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Fleet Sizing of Automated Material Handling UsingSimulation ApproachTo cite this article: Radinal Wibisono et al 2018 IOP Conf. Ser.: Mater. Sci. Eng. 319 012030

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The 4th Asia Pacific Conference on ManufacturingSystems and the 3rd International ManufacturingEngineering ConferenceTo cite this article: 2018 IOP Conf. Ser.: Mater. Sci. Eng. 319 011001


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APCOMS-IMEC2017 IOP Publishing

IOP Conf. Series: Materials Science and Engineering 319 (2018) 011001 doi:10.1088/1757-899X/319/1/011001

FOREWORDS

It is a great honor for Bandung Intitute of Technology (ITB) in collaboration with Universiti Malaya Pahang to host the second joint conference of The The 4th Asia Pacific Conference on Manufacturing Systems and The 3rd International Manufacturing Engineering Conference (APCOMS-iMEC 2017) at Yogyakarta. The special region that is very important to history of our country, Indonesia. It is also a great honor for ITB to work along with Sebelas Maret University in organizing APCOMS-iMEC 2017 locally in Yogyakarta. We sincerely express our gratitude to Vice Chancellor of UMP; Dean of Sebelas Maret University; Professor Zahari Taha from the Fakulti Kejuruteraan Pembuatan Universiti Malaysia Pahang; The Head Secretary of The Creative Economy Agency of Indonesia (BEKRAF), Doctor Mesdin Simarmata; Professor Shih-Ming Wang, from Mechanical Engineering Department of Chung-Yuan Christian University, and; All parties, which have been very supportive to holding this conference in Indonesia and being part of our important milestone. To date, we are witnessing another revolution of industrial development. The internet of things era has lead the change on consumer behavior, innovate production system technology, transform global manufacturing network. All of these may reshape our future. Our conference theme is about “Taking The Factories to The Next Level”. All technologies which may bring the seamless integration (vertically-horizontally) within or between manufacturers are the hot topics to realize the concept of Industry 4.0. The current requirement analysis and future plan for a country within Asia Pacific will be needed accordingly. On behalf of Bandung Institute of Technology, I encourage all participants of APCOMS-iMEC to work together and contribute to the future development of Manufacturing Technologies to strengthening and harmonizing as well the competitiveness of Asia Pacific countries and for our better society. We wish all participants to have an excellent conference, expand our academic network, and enjoy the historical city of Yogyakarta. Bandung, December 2017 The APCOMS-iMEC 2017 Organizing Committee [email protected]

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COMMITTEE Chair: Dr. Mohammad Mi`radj Isnaini Co-Chairs: Prof. Abdul Hakim Halim

Prof. Dradjad Irianto Assoc. Professor Dr. Ahmad Razlan Yusoff Dr. Muhammed Nafis Osman Zahid

Steering and Organizing Committee: Dr. Anas Ma`ruf Prof. Bermawi Priyatna Iskandar Mr. Fariz Muharram Hasby Dr. Iwan Inrawan Wiratmadja Mr. Muhammad Akbar Dr. Rachmawati Wangsaputra Dr. Sukoyo Dr. TMA. Ari Samadhi Mr. Wildan Trusaji Dr. Wisnu Aribowo

Dr Ahmad Shahrizan Abdul Ghani Prof. Dato' Dr. Daing Nasir Ibrahim Assoc. Prof. Dr. Ismed Iskandar Dr. Mohd Azmir Mohd Azhari Mr. Mohd Khairulnazri bin Saidi Dr. Nafrizuan Mat Yahya Prof. Ir. Dr. Wan Azhar Wan Yusoff Dr. Zamzuri Hamedon Mr. Zulkifli Md. Yusof Ms. Zuryaty binti Zol

Local-Organizing Committee from Sebelas Maret University: Dr. Cucuk Nur Rosyidi Mr. Pringgo Widyo Laksono Mr. Wakhid Ahmad Jauhari Ms. Aditya Isnaini Setyargo P Mr. Aldy Fajrianto Ms. Anida Norma Cahyani Ms. Endah Budiningsih Ms. Fathin Kusumo Pramesti Ms. Fitri Nur Muqodimah Ms. Intan Dewi Melinda

