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Industrial Engineering 4.0 Strategies to Improve Manufacturing Efficiency and Productivity Kailie Maharjan; McCarty Elliot; Scherschligt Oscar
Journal of Moeslim Research Technik Vol. 1 No. 3 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v1i3.938

Abstract

The Industrial Revolution 4.0 has brought significant changes in the manufacturing sector through the application of advanced technologies such as the Internet of Things (IoT), artificial intelligence (AI), and big data analytics. The application of these technologies aims to address the challenges of improving efficiency and productivity in an increasingly complex and competitive manufacturing environment. This research aims to identify and analyse effective strategies in implementing Industry 4.0 techniques to improve operational efficiency and productivity in the manufacturing sector. This research uses a case study method on several manufacturing companies that have implemented Industry 4.0 technology. Data were collected through interviews, direct observation, and analysis of company documents. Qualitative and quantitative approaches were used to analyse the data obtained. The results showed that the implementation of IoT, AI, and big data analytics technologies significantly improved efficiency and productivity. Successful implementation involves good integration between technology and business processes, employee training, and commitment from top management. Companies that implement these strategies successfully reduce downtime, improve product quality, and speed up production time. The research concludes that the right Industry 4.0 strategy can deliver significant improvements in manufacturing efficiency and productivity. The key to success lies in thorough technology integration, improved workforce competencies, and strong management support. Effective implementation of these strategies can give companies a competitive advantage in the global market
Current Quantum Optics Research: Exploring the Potential of Quantum Computing McCarty Elliot; Scherschligt Oscar; Morse Kathryn
Journal of Tecnologia Quantica Vol. 1 No. 1 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v1i1.874

Abstract

Quantum Optics is a branch of physics that studies the interaction between light and matter on a quantum scale. Research in this field aims to understand the basic properties of light particles (photons) and matter (atoms, molecules) and utilize them in various applications, including quantum computing. The aim of this research is to explore the potential of quantum computing in the context of Quantum Optics. This includes quantum algorithm development, experimental implementation, and practical applications in quantum information processing. The research method used involves a combination of theoretical and experimental approaches. The theoretical approach involves the development and mathematical analysis of Quantum Optics models, while the experimental approach involves the design and implementation of quantum physics systems in the laboratory. The research results show significant progress in the development of quantum algorithms that can be used in modeling quantum physics systems, quantum information processing, and other applications. In addition, the experimental results also show achievements in the implementation of quantum system prototypes that can be applied in the field of quantum computing. From the research that has been conducted, it can be concluded that quantum computing has great potential in improving the understanding of quantum physical systems and in developing new technologies based on quantum principles. However, challenges such as quantum quality control and maintenance and system scalability remain the focus of future research. As such, current Quantum Optics research offers exciting and potentially paradigm-shifting insights into future information processing and computing technologies