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Dedi Purwanto Indra Kusuma
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RESWARA: Jurnal Riset Ilmu Teknik
Published by Lembaga Penelitian dan Pendidikan (LPP) Kalibra
ISSN : -     EISSN : 30259444     DOI : https://doi.org/10.70716/reswara
Core Subject : Engineering,
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering Transportation
RESWARA: Jurnal Riset Ilmu Teknik is a leading scholarly platform that examines the strategic role of engineering disciplines in advancing the Sustainable Development Goals (SDGs). The journal is dedicated to publishing recent research, innovations, and engineering solutions that support sustainable development. The editorial board welcomes manuscripts based on theoretical frameworks and empirical research. The journal scope covers scientific knowledge and research-based information, including applied research and recent developments in engineering research and development. The primary focus includes Civil Engineering and Spatial Planning, Industrial Engineering, Electrical Engineering and Informatics, Earth Science Technology, and Naval Architecture. All manuscripts published in RESWARA undergo a double-blind peer review process. The final decision on manuscript acceptance rests with the Editorial Board, based on recommendations from independent peer reviewers.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 55 Documents
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Experimental Study of Wear Behavior on Composite Materials under Dry Sliding Conditions Borneo, Aisyah Noor; Hartono, Daniel Sebastian
RESWARA: Jurnal Riset Ilmu Teknik Vol. 3 No. 3 (2025): RESWARA: Jurnal Riset Ilmu Teknik, July 2025
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/reswara.v3i3.426

Abstract

Dry sliding wear significantly influences the service life of composite materials used in automotive, aerospace, and marine engineering applications. This study presents a comparative experimental investigation of dry sliding wear behavior in various polymer matrix composites and metal matrix composites reported in recent literature. The objective of this study is to synthesize and critically analyze wear trends, dominant mechanisms, and the influence of reinforcement type, load, sliding speed, and filler content on tribological performance. A systematic experimental review methodology was applied by extracting quantitative and qualitative wear data from peer-reviewed journals and classifying them based on material system and test parameters. The analysis shows that hybrid reinforcement systems, such as Si₃N₄–graphite in aluminum matrices and carbon nanotube–alumina in epoxy matrices, consistently exhibit lower wear rates than single-reinforcement systems. Solid lubricants such as graphite and h-BN significantly reduce friction coefficients, while fiber orientation and filler percentage strongly influence wear mechanisms. The findings indicate that optimized hybrid composites can achieve up to 25–40% improvement in wear resistance compared to monolithic materials. This study contributes a structured synthesis of experimental tribological results and provides guidelines for material selection and parameter optimization in dry sliding applications.
Mechanical Properties Analysis of Aluminum Alloy with Heat Treatment Variation Prabowo, Dimas Aditya; Dewanti, Rina Kusuma
RESWARA: Jurnal Riset Ilmu Teknik Vol. 3 No. 3 (2025): RESWARA: Jurnal Riset Ilmu Teknik, July 2025
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/reswara.v3i3.448

Abstract

Heat treatment plays a critical role in controlling the mechanical performance of aluminum alloys used in structural, automotive, and aerospace applications. Variations in solution treatment, aging temperature, holding time, and cooling rate significantly influence strength, hardness, and ductility. This study aims to analyze the mechanical properties of aluminum alloys under different heat treatment conditions through a systematic synthesis of experimental findings reported in recent peer reviewed literature. The research applies a qualitative comparative method by examining tensile strength, hardness, fatigue resistance, and microstructural evolution across multiple aluminum alloy series, including 6xxx, 7xxx, and Al-Si based alloys. The results indicate that optimized heat treatment parameters consistently enhance mechanical properties, with tensile strength improvements ranging from 20 percent to over 50 percent depending on alloy composition and treatment route. Excessive aging or improper quenching, however, leads to strength degradation and reduced ductility. Comparative analysis confirms that precipitation hardening and controlled grain refinement are the dominant mechanisms governing performance improvement. This study provides a consolidated technical reference for selecting heat treatment parameters to achieve targeted mechanical properties in aluminum alloys and supports process optimization in industrial manufacturing.
Design and Analysis of Smart Grid Systems for Improved Energy Reliability Arsyad, Andi Muhammad; Firdaus, La Ode Ahmad
RESWARA: Jurnal Riset Ilmu Teknik Vol. 3 No. 4 (2025): RESWARA: Jurnal Riset Ilmu Teknik, October 2025
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/reswara.v3i4.449

