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This article explores recent advancements in sustainable industrial innovation within the field of mechanical engineering. With the shift towards environmental consciousness, the integration of sustainable practices in manufacturing, energy use, and waste management has become crucial. This paper reviews current trends, emerging technologies, and projected future directions, providing insights into how mechanical engineering can play a pivotal role in fostering sustainable industrial practices.

This study analyzes and optimizes production systems in the Industry 4.0 context, examining the fundamental shift from centralized, push-based production models to decentralized, adaptive, pull-based approaches. The research employs a mixed-method approach combining comprehensive literature review and multiple case studies across manufacturing sectors. Findings reveal that integration of Internet of Things (IoT), cyber-physical systems, artificial intelligence, and big data analytics enables real-time communication between production components, product personalization, and faster decision-making. Despite significant benefits in efficiency, flexibility, and competitiveness, implementation challenges persist, including high initial investment, employee resistance, technical expertise limitations, and integration complexity. Optimization approaches such as mixed-integer linear programming, digitally-integrated Lean Six Sigma, and digital twin simulations effectively enhance performance indicators including flexibility, reliability, and energy efficiency. The study concludes that successful production system transformation requires an integrated strategy encompassing process engineering, digital competency development, change management, and continuous evaluation to ensure sustainable optimization in the digital era

The rapid development of smart city initiatives has significantly increased the adoption of Internet of Things (IoT) technologies to enhance urban services, infrastructure efficiency, and quality of life. However, the large-scale deployment of interconnected IoT devices also introduces critical cybersecurity challenges, including unauthorized access, data breaches, and system vulnerabilities. This study aims to develop an integrated IoT security management model to improve cybersecurity resilience in smart city environments. The research adopts a Design Science Research (DSR) approach, which involves problem identification, literature analysis, model design, implementation, and evaluation. The proposed model incorporates key security components such as Identity and Access Management (IAM), device authentication, secure communication through encryption, firmware and patch management, and continuous monitoring with intrusion detection mechanisms. The model is evaluated through simulation in smart city scenarios, including transportation systems, environmental monitoring, and energy management. The results demonstrate significant improvements in security performance, with increases in threat detection rate, vulnerability reduction, access control effectiveness, and system stability under attack conditions. Quantitative analysis shows improvements of up to 37% compared to conventional approaches, indicating the effectiveness of the proposed model in mitigating IoT-related cybersecurity risks. This study contributes by providing a comprehensive and scalable framework for IoT device security management, which can be applied to enhance the reliability and sustainability of smart city systems. Future research is recommended to validate the model in real-world implementations and integrate advanced technologies such as artificial intelligence for predictive threat detection.

Sustainable Development Goals (SDGs) are a global action plan agreed upon by world leaders, including Indonesia, to achieve sustainable development in all aspects, especially in the use of renewable energy sources. For Indonesia, the implementation of SDGs can contribute to the country's progress and development, especially in the use of solar energy as an alternative energy source. Solar energy consistently dominates the expansion of renewable energy capacity, making it the main focus of sustainable development efforts in Indonesia. In fact, solar energy accounted for 73% of renewable energy growth last year, reaching a capacity of 1,419 GW, followed by wind energy with a 24% share in renewable energy expansion. The emphasis on solar power and other renewable energy sources is in line with Indonesia's goal of becoming a fully developed country. The research method used in this scientific article is the literature study method. A literature review that focuses on a particular topic to identify a theory or method, develop the theory or method, and summarize its development. Therefore, the aim of this paper is to reveal that the role of solar energy in increasing energy efficiency is very important and is growing very significantly every year.