Mr. Iqbal Wahyu Saputra Mr. Kuncoro Sakti Pambudi Ms. Kusumaningtyas Tika Mr. Nurrudin Baidowi Ms. Octavia Riskadayanti Mr. Seamus Tadeo Marpaung Ms. Shanella Nestri Hapsari Ms. Stephani Diesya Floratiara Ms. Viny Sartika Ms. Yuka Sato

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INTERNATIONAL SCIENTIFIC COMMITTEE Prof. A.K. Prasada Rao (BML Munjal University, ID) Prof. Abdul Hakim Halim (Bandung Institute of Technology, ID) Prof. Ahsan Ali Khan (International Islamic University Malaysia, MY) Dr. Amelia Santoso (University of Surabaya, ID) Prof. (Anthony) Shun Fung CHIU (De La Salle University, PH) Prof. Bermawi Priyatna Iskandar (Bandung Institute of Technology, ID) Prof. Che Hassan Che Haron (National University of Malaysia, ID) Dr. Cucuk Nur Rosyidi (Sebelas Maret University, ID) Dr. Delia J. Valles-Rosales (New Mexico State University, US) Prof. Dradjad Irianto (Bandung Institute of Technology, ID) Dr. Dida Diah Damayanti (Telkom University, ID) Dr. Docki Saraswati, M.Eng (Trisakti University, ID) I Made Dana Tangkas, M.Si. (Institut Otomotif Indonesia, ID) Prof. I.S. Jawaher (University of Kentucky, US) Prof. Ir. Isti Surjandari P., MT., Ph.D (University of Indonesia, ID) Dr. Iwan Inrawan Wiratmadja (Bandung Institute of Technology, ID) Prof. Kai Cheng (Brunel University London, UK) Prof. Katsuhiko Takahashi (Hiroshima University, JP) Prof. Mani Maran Ratnam (University of Sciences Malaysia, MY) Prof. Mohd. Adzir b. Mahdi (Universiti Putra Malaysia, MY) Prof. Musa Mailah (Universiti Teknologi Malaysia, MY) Dr. Muhammad Dirhamsyah (Syiah Kuala University, ID) Prof. Niel D Sims (University of Sheffield, UK) Prof. Nik Abdullah Nik Mohamed (Universiti Malaysia Pahang, MY) Dr. Nilda Tri Putri (University of Andalas, ID) Dr. Nur Indriati (UPN `Veteran` Yogyakarta, ID) Prof. Osman Tokhi (London South Bank University, UK) Prof. Raden Chairul Saleh (Islamic University of Indonesia, UD) Prof. Robert Weiss (Karlsruhe University of Applied Sciences, DE) Prof. Saleem Hashimi, (Dublin City University, GB) Prof. Shamsuddin Baharin (Universiti Malaysia Pahang, MY) Prof. Shamsuddin Sulaiman (Universiti Putra Malaysia, MY) Dr. The Jin Ai (Atma Jaya Catholic University of Indonesia, ID) Dr. TMA. Ari Samadhi (Bandung Institute of Technology, ID) Prof. Voratas Kachitvichyanukul, PhD (Asian Institute of Technology, TH) Prof. Wan Azhar Wan Yusoff (Universiti Malaysia Pahang, MY) Prof. Zahari Taha (Universiti Malaysia Pahang, MY)



Peer review statementTo cite this article: 2018 IOP Conf. Ser.: Mater. Sci. Eng. 319 011002


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Peer review statement

All papers published in this volume of IOP Conference Series: Materials Science and Engineering havebeen peer reviewed through processes administered by the proceedings Editors. Reviews were conductedby expert referees to the professional and scientific standards expected of a proceedings journal publishedby IOP Publishing.

