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All Journal PROZIMA (Productivity, Optimization and Manufacturing System Engineering)
Ahmad Darmawan Andhika Bakti
Teknik Industri, Departemen Teknik Sistem dan Industri, Institut Teknologi Sepuluh Nopember, Surabaya
Industrial & Manufacturing Engineering

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Development of A Supply Chain Resilience Model For Flood Disasters in PLN Customer Service Unit (ULP) Ahmad Darmawan Andhika Bakti; Iwan Vanany
PROZIMA (Productivity, Optimization and Manufacturing System Engineering) Vol. 10 No. 1 (2026): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/prozima.v10i1.1787

Abstract

Flooding can disrupt electricity distribution systems, particularly within the PLN Customer Service Unit (ULP) operational area, affecting both operational performance and customer service delivery. Therefore, it is important to identify potential disruption events and understand the organizational capabilities needed to improve operational resilience during flood conditions. This study develops a Supply Chain Resilience (SCRes) model for flood-related disruptions that may cause widespread outages within PLN ULPs. The research was conducted in the service area of PT PLN (Persero), Distribution Main Unit of South Sumatra, Jambi, and Bengkulu. This study used a Bayesian Network to analyse how flood-related disruption events are interconnected under uncertain conditions. The probability values generated by the model were then converted into expected values to determine disruption priorities. Afterward, the priority disruptions were mapped to SCRes capabilities to examine which capabilities contribute most to mitigating their impacts. The analysis shows that the most significant disruptions involve increasing customer complaints, delays in operation and maintenance activities, impacts on substations and distribution networks, limited mobility of technical personnel, and longer outage durations. Regarding SCRes capabilities, the most contributive elements are Learning and Improvement Capability, coordination among ULP–UP3–UID during disturbances, and Operational Flexibility. The study also identifies capability gaps for several disruptions that are not optimally mitigated by the current capabilities of PLN.
Co-Authors Iwan Vanany