he world's energy industries contribute 87% to the increase in global greenhouse gases. To reduce global greenhouse gas emissions, hydrogen as clean energy is an alternative energy source with a gravimetric energy density of 120 MJ/kg and a volumetric density of 0.0824 kg/m3. The main challenge of hydrogen as an energy carrier is its low volumetric density, thus requiring hydrogen storage technology at higher volumetric densities. Hydrogen storage systems are crucial to the hydrogen supply chain process, especially in terms of its economics. The hydrogen storage system consists of hydrogenation, transportation, and dehydrogenation processes. This paper uses the techno-economic analysis of five types of hydrogen storage technologies: compressed hydrogen, liquid Hydrogen, liquid organic hydrogen carrier, metal hydride, and ammonia. Hysys was introduced to help process design, process modeling, and equipment sizing of each technology. System costs ($/kg) are determined based on projected Capital Expenditure (CapEx) and Operational expenditure (OpEx) of each hydrogenation and dehydrogenation process, as well as shipping transportation cost at 2000 km. The results show that liquid organic hydrogen carrier had the lowest system cost of $2.84/kg, followed by metal hydride at $2.95/kg, compressed hydrogen at $3.33/kg, ammonia at $7.21/kg, and liquid hydrogen at $11.51/kg. However, the storage efficiency of liquid organic hydrogen carriers is only 8.73%, compared to compressed hydrogen at 99%. The results show that the cost of hydrogen storage systems needs to be significantly reduced for long-term and large-scale applications.

Energy efficiency is a critical concern in wireless sensor networks (WSNs) due to the limited power resources available in sensor nodes. Prolonging network lifespan while ensuring reliable data transmission is essential for successful deployment in various applications, such as environmental monitoring, military operations, and industrial automation. This paper presents a mathematical model designed to optimize energy consumption across various nodes in WSNs. By implementing simulations and analyzing data from these models, the study demonstrates significant improvements in extending network lifespan while maintaining reliable data throughput. The findings contribute valuable insights into energy management for large-scale sensor deployments.

Smart grids incorporate IoT devices that enhance energy management, monitoring, and overall grid efficiency. However, this interconnectivity also increases vulnerability to cybersecurity threats, posing risks to critical infrastructure. This research investigates the implementation of blockchain technology to secure data transactions within IoT-based smart grids. By leveraging blockchain's decentralized, tamper-resistant characteristics, the study demonstrates improvements in data integrity and cybersecurity for smart grids, providing a potential framework for resilient and secure energy infrastructures.

Cyber Physical Systems (CPS) are vital for managing and controlling critical infrastructures, such as industrial control systems, power grids, and transportation networks. These systems integrate digital and physical components, offering numerous benefits for industrial automation. However, the increasing interconnectivity of these systems has introduced new security vulnerabilities, particularly in anomaly detection and system reliability. This research aims to address these challenges by proposing an edge based anomaly detection framework that leverages lightweight deep learning models, specifically designed to operate efficiently on resource constrained edge devices. Literature Review: Previous studies have shown the effectiveness of anomaly detection in CPS, with traditional methods struggling to keep up with the complexity and scale of modern industrial environments. Machine learning and deep learning approaches, particularly hybrid models combining rule based systems and AI, have emerged as effective solutions for real time anomaly detection. Techniques such as model compression, quantization, and pruning are essential for adapting these models to resource limited edge devices while maintaining high detection accuracy and low latency. Materials and Method: The proposed framework integrates deep learning models such as Convolutional Neural Networks (CNNs) and Long Short Term Memory (LSTM) networks, optimized for edge computing environments. The datasets used for training and testing include industrial network traffic and sensor anomaly datasets. Model optimization techniques like pruning and quantization were applied to reduce computational overhead and energy consumption on edge devices. Results and Discussion: The framework demonstrated high detection accuracy (AUC of 0.9720) with ultra low latency (0.0019 seconds training time), making it highly suitable for real time anomaly detection in CPS. Resource efficiency was achieved by optimizing the models for edge devices, reducing energy consumption while maintaining performance. The framework also significantly improved security by identifying anomalies early, preventing potential threats to critical infrastructures. Future directions include exploring federated learning to enhance privacy and data sharing across distributed devices.