6/11/2019 IOP Conference Series: Materials Science and Engineering, Volume 319, 2018 - IOPscience

https://iopscience.iop.org/issue/1757-899X/319/1 1/14

Table of contents

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Accepted papers received: 16 February 2018 Published online: 21 March 2018 Preface

Papers

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Volume 3192018

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The 4th Asia Pacific Conference on Manufacturing Systems and the 3rd InternationalManufacturing Engineering Conference 7–8 December 2017, Yogyakarta, Indonesia

011001OPEN ACCESS

The 4th Asia Pacific Conference on Manufacturing Systems and the 3rd InternationalManufacturing Engineering Conference

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011002OPEN ACCESS

Peer review statement View article PDFView abstract

012001OPEN ACCESS

e-Learning Content Design for Corrective Maintenance of Toshiba BMC 80.5 based onKnowledge Conversion using SECI Method: A Case Study in Aerospace CompanyAyu Permata Shabrina, Rayinda Pramuditya Soesanto, Amelia Kurniawati, Mochamad Teguh Kurniawan andLuciana Andrawina

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Effect of laser parameters on surface roughness of laser modified tool steel after thermalcyclic loadingAnnie Lau Sheng, Izwan Ismail and Syarifah Nur Aqida


012003OPEN ACCESS

Game-Theoretic Models for Usage-based Maintenance ContractH Husniah, R Wangsaputra, A Cakravastia and B P Iskandar


012004OPEN ACCESS

Assembly Line Efficiency Improvement by Using WITNESS Simulation SoftwareA S H M Yasir and N M Z N Mohamed


012005OPEN ACCESS

Bridging Technometric Method and Innovation Process: An Initial StudyA A Rumanti, R Reynaldo, T M A A Samadhi, I I Wiratmadja and A C Dwita


012006OPEN ACCESS

Development of hydropower sustainability assessment method in Malaysia contextFaiz Mohd Turan, Kartina Johan and Nur Atiqah Omar


012007OPEN ACCESS

A new framework for sustainable hydropower development projectKartina Johan, Faiz Mohd Turan and Nur Syazwani Abdul Gani


012008OPEN ACCESS

Characteristic and Competency Measurement Instrument Development for MaintenanceStaff of Mechanical Expertise with SECI Method: A Case of Manufacturing CompanyP A Mahatmavidya, R P Soesanto, A Kurniawati and L Andrawina


012009OPEN ACCESS


































Success Measures Evaluation for Mobile Commerce Using Text Mining based on Customer TweetsA A Habib and R Govindaraju


012010OPEN ACCESS

Investigation of roughing machining simulation by using visual basic programming in NXCAM systemMohamad Hafiz Mohamad and Muhammed Nafis Osman Zahid


012011OPEN ACCESS

PVA/Graphene Nanocomposite: Morphology and its Thermal PropertiesAbu Hannifa Abdullah, Zulhelmi Ismail, Anis Sakinah Zainal Abidin, Fadwa Sameeha Ismail and Kamal Yusoh


012012OPEN ACCESS

Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and ParticleSwarm OptimizationNur Iffah Mohamed Azmi, Kamal Arifin Mat Piah, Wan Azhar Wan Yusoff and Fadhlur Rahman Mohd Romlay


012013OPEN ACCESS

Design for Warehouse with Product Flow Type Allocation using Linear Programming: A CaseStudy in a Textile IndustryM S A Khannan, L Nafisah and D L Palupi


012014OPEN ACCESS

Development of Product Availability Monitoring System In Production Unit In AutomotiveComponent IndustryRachmad Hartono, Sri Raharno, Yatna Yuwana Martawirya and Bagus Arthaya


012015OPEN ACCESS

Modeling of Geometric Error in Linear Guide Way to Improved the vertical three-axis CNCMilling machine's accuracyWidiyanti Kwintarini, Agung Wibowo, Bagus M Arthaya and Yatna Yuwana Martawirya


012016OPEN ACCESS































Preliminary Development of Real Time Usage-Phase Monitoring System for CNC Machine Tools with aCase Study on CNC Machine VMC 250Herman Budi Harja, Tri Prakosa, Sri Raharno, Yatna Yuwana Martawirya, Indra Nurhadi and Alamsyah SetyoNogroho


