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All Journal Sinergi International Journal of Sustainable Building, Infrastructure and Environment
Supriyono, Joko
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Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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TE-LSTM: winding temperature prediction for induction motors in the oil and gas industry Supriyono, Joko; Mukhlash, Imam; Iqbal, Mohammad; Asfani, Dimas Anton
SINERGI Vol 29, No 3 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.3.022

Abstract

Induction motor winding failure repair takes longer compared to other failures, such as bearing failure. This research introduces a hybrid deep learning framework, TE-LSTM, to predict winding temperatures in induction motors used in oil and gas operations, aiming to address the challenges of accurately forecasting potential winding failures and enabling proactive maintenance strategies. The TE-LSTM model combines a transformer encoder-based architecture with long short-term memory to effectively model intricate temporal relationships and sensor dynamics within the dataset. The study utilized data collected from January 2016 to December 2024 at 1-minute intervals from induction motors equipped with stator winding temperature sensors, where the motors were designed with Class F insulation and had stage 1 and stage 2 alarms set at 257°F and 285°F, respectively. The findings highlight the efficiency and performance of the TE-LSTM model in predicting winding temperatures, which can significantly reduce unplanned downtime and associated costs, thereby optimizing maintenance operations and enhancing the reliability of the motor.
COST EFFICIENCY ANALYSIS AND RISK MANAGEMENT OF THE SELF-MANAGED BATCHING PLANT METHOD MUSI TOLL KAYU AGUNG-PALEMBANG-BETUNG BRIDGE PROJECT Supriyono, Joko; Kristiawan, Agung; Ramadhani, Vicha Silviana; Suwandi, Putri Anggi Permata
International Journal of Sustainable Building, Infrastructure and Environment (IJOSBIE) Vol 7, No 1 (2026)
Publisher : Science and Technology Research Centre, Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/ijosbie.v7i1.27063

Abstract

This study was conducted on the Musi Bridge Project of the Kayu Agung–Palembang–Betung Toll Road to determine the most efficient and controlled concrete supply method, considering the high proportion of concrete costs, potential distribution delays, and structural quality requirements in strategic infrastructure projects. The research aimed to compare the self-managed batching plant method and the ready-mix method in terms of cost efficiency, technical and non-technical risks, and concrete quality performance. A quantitative descriptive-comparative approach was applied using primary data from project documents, including cost summaries, material quantities and prices, job mix formulas, risk matrices, and quality testing reports, supported by field observations. The analysis involved cost calculations, risk scoring and categorization, and evaluation of compliance with technical specifications. The results show that the self-managed method achieved cost savings of 15.7% and lower risk levels compared to the ready-mix method, while both methods met structural quality requirements. Therefore, the study concludes that self-managed batching plants are more effective for large-scale projects when supported by adequate technical and operational capacity. Keywords: concrete supply method, self managed batching plant, ready-mix concrete, cost and risk analysis ;
Co-Authors Agung Kristiawan Dimas Anton Asfani Imam Mukhlash Mohammad Iqbal Ramadhani, Vicha Silviana Suwandi, Putri Anggi Permata