Toward Autonomous Systems: A Comparative Analytic Hierarchy Process Evaluation of Diesel, Electric, and Autonomous Forklifts

With the rise of autonomous systems in intralogistics, the integration of intelligent technologies into material handling processes is becoming increasingly important in terms of efficiency, sustainability and safety. Forklift systems, one of the main tools of material handling processes, are evolving from traditional diesel and electric models to autonomous systems that can operate without the need for human intervention. This study aims to comparatively evaluate diesel, electric and autonomous forklift systems in terms of technical, economic and environmental criteria. Six main criteria were considered in the decision-making process: annual operating cost, purchase price, operational efficiency, product efficiency, lift height and carbon emissions. The weights of the criteria and the evaluation of the alternatives were carried out with the Analytic Hierarchy Process (AHP) method. The required technical data were obtained from manufacturer catalogs and operational scenario analysis. The findings show that although conventional forklifts maintain their superiority in some technical parameters, autonomous forklifts stand out as the most suitable alternative with the advantages of low labor cost, reduced carbon emissions and high uptime. This study aims to provide a structured selection process for decision makers in smart industrial environments and contribute to more sustainable investments.