012017OPEN ACCESS

Integrated multi sensors and camera video sequence application for performancemonitoring in archeryZahari Taha, Jessnor Arif Mat-Jizat, Muhammad Amirul Abdullah, Rabiu Muazu Musa, Mohamad Razali Abdullah,Mohamad Fauzi Ibrahim and Mohd Ali Hanafiah Shaharudin


012018OPEN ACCESS

Reverse engineering of wörner type drilling machine structure.A Wibowo, I Belly, R llhamsyah, Indrawanto and Y Yuwana


012019OPEN ACCESS

Effect of Processing Variables on Tensile Modulus and Morphology of Polyethylene/ClayNanocomposites Prepared in an Internal MixerO Ujianto, M Jollands and N Kao


012020OPEN ACCESS

Reliability Centred Maintenance (RCM) Analysis of Laser Machine in Filling Lithos at PT XM A E Suryono and C N Rosyidi


012021OPEN ACCESS

A Goal Programming Optimization Model for The Allocation of Liquid Steel ProductionS N Hapsari and C N Rosyidi


012022OPEN ACCESS

Preparation of tin oxide (SnO ) thin films using thermal oxidationN Abdullah, N M Ismail and D M Nuruzzaman

2


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Influence of groove size and reinforcements addition on mechanical properties and microstructure offriction stir welded jointsRavinder Reddy Baridula, Abdullah Bin Ibrahim, Che Ku Mohammad Faizal Bin Che Ku Yahya, Ratnakar Kulkarniand Ramgopal Varma Ramaraju


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Design logistics performance measurement model of automotive component industry forsrengthening competitiveness of dealing AEC 2015T G Amran and Mindy Janitra Yose


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PSO-based PID Speed Control of Traveling Wave Ultrasonic Motor under TemperatureDisturbanceKamal Arifin Mat Piah, Wan Azhar Wan Yusoff, Nur Iffah Mohamed Azmi and Fadhlur Rahman Mohd Romlay


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Six Sigma Approach to Improve Stripping Quality of Automotive Electronics Component – acase studyNoraini Mohd Razali, Siti Murni Mohamad Kadri and Toh Con Ee


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The identification of high potential archers based on relative psychological coping skillsvariables: A Support Vector Machine approachZahari Taha, Rabiu Muazu Musa, A P P Abdul Majeed, Mohamad Razali Abdullah, Muhammad Aizzat Zakaria,Muhammad Muaz Alim, Jessnor Arif Mat Jizat and Mohamad Fauzi Ibrahim


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Failure Behaviour of Aluminium/CFRP Laminates with Varying Fibre Orientation in Quasi-static Indentation Test




























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012030OPEN ACCESS

Fleet Sizing of Automated Material Handling Using Simulation ApproachRadinal Wibisono, The Jin Ai and Deny Ratna Yuniartha


012031OPEN ACCESS

Analysis of Container Yard Capacity In North TPK Using ARIMA MethodSirajuddin, M Cut Gebrina Hisbach, Ratna Ekawati and SM Ade Irman


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Investigation on the effect of Friction Stir Processing Parameters on Micro-structure andMicro-hardness of Rice Husk Ash reinforced Al6061 Metal Matrix CompositesN Fatchurrohman, N Farhana and C D Marini


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A feasibility study in adapting Shamos Bickel and Hodges Lehman estimator into T-Methodfor normalizationN Harudin, K R Jamaludin, M Nabil Muhtazaruddin, F Ramlie and Wan Zuki Azman Wan Muhamad


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Work-related musculoskeletal disorders (WMDs) risk assessment at core assemblyproduction of electronic components manufacturing companyN M Yahya and M N O Zahid
































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A Multiple Items EPQ/EOQ Model for a Vendor and Multiple Buyers System withConsidering Continuous and Discrete Demand SimultaneouslyJonrinaldi, T Rahman, Henmaidi, E Wirdianto and D Z Zhang


