Analysis of the Electricity Distribution Network Asset Data Management Process at PLN UP3 Sidoarjo Using Bottleneck and PIECES Methods
Analisis Proses Pengelolaan Data Aset Jaringan Distribusi Listrik Di PLN UP3 Sidoarjo Dengan Metode Bottleneck dan PIECES
DOI:
https://doi.org/10.21070/pels.v10i1.3139Keywords:
Asset Data Management, Bottleneck Analysis, PIECES Framework, Electricity Distribution Network, System IntegrationAbstract
General Background Electrical networks distribute energy directly to end-users, requiring meticulous equipment maintenance and reliable information systems to secure continuous operational capability. Specific Background Maintenance strategies depend on precise spatial and operational characteristics, yet technicians frequently must extract this data from disjointed digital infrastructures. Knowledge Gap While independent platforms store critical asset information, the procedural bottlenecks and inefficiencies caused by constantly switching between these fragmented systems during daily operations remain systematically unquantified. Aims This study investigates an asset data management workflow, aiming to identify operational bottlenecks and evaluate system deficiencies across six performance dimensions. Results Observational data demonstrated that a single data management sequence requires 24 minutes to complete. Bottleneck analysis identified that manually recording findings into spreadsheets and repeatedly searching for specific asset data across multiple platforms consumed the most time, requiring five minutes each. Furthermore, evaluating the system using the PIECES framework highlighted significant inefficiencies, specifically concerning repeated data entry, redundant verification procedures, and the lack of a centralized information hub. Novelty This research directly correlates specific time-measured procedural delays with qualitative system deficiencies across multiple disjointed platforms in a public utility environment. Implications Deploying a centralized web interface that aggregates spatial, operational, and fundamental asset data eliminates redundant data entry, accelerates retrieval times, and streamlines maintenance planning.
Highlights:
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Extracting comprehensive asset information requires navigating disjointed platforms, resulting in a 24-minute procedural workflow.
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Manually recording findings into spreadsheets and repeatedly searching multiple platforms consume the most time, requiring five minutes each.
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Aggregating spatial, operational, and fundamental data into a centralized interface eliminates redundant entry and accelerates maintenance planning.
Keywords: Asset Data Management, Bottleneck Analysis, PIECES Framework, Electricity Distribution Network, System Integration
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