Abstract
This study presents the IoT adoption policy analysis to estimate the benefit of redesigning the maintenance process in a predictive way for the Seoul Metro railway Line two. Accordingly, first, elicit five policy-level IoT deployment schemes for the rolling stock components. Secondly, five process change scenarios corresponding to each of the five schemes are redesigned for the depot maintenance operation. Thirdly, as per the industry-recommended IoT solution deployment analysis methods, simulation analyses using ARENA are conducted for each redesigned process. The simulation analysis assesses the incremental changes in the number of waiting trains for inspection, reduced maintenance manpower requirements, and reduced inspection time. Finally, with reference to the simulation results, the effect of alternative IoT deployment schemes is analyzed, and referenced to derive the plausible optimal level IoT deployment policy. The modelling and simulation procedures presented in this paper offer useful insights into the economic feasibility analysis of the IoT-embedded predictive maintenance area.
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