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An integer batch scheduling model considering learning, forgetting, and deteriorationeffects for a single machine to minimize total inventory holding costR Yusriski, Sukoyo, T M A A Samadhi and A H Halim


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Optimization of Coolant Technique Conditions for Machining A319 Aluminium Alloy UsingResponse Surface Method (RSM)S Zainal Ariffin, A Razlan, M Mohd Ali, A M Efendee and M M Rahman


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Taguchi experimental design to determine the taste quality characteristic of candied carrotY Ekawati and A A Hapsari


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Performance Analysis of Abrasive Waterjet Machining Process at Low PressureM Murugan, MA Gebremariam, Z Hamedon and A Azhari


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Simulation on Effect of Preform Diameter in Injection Stretch Blow MoldingZ Q Tan, Nurrina Rosli and Muchamad Oktaviandri


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Study on the effectiveness of Extreme Cold Mist MQL system on turning process of stainlesssteel AISI 316A S Jamaludin, A Hosokawa, T Furumoto, T Koyano and Y Hashimoto


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Control of wheeled mobile robot in restricted environmentMohammed A H Ali and Chang Yong En


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Cost viability of 3D printed house in UKA L Mohd Tobi, S A Omar, Z Yehia, S Al-Ojaili, A Hashim and O Orhan


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Laser surface modification of Yttria Stabilized Zirconia (YSZ) thermal barrier coating on AISIH13 tool steel substrateM S Reza, S N Aqida and I Ismail


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Fleet Sizing of Automated Material Handling Using

Simulation Approach

Radinal Wibisono, The Jin Ai*, Deny Ratna Yuniartha

1Department of Industrial Engineering, Universitas Atma Jaya Yogyakarta, Indonesia

*[email protected]

Abstract. Automated material handling tends to be chosen rather than using human power in

material handling activity for production floor in manufacturing company. One critical issue in

implementing automated material handling is designing phase to ensure that material handling

activity more efficient in term of cost spending. Fleet sizing become one of the topic in designing

phase. In this research, simulation approach is being used to solve fleet sizing problem in flow

shop production to ensure optimum situation. Optimum situation in this research means

minimum flow time and maximum capacity in production floor. Simulation approach is being

used because flow shop can be modelled into queuing network and inter-arrival time is not

following exponential distribution. Therefore, contribution of this research is solving fleet sizing

problem with multi objectives in flow shop production using simulation approach with ARENA

Software

Keywords: Automated material handling, Fleet sizing, ARENA Software, Queuing theory, Flow

shop, Simulation

1. Introduction

Currently, manufacturing company has to face tight competition with many competitors. Company try

to have lower price for their products compared to another competitor but still maintain or even higher

profit level. The ultimate way to reach the objective is lower the cost to perform an enterprise in form

of manufacturing and administration activity. It is well known that lean principle can be applied to

response this issue, i.e. eliminating seven waste in the company [1], including transportation waste.

A case study is presented here, in which a manufacturing company tried to minimize its material

handling cost by automating material handling in production floor. Automated Guided Vehicle (AGV)

is the most popular solution in automated material handling in manufacturing due to many advantages

over human power in material handling activity [2-4]. However, this company decided to implement a

simple type AGV, which is called AGV towing vehicles. The principle is actually the same as AGV in

term of driverless material handling [5] and consists of many parts, such as: DC Motors, sensors to

ensure the safety, wireless communication, and energy sources in form of rechargeable battery [6]. The

difference between them, AGV towing vehicle is simplification of common AGV which are not fully

automated and not flexible as AGV system. It has only two stop points, one is considered as start point

and another is considered as end point. Term usage of start and end point is based on material flow in

production. Start point is stop point to load material that ready to be processed to the next station and

end point is stop point to unload material in the arrival station.

