. Time Distribution of Pack 2 34
Figure 5.1. Process Flow Diagram 37
Figure 5.2. Complete Model on ARENA Software 39
Figure 5.3. Model in ARENA for Start Point in Phase One 40
Figure 5.4. Model in ARENA for End Point in Phase One 40
Figure 5.5. Model in ARENA for Start Point in Phase Two 41
Figure 5.6. Model in ARENA for End Point in Phase Two 41
Figure 5.7. Generate Model in ARENA Software 42
Figure 5.8. Feature to Verify Model in ARENA Software 42
Figure 5.9. Comparison of Flow Time between Scenarios 46
Figure 5.10. Comparison of Production Volume between Scenarios 47
Figure 5.11. ANOVA Analysis on Flow Time 48
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LIST OF APPENDICES
Appendix 1 Uniformity and Sufficiency Test Loading I-Trolley 60
Appendix 2 Uniformity and Sufficiency Test Unloading I-Trolley 61
Appendix 3 Uniformity and Sufficiency Test Transporting to Pack 2 62
Appendix 4 Uniformity and Sufficiency Test Transporting from Pack 2 63
Appendix 5 Uniformity and Sufficiency Test Transporting to Backend
Stream Line
64
Appendix 6 Uniformity and Sufficiency Test Transporting from Backend
Stream Line
65
Appendix 7 Uniformity and Sufficiency Test Unloading from Lift 66
Appendix 8 Uniformity and Sufficiency Test Loading to Lift 67
x ABSTRACT
The thesis entitled “Fleet Sizing Using Simulation Approach and Profitability Analysis on Investment of I-Trolley in Hard Drive Manufacturer” began with problem occurred in hard drive manufacturer in determine number of automated material handling used in production floor. The purpose of automated material handling is to replace human power in material handling activity due to efficiency in transportation activity. Hard drive manufacturer decide to use I-Trolley.
Industrial Engineering Department in the project is responsible to determine optimum number of I-Trolley or can be defined as fleet sizing of I-Trolley and activity. Operator requirement in operating I-Trolley is analyzed using time study. The objectives of this research to have optimum number of I-Trolley based on minimum material waiting time and maximum capacity in production floor.
The conclusion on optimum number of I-Trolley is 14 with phase one and phase two respectively need six and eight. ANOVA analysis shows that there is no significance difference if one I-Trolley added into the scenario. Operator reduced with I-Trolley implementation is 18 employees. Management decide to accept the project when investment is feasible in two years. Payback period and Internal Rate of Return is done and the conclusion is investment feasible in two years. Sensitivity analysis is also done to support decision making due to maintenance cost and operator adjustment cost, in example: operator training cost, are unknown. Decision will not change when maintenance cost is 100 percent of operation cost and operator adjustment cost is 96 percent of initial investment cost.
