Analysis of quantum computing industrial developments and applications

Sabine Wölk

R. Ratheesh, R. Keerthana, D. ThamizhSelvam +1 more

Quantum computing is at the forefront of technological progress, offering unparalleled computational power and capabilitiesthat have the potential to revolutionize a wide range of industries. The convergence of quantum computing and the Internetof Things (IoT) is reshaping the landscape of Industry 4.0, presenting exceptional opportunities for innovation andtransformation. By combining the immense computational power of quantum computing with the interconnected network ofIoT devices, there is vast potential to revolutionize data processing, analysis, and security within industrial settings.This paper delves into the profound impact of quantum computing on IoT applications in Industry 4.0, exploring how theseadvanced technologies are driving advancements in data processing, sensor technology, supply chain management, andcybersecurity. By examining the synergies between quantum computing and IoT, we uncover promising developments andchallenges that lie ahead at this dynamic intersection of cutting-edge technologies.Furthermore, this paper provides an in-depth analysis of the future of IoT devices by exploring the integration of quantumcomputing, assessing its impact on security, data processing, implementation challenges, future applications, and keyconsiderations for unlocking the full potential of this transformative partnership.

Daowen Qiu

Shuheng Gu, Yijiang Liu, Zihan Gu +3 more

Quantum computing, with its unique parallel computing ability and efficient optimization algorithm, provides new possibilities for the optimization of complex systems. This paper aims to explore the modeling and optimization methods of complex industrial engineering systems based on quantum computing and big data analysis technology. Through the comprehensive application of quantum approximate optimization algorithm, quantum support vector machine, data mining and machine learning technology, this study has realized the accurate modeling and optimization of complex industrial engineering systems. The research results show that compared with the traditional ID3 algorithm, the method adopted in this study shows better real-time performance and smaller relative error in industrial system assessment, which significantly improves the accuracy of assessment. This achievement not only provides more reliable data support for the prediction and risk control of industrial systems, but also verifies the effectiveness of quantum computing and big data analysis in dealing with complex system modeling and optimization problems. To sum up, the method proposed in this paper is expected to bring sustainable development momentum to the field of industrial engineering, and improve the decision-making support ability and risk control level of enterprises.

Tim van Erp, Bartłomiej Gładysz

In the medium- and long-term future, quantum technologies will become a megatrend shaping global industrial value creation. Quantum technologies will open novel pathways for manufacturing systems innovations, while also providing new opportunities for Sustainable Development. Manufacturing companies must already strive for a better understanding of quantum technologies and their potential applications if they are to maintain and improve their competitive advantage in the future. An overview of the theoretical background and state-of-the-art for quantum technologies and manufacturing systems is presented. Fields of application for quantum technologies are explored in the context of relevant manufacturing systems domains. Potential applications are proposed based on an analysis and synthesis of relevant literature, industrial case studies, as well as the authors’ ideations. A case is laid out for how quantum technologies can potentially facilitate industrial symbiosis within limited global ecological boundaries. In other words, the case study describes how Sustainable Development can be potentially facilitated using quantum computing and quantum AI.

Siddharth Kote, Dnyaneshwar Kshirsagar, Raj B. Kulkarni +3 more