AGV towing vehicle still needs operator to load and unload container manually. The purpose of

AGV towing vehicle is to reduce headcount and prevent human operator fatigue due to far distances and

repetitive transportation activity. This objective is driven by the increasing labor cost, so that

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manufacturing company is forced to reduce workers in production floor and tend to have automated or

semi-automated system in the production activity. Another consideration of using AGV towing vehicle

rather than common AGV is because cheaper investment. Cheaper investment is caused by not all

features in AGV used in AGV towing vehicle system.

In this research, real case study used in manufacturing company which AGV towing vehicle will

be implemented and already in prototype phase. AGV towing vehicle will be implemented to transport

material consecutively from supermarket to X station and from X station to Y station. The layout map

for case study in AGV towing vehicle systems implementation can be seen in Figure 1.

Figure 1. Layout Map

AGV towing vehicle can be said as automation in manufacturing process in term of material

handling. As automation, designing the system is a critical phase to ensure that production system is

optimized. It is critical because main reason of automation is actually to improve previous process in

term of cost spending and ensure that AGV towing vehicle usage is to eliminate and not adding any

waste in previous process. AGV towing vehicle also should not become a bottleneck in production or

make production capacity reduced. This research is important because appropriate number of AGV

towing vehicle can have minimum flow time of material.

2. Simulation Model

In order to imitate how the system works, a simulation model is developed using ARENA software. The

description of the model is presented below, while the whole model is available in Figure 2. It is noted

that the key decision variables to be taken in this situation are number of AGV towing vehicle to be

placed in phase one (between supermarket and X station) and number of AGV towing vehicle to be

placed in phase two (between X station and Y station).

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Figure 2. Complete Model in ARENA Software

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In the phase one, start point is supermarket and end point is X station. There will be two entities

involved in start point, which are empty entities and filled entities. If entity that arrived is empty,

operator should unload it first from AGV towing vehicle before it ready to transport another entity. After

that empty entities will disposed or exit the system. If it is filled entities arrived, AGV towing vehicle

will be requested first before operator can load entities. Filled entities will be departing to X station. End

point in phase one is X station. Filled entities will come first from supermarket to X start station and

operator need to unload filled entities before AGV towing vehicle ready to use again. After filled entities

being unloaded, it will be transported to X station and processed in the station. If filled entities already

processed, two entities will be occurred which are empty entities to reuse in previous process and filled

entities to be transported to Y station. Empty entities will be transported to X station start point. After

that, AGV towing vehicle is requested and operator load it to AGV towing vehicle after it is available.

In the end, empty entities leave X station start point and go to supermarket. Another model made in

phase one is to generate filled entities to the system. Assumption of supermarket concept in lift should

be considered because systems only generate new filled entities when X station needs it. Unfortunately,

create module in ARENA Software cannot generate new entities based on conditions. It is only based

on schedule or expression of time distribution. Therefore, decide module is placed after create module

to create appropriate model to represent pull system between supermarket to X station.

In phase two, start point is X station and end point is Y station. There will be two entities in X

station which are filled entities that ready to be transported to Y station and empty entities that will be

reuse in X station. If empty entities arrived to X station, operator will unload the empty entities so AGV

towing vehicle will be ready to transport again. Empty entities will be disposed so X station can reuse

it again. If it is filled entities arrived, AGV towing vehicle will be requested. After AGV towing vehicle

requested, operator load filled entities and AGV towing vehicle will leave to Y station. End point in

phase two is Y station. There are three entities involved in end point, which are empty entities, filled

entities, and final product. Filled entity is arrived in Y station and operator should unload from AGV

towing vehicle first before it is ready to transport another entity. After filled entities being unloaded,

operator transports it to Y station line and being processed in Y station. The outputs are final product

and empty entities. Final product will exit the system or disposed and empty entities will be transported

first to end point of AGV towing vehicle system. Empty entities will be transported to X station again

for reuse. Therefore, AGV towing vehicle will be requested first and operator load empty entities to

AGV towing vehicle before it leave Y station to X station.

