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Investment analysis of solar power plant installation on the roof of the central business district office building with the best investment value Soejanto, Irwan; Poerbaningrat, Raden Muhammad Nalindra; Ristyowati, Trismi; Puryani, Puryani
OPSI Vol 17 No 1 (2024): ISSN 1693-2102
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Industri UPN "Veteran" Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/opsi.v17i1.11233

Abstract

The Central Business District (CBD) office building is making efforts to reduce building electricity costs, and one alternative is solar power plant installation. PT. Rancang Prima Sejahtera, engaged in the solar energy industry, conducts consulting services with Central Business District office buildings, so PT. Rancang Prima Sejahtera made an indicative proposal with several solar power plant installation scenarios to be installed on the roof of the Central Business District office building. Four scenarios are created from the combination of 2 PV modules and two inverters. Each scenario created will be assessed for the level of opt, and the investment value will be calculated. In combining components using the principles of the Vereun Deutsche Ingineuer (VDI) 2222 method and assessed each scenario using six aspects of assessment.Meanwhile, the investment analysis assessment uses the parameters of Cost of Energy (CoE), Net Present Value (NPV), Internal Rate of Return (IRR), Benefit-Cost Ratio (B-CR), and discounted payback period. The results of the analysis conducted found that the third scenario was the best scenario with a percentage of the design value of 82.5%, CoE value of Rp398.31/kWh, NPV value of Rp2,451,719,005, IRR percentage of 23.75%, B-CR value of 7.8, and DPP value for 6.8 years with a project life of 30 years. The findings of the investment research indicate that the implementation of solar power plant installations in office buildings located in Central Business Districts yields long-term cost reductions in electricity expenses over a 30-year period, as opposed to relying solely on the services provided by the State Electricity Enterprise.
A hybrid Genetic Algorithm and Fuzzy Logic approach to ergonomic design of workstations in metal casting operations Berlianty, Intan; Soejanto, Irwan; Titisariwati, Indun; Putra, Favian Ersanta Andhika; Utami, Wahyu Tri; Insani, Mohamad Kamil
OPSI Vol 17 No 2 (2024): ISSN 1693-2102
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Industri UPN "Veteran" Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/opsi.v17i2.13943

Abstract

The metal casting industry faces significant challenges in balancing productivity with worker safety and well-being. Hazardous working conditions, including high temperatures, exposure to gases, and repetitive motions, increase the risk of injuries and fatigue. 1 This study proposes a novel hybrid approach that integrates Genetic Algorithm (GA) and Fuzzy Logic (FL) to optimize workstation ergonomics. The system utilizes real-time data from sensors to evaluate ergonomic factors such as worker posture, fatigue levels, and environmental conditions. Fuzzy Logic processes this data, while GA optimizes the system's parameters for enhanced accuracy and adaptability. Experimental results demonstrated significant improvements, including a 25% reduction in worker fatigue, a 30% improvement in air quality compliance, and a 35% decrease in ergonomic risks. Real-time adjustments, such as desk height modifications and improved ventilation, effectively enhanced worker safety and comfort. This innovative approach offers a scalable and reliable solution for improving ergonomics in dynamic industrial environments, contributing to both worker well-being and operational efficiency. Future research could further enhance the system by incorporating machine learning for improved predictive capabilities and expanded optimization of ergonomic parameters.
Adaptation of Internet of Things Technology to Measure Energy Consumption Levels to Reduce Ergonomics-Based Work Accidents Berlianty, Intan; Soejanto, Irwan; Titisariwati, Indun; Nursubiyantoro, Eko; Arifin, Miftahol
Jurnal Ilmiah Teknik Industri Vol. 22, No. 2, December 2023
Publisher : Department of Industrial Engineering Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jiti.v22i2.22561

Abstract

This research focuses on applying Internet of Things (IoT) technology to measure energy consumption levels to reduce work accidents based on ergonomics. Work accidents caused by ergonomic factors, such as physical fatigue and discomfort, can be overcome by understanding and managing energy consumption in the work environment. Comparisons made between IoT-based approaches and traditional methods, such as manual observation and periodic evaluation, are often less efficient and unresponsive to changes in the dynamic work environment.The research methodology consists of three main stages. First, design and implement an IoT system involving intelligent sensors to measure energy consumption and ergonomic factors. Second, real-time data collection by analyzing data using artificial intelligence algorithms. Third, performance comparison between IoT-based and traditional methods through field trials and statistical analysis. The research results are expected to provide new insights regarding the effectiveness and efficiency of IoT technology in managing the risk of work accidents based on ergonomics. Future implications of this research include the potential for widespread use of IoT technology in various industrial sectors to improve worker safety and well-being. In addition, this research can pave the way for developing more sophisticated technological solutions tailored to the specific needs of each sector.