Abstract

The increasing complexity of modern power systems and the growing penetration of renewable energy sources have made energy reliability a critical challenge in smart grid development. Smart grids integrate advanced information, communication, and control technologies to enhance system flexibility, efficiency, and resilience. This study aims to design and analyze smart grid systems with a specific focus on improving energy reliability through cyber-physical integration, intelligent monitoring, and advanced optimization techniques. A systematic literature-based analytical method was employed, synthesizing findings from recent journal articles and conference proceedings related to smart grid reliability, artificial intelligence, Internet of Things integration, and cyber-power interdependencies. The results indicate that the incorporation of intelligent sensing, real-time data analytics, AI-driven optimization, and robust communication architectures significantly enhances reliability indices such as SAIFI and SAIDI while reducing outage durations and cascading failure risks. Furthermore, the analysis highlights that holistic reliability modeling considering both cyber and physical layers provides more accurate and resilient system designs. This study contributes a comprehensive design-oriented perspective that integrates technological, analytical, and managerial dimensions of smart grid reliability. The findings are expected to support policymakers, system planners, and researchers in developing reliable and sustainable smart grid infrastructures.
Implementation of Internet of Things for Predictive Maintenance in Manufacturing Industry Pratama, Rizky Adi; Collins, James Andrew
RESWARA: Jurnal Riset Ilmu Teknik Vol. 3 No. 3 (2025): RESWARA: Jurnal Riset Ilmu Teknik, July 2025
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/reswara.v3i3.450

Abstract

The rapid advancement of Industry 4.0 has accelerated the adoption of Internet of Things (IoT) technologies in manufacturing systems, particularly in predictive maintenance applications. Traditional maintenance strategies, such as corrective and preventive maintenance, often result in unplanned downtime, increased operational costs, and inefficient resource utilization. This study aims to analyze and synthesize recent scientific literature on the implementation of IoT-based predictive maintenance in the manufacturing industry, focusing on system architecture, data acquisition, analytics techniques, and operational impacts. A qualitative systematic literature review method was employed, analyzing peer-reviewed journal articles, conference proceedings, and book chapters published between 2020 and 2025. The findings indicate that IoT-enabled predictive maintenance significantly improves equipment reliability, reduces downtime by up to 50%, lowers maintenance costs, and enhances production efficiency. The integration of machine learning, edge computing, and digital twin technologies further strengthens real-time decision-making and failure prediction accuracy. This study contributes by providing a comprehensive and structured understanding of IoT-driven predictive maintenance implementations and identifying research gaps related to scalability, data interoperability, and cybersecurity. The results serve as a reference for both researchers and practitioners seeking to adopt predictive maintenance solutions in smart manufacturing environments.
Thermodynamic Analysis of Refrigeration Systems Using Eco-Friendly Refrigerants Rahman, Siti Nur Aisyah; Smith, Michael Jonathan
RESWARA: Jurnal Riset Ilmu Teknik Vol. 3 No. 4 (2025): RESWARA: Jurnal Riset Ilmu Teknik, October 2025
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/reswara.v3i4.451

Abstract

The global transition toward environmentally sustainable refrigeration systems has intensified research on eco-friendly refrigerants with low global warming potential and zero ozone depletion potential. Conventional refrigerants such as R22 and R134a are increasingly restricted due to their adverse environmental impacts. This study presents a systematic thermodynamic analysis of refrigeration systems operating with eco-friendly refrigerants, based on an extensive synthesis of recent peer-reviewed literature. The research evaluates system performance using first and second law analyses, focusing on key indicators such as coefficient of performance, exergy efficiency, entropy generation, and environmental impact metrics. The methodological approach integrates comparative analysis across single-stage, cascade, and multi-evaporator refrigeration configurations employing hydrofluoroolefins, hydrocarbons, carbon dioxide blends, and emerging nano-refrigerants. The results indicate that refrigerants such as R290, R1234yf, R1234ze, and R744-based mixtures consistently demonstrate superior energy and exergy performance compared to conventional fluids. Cascade and multi-stage systems further enhance performance under ultra-low temperature applications. The study confirms that eco-friendly refrigerants can achieve both thermodynamic efficiency and environmental sustainability. These findings provide a robust scientific basis for refrigerant selection and system design in future refrigeration and air-conditioning applications.

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