Waste management poses an inevitable challenge in human life and is often poorly handled. One type of waste causing significant issues is solid organic waste from households, which can lead to unpleasant odors and soil and water pollution due to its high organic content. However, the potential of organic waste to be converted into biogas, as an alternative energy source, can be harnessed through anaerobic processes. In this experiment, the researchers aimed to observe the effectiveness of adding additives to organic waste with varying doses. The organic content in the substrate for anaerobic microbes was represented by VS (volatile solid), with the inoculum sourced from cow dung. The experiment results indicate that adding NPK fertilizer additives with different doses increases biogas production. This suggests that the use of NPK additive can enhance the efficiency of anaerobic processes in generating biogas from organic waste.

This research aims to analyze behavioral dynamics in the implementation of responsibility accounting and identify the challenges faced by PT Sky Energy Indonesia Tbk in the financial and operational context. This study is a case study analysis by collecting data through company annual report and the latest news to understand the financial condition, governance and operational challenges faced by the company. The research results show that PT. Sky Energy Indonesia Tbk experienced a decline in sales, faced a Postponement of Debt Payment Obligation (PKPU) process, and was at risk of being delisted from the Indonesian Stock Exchange (BEI), which was exacerbated by the impact of the COVID-19 pandemic. Although annual reports demonstrate a commitment to transparency and sustainability, the findings indicate a gap between commitments and actual practices. This research recommends that to overcome this challenge, PT. Sky Energy Indonesia Tbk needs to increase transparency, operational efficiency, focus on renewable energy, strengthen governance, and develop a solid financial strategy. These steps require a strong commitment from companies to adaptation, innovation and long-term sustainability. This research provides insight into the importance of responsibility accounting in facing financial and operational challenges, as well as contributing to the literature on corporate governance and sustainability in Indonesia.

The oil fuel stock monitoring system (BBM) is becoming crucial to the management of valuable energy assets. The aim of the author is to conduct an effective system analysis and development to monitor BBM stocks. The research uses prototyping methods, which include the following steps: identification of initial needs, initial prototype making, evaluation and feedback, improvement and development, final implementation, and final evaluation. An easy-to-understand user interface design and an efficient database structure are important components of system design. Web-based software development is part of the system implementation. The testing process is carried out to ensure the performance, reliability, and security of the system. The system is regularlyined to remain functional and relevant. It is expected that the results of this practice will make a significant contribution in improving the efficiency and accuracy of monitoring BBM stocks. Moreover, these results will provide the basis for similar system development in the future.  

The rapid development of technology will obtain excellent effectiveness and efficiency from sources of electrical energy owned by a company or agency. With the progress of the industrial world today, the development of digital technology which ends in computer systems indirectly makes control technology involved as part of this progress. The availability of a power source is a very important aspect in the midst of technological developments. However, because the system is very complex, starting from the power plant to distribution to consumers, there is a high possibility of disturbances that can cause the flow of electrical energy to consumers to be cut off. There are certain places including factories, offices, banks, campuses, hospitals, airports and other places that could potentially endanger one's safety or drastically disrupt the course of the economic cycle. The flow of electrical energy must not be interrupted for a very long time because it can hamper the production process. and others, so that additional supply is needed to anticipate when the electricity is cut off from the National Power Plant source.

Renewable energy microgrids integrated with smart control systems are emerging as a sustainable solution for electrifying rural industrial zones, offering substantial improvements in energy efficiency and reductions in carbon emissions. This study explores the implementation of hybrid renewable energy systems, combining solar and wind energy, and the integration of Internet of Things (IoT) sensors to optimize energy consumption in real-time. The findings highlight that the combination of solar and wind energy in microgrids leads to up to a 30% increase in energy efficiency, with a significant reduction in CO₂ emissions, reaching up to 50% compared to traditional grid systems. IoT sensors play a crucial role in load forecasting, optimization, and system stability, enabling real-time monitoring and proactive adjustments to energy distribution. Additionally, the implementation of these systems in rural industrial zones not only provides reliable, clean energy but also reduces reliance on fossil fuels, making them economically viable and environmentally sustainable. However, challenges such as high initial investment costs, integration complexities, and the need for skilled technicians remain. Despite these barriers, the long-term benefits of reduced energy costs, improved energy security, and lower carbon footprints make renewable energy microgrids a promising solution. The study suggests that these systems can be scaled to other rural regions facing similar challenges in energy access and carbon emissions, offering a path to sustainable development. Further research is recommended to explore alternative renewable energy combinations and advancements in IoT applications to improve system scalability and efficiency.