Time data are collected from the system in order to qualitatively model the system, which are the

operator time to: (1) load AGV towing vehicle, (2) unload AGV towing vehicle, (3) transport to Y

station, (4) transport from Y station, (5) transport to X station, (6) transport from X station. The mean

of these times are (1) 6.60 seconds, (2) 5.56 seconds, (3) 20.94 seconds, (4) 20.15 seconds, (5) 32.46

seconds, and (6) 30.00 seconds, respectively. Moreover, the processing cycle time at X and Y stations

are also being observed. It is statistically proven that the distribution of processing cycle time at X station

is triangular distribution with minimum value is 5 seconds, mode is 5.12 seconds, and maximum value

is 136 seconds. While, the distribution of processing cycle time at Y station is beta distribution with

parameter α = 0.655 and β = 1.48. Experiment from the AGV towing vehicle prototype is showed that

the cycle time for AGV towing vehicle for phase one and two are 315 seconds and 220 seconds,

respectively. For the AGV towing vehicle, cycle time means time needed for the vehicle departs from

start point and arrives again in start point.

3. Result and Discussion

Preliminary simulation runs indicate that 80 replications are required for fulfilling desired precision.

The alternative of number of AGV towing vehicle to be placed in phase one is 6 – 9 vehicles and number

of AGV towing vehicle to be placed in phase two is 8 – 9 vehicles. Therefore, 8 combination of scenario

are tested. Flow time and daily production volume are recorded as the system performances. Average

performances of each scenario from all replications are presented in Table 1.

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Table 1. Simulation Results

Scenario Phase One

Vehicles

Phase Two

Vehicles

Flow Time

(minutes)

Production

Volumes (units)

1 6 8 18.8 1676

2 6 9 17.9 1671

3 7 8 18.8 1674

4 7 9 18.5 1677

5 8 8 18.7 1678

6 8 9 18.0 1676

7 9 8 18.1 1680

8 9 9 17.9 1676

It is shown in Table 1 that the results are quite similar among scenarios, i.e. increasing number of

AGV towing vehicles is not having any significance difference in flow time and production volume.

Therefore, statistical analysis is required in order to ensure that the performance among scenarios can

be considered as statistically same. One-way ANOVA is applied here, with the null hypothesis: all the

mean flow time (or the mean production volume) are similar, versus the alternate hypothesis: at least

one mean is different. The results of the ANOVA test for flow time and production volume in MINITAB

software are presented in Figure 3 and 4, respectively. Since the p-value is greater than α (i.e. α=0.05),

therefore, in both hypothesis testing we failed to reject null hypothesis. In other words, there are no

statistical evidence that the flow time and production volume are different among scenarios.

Based on these performance analysis, it is recommended that the company use only 6 vehicles in

the phase one and 8 vehicles in the phase two. By using this recommendation, the company can save the

investment for acquiring the vehicles, while the performance of the system is not significantly different

with the system at higher number of vehicles.

Figure 3. ANOVA Results on Flow Time

Figure 4. ANOVA Results on Production Volume

4. Conclusion

In order to solve the optimization problem for determining optimum number of AGV towing vehicle

used in production floor, a simulation model is developed using ARENA software. Using standard

simulation methodology, i.e. input analysis, experiment, and output analysis, the situation of smaller

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material flow time and higher production volume is reached with six AGV towing vehicles in the phase

one and eight AGV towing vehicles in the phase two.

References

[1] Marchwinski C and Shook J 2003 Lean Lexicon: a Graphical Glossary for Lean Thinkers

[2] Lin L, Shinn SW, Gen M and Hwang H 2006 Journal of Intelligent Manufacturing 17 465–77

[3] Shneor R, Berman S and Edan Y 2006 Applied Soft Computing Technologies: The Challenge of

Complexity 749–60.

[4] Leite LFV, Esposito RMA, Vieira AP and Lima F 2015 Independent Journal of Management &

Production 6 269–85

[5] Fazlollahtabar H and Saidi-Mehrabad M 2015 Journal of Intelligent & Robotic Systems 77 525–

45

[6] Zajac J, Slota A, Krupa K, Wiek T, Chwajol G and Małopolski W 2013 Applied Mechanics and

Materials 282 59–65

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