Article Critique: Smart Operating Robot in Power System
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This article critique discusses the use of smart operating robots in power systems and the application of AI technology for better evaluation and ticketing operations. It also highlights the challenges faced in implementing the system and the potential benefits it offers.
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Running head: ARTICLE CRITIQUE RESEARCH METHODS FOR ENGINEERS: ARTICLE CRITIQUE Students ID: Name of University Authors Note
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2ARTICLE CRITIQUE Introduction The purpose of the article is to highlight the concept of the smart processing system and the significant use of artificial technology application within powers control centre. The article portrays issues found within the Tianjin power process in China. Another major problem highlighted in the paper, is the power operations tickets are generated in a manual way by the operators. Therefore, based on these issues the paper provides a framework of the smart processing system specifically an operated robot that consists of an intelligent power system along with smart ticket operating system. Summary paragraph One of the major demands of the power system evaluating tool is the urge for an effective analysis process. It has been seen in the article that, with a growth of technology, institutions and organisation are increasingly implementing new technology that urges in terms of various locations with a better system of evaluation tool and automatic system for ticketing operations (Wang et al., 2017). The fact illustrated here is that during the time when the power process faces interruption the evaluation process used may not be helpful for the functioning operators therefore; to solve this issue AI techniques has proposed in the paper to establish a better system of evaluation. The reason for the slowdown of the system that is the traditional method of analysis using an algorithm such as the Newton Raphson method due to which calculation process takes a lot of time. Therefore, the paper reveals the use of AI technology for developing the DSA process with an advanced process of AI (Culler & Long, 2016). Moreover, the article presents an understanding of the use and handling of the ticket compilation system for