The increasing complexity of modern software systems and the growing demand for real-time data processing have significantly contributed to higher energy consumption in computing infrastructures. This challenge is particularly evident in systems that rely on continuous monitoring, analytics, and adaptive decision-making. Addressing energy efficiency without compromising system performance has therefore become a critical concern in sustainable software engineering. This study proposes an energy-aware software approach that integrates real-time analytics with adaptive feedback mechanisms to optimize energy consumption while maintaining operational performance. The research adopts a design science oriented methodology, encompassing system design, implementation, and experimental evaluation. The proposed system architecture consists of real-time data acquisition, intelligent analytics, and an adaptive control layer based on the MAPE-K (Monitor, Analyze, Plan, Execute, Knowledge) feedback loop. Experimental evaluations were conducted under dynamic workload scenarios to compare the proposed adaptive system with a baseline non-adaptive system. Key performance indicators included energy consumption, response time, throughput, and adaptation latency. The results demonstrate that the proposed system achieves a substantial reduction in energy consumption while maintaining, and in some cases improving, system performance metrics. The adaptive feedback mechanism enables the system to respond effectively to workload fluctuations, reducing unnecessary energy usage during low-demand periods and ensuring stable performance during peak loads. These findings provide empirical evidence that real-time analytics and adaptive control can effectively support energy-efficient and sustainable software systems. This research contributes to the field of energy-aware software engineering by demonstrating that intelligent real-time adaptation is a viable strategy for achieving sustainability objectives in dynamic and performance-critical environments.

This research explores the potential of local bio-composites made from bamboo and coconut fiber as sustainable building materials in Indonesia. The construction sector in Indonesia faces significant environmental challenges, particularly the high carbon emissions associated with conventional materials like concrete and steel. The primary objective of this research is to evaluate the environmental and economic benefits of substituting these traditional materials with bio-composites, using Life Cycle Assessment (LCA) and energy optimization simulations. The LCA methodology evaluates the environmental impact of bio-composites across their entire life cycle, comparing them with conventional materials in terms of carbon emissions, energy consumption, and waste. Energy optimization simulations focus on assessing the thermal performance and overall building efficiency when using bio-composites in construction. The main findings suggest that bio-composites exhibit a significantly lower carbon footprint and better thermal insulation properties than concrete and steel, contributing to reduced energy consumption in buildings. Additionally, the use of locally sourced materials like bamboo and coconut fiber offers economic advantages, such as lower transportation costs and support for local economies. The research concludes that bio-composites can serve as viable alternatives to traditional materials, providing both environmental and economic benefits. For successful adoption, the research recommends policy support, technological advancements, and educational initiatives to promote the use of bio-composites in Indonesia’s construction industry.

This study aims to analyze the application of sustainable principles in modern residential interior design and focuses on aesthetic aspects. With increasing attention to environmental sustainability issues, interior design plays an important role in reducing environmental impacts through the selection of environmentally friendly materials, efficient energy use, and space optimization. However, the aesthetic aspect cannot be separated from design, because it plays a role in creating visual comfort and occupant well-being. This study uses a qualitative descriptive method with an interdisciplinary approach, which includes literature reviews, design analysis, and case studies on several interior projects that have successfully combined sustainable and aesthetic principles. The results of the study show that interior design that considers sustainability not only focuses on energy efficiency and the selection of environmentally friendly materials, but also integrates aesthetic elements that enhance the comfort of the space. These findings emphasize the importance of public and designer awareness in creating functional, environmentally friendly, and aesthetic spaces. This study is expected to provide theoretical and practical contributions to the development of interior design that supports sustainability without sacrificing the aesthetic quality and comfort of the space.

