Sri Hartanti
Universitas Nahdlatul Ulama Surakarta

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Investment Feasibility Analysis of Automated Guided Vehicles Using Return on Assets (ROA) Approach for Material Handling Cost Reduction Sri Hartanti; Muflikhul Amin; Randy Sutopo; Agus Dwi Setiyono
Airlangga Journal of Innovation Management Vol. 7 No. 2 (2026): Airlangga Journal of Innovation Management
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/ajim.v7i2.87618

Abstract

Increased production volumes and higher demands for operational efficiency have prompted PT X to reduce its reliance on manual material handling activities, as such practices lead to time waste, human error, and disruptions in material flow. These conditions have driven manufacturing industries to transition toward automation technologies. One widely adopted automation solution is the Automated Guided Vehicle (AGV). However, the implementation of AGVs requires a relatively high initial investment, making a comprehensive investment feasibility analysis essential to ensure that the transition delivers sustainable benefits. This study aims to analyze the investment feasibility of implementing AGVs in the material handling system using a Return on Assets (ROA) approach based on operational cost savings. The research employs a quantitative analysis by comparing total investment and maintenance costs with the financial benefits derived from labor cost reductions over the analysis period, while also considering annual increases in benefit values due to inflation. The results indicate that the implementation of AGVs generates cumulative operational cost savings that exceed the total investment cost, with the investment payback period achieved in 2031. This finding shows that AGV investment is financially feasible in the long term. The main conclusion of this study is that AGV implementation contributes significantly to cost efficiency and process stability in material handling operations. The research implications suggest that these findings can serve as a decision-making basis for management in planning investments in automation technologies.