Microenterprises are crucial to the economic landscape, especially in developing countries, as they contribute significantly to GDP and employment. However, these businesses often face challenges in adopting sustainable practices due to financial constraints, limited resources, and market access issues. This research evaluates the impact of energy efficiency on the profitability of Sharia-compliant microenterprises applying green business principles. By integrating energy-saving measures, such as energy-efficient technologies and optimized consumption, microenterprises can reduce operational costs and improve profitability. Sharia-compliant businesses, which adhere to ethical and sustainable practices, tend to be more open to implementing such green practices. The findings show that energy-efficient microenterprises outperform conventional ones in profitability, as energy-saving leads to lower costs and enhanced competitiveness. The study also highlights the importance of green finance in supporting these enterprises by overcoming financial barriers, allowing them to adopt energy-efficient technologies. Despite the clear benefits, challenges such as high initial investment costs and limited access to efficient technologies remain. Policy intervention, including financial incentives and education, is necessary to address these barriers and enable microenterprises to fully capitalize on energy efficiency. In conclusion, energy efficiency is not only a key driver of profitability for Sharia-compliant microenterprises but also a strategy for long-term sustainability and competitiveness.

This paper presents an optimization approach for a hybrid photovoltaic (PV)-wind-battery energy system tailored for remote areas in Indonesia. Due to the archipelagic nature of the country, many remote areas lack access to the national power grid, making renewable energy solutions crucial. This study utilizes a genetic algorithm to optimize system configurations, balancing energy production, storage requirements, and cost efficiency. Results indicate that the proposed hybrid system can meet local demand with high reliability and at lower costs compared to diesel generators. The study also addresses environmental and social impacts, proposing sustainable energy strategies for Indonesia's underserved regions.

This study investigates the performance and sustainability of a hybrid solar-biomass drying system for agricultural products, focusing on its efficiency, environmental impact, and economic feasibility. The hybrid system combines solar energy and biomass combustion to create a continuous and reliable drying process. The key findings reveal that the hybrid system achieves over a 20% improvement in drying efficiency compared to solar-only and biomass-only dryers. This efficiency gain is attributed to the synergistic use of solar energy during the day and biomass energy during periods of low sunlight or at night, ensuring consistent drying conditions and reduced drying time. Additionally, the hybrid system significantly reduces CO₂ emissions, contributing to a more sustainable approach to agricultural processing. The environmental benefits of using renewable energy sources, as opposed to fossil fuels, align with the growing need for energy-efficient and eco-friendly agricultural technologies. Economic analysis suggests that the hybrid system is a cost-effective solution for small- to medium-scale farmers, particularly in rural areas where access to grid electricity is limited. The use of locally available biomass fuels further enhances the system’s sustainability and affordability. This study also discusses the practicality of implementing hybrid dryers in rural farming communities, emphasizing their potential to improve drying efficiency, reduce environmental impacts, and boost economic opportunities for farmers. Future research should focus on optimizing system integration, expanding biomass fuel options, and exploring automation to enhance the performance and scalability of hybrid drying systems.

Electrical power is a very important source for life. One of the electrical components is a distribution transformer which is used to transmit electrical voltage from the substation to the load center. Every year the electricity demand increases, so that the transformer works optimally, you must also pay attention to the loading. Load imbalance on electric power distribution transformers always occurs and this imbalance occurs due to the use of electrical energy. The current flowing in the neutral conductor of the transformer causes an imbalance in the transformer load and losses, namely losses due to the neutral current in the neutral conductor of the transformer. When analyzing mass, use quantitative methods. After analysis, it shows that the transformer is in an unbalanced state where neutral current appears in the transformer. To determine the efficiency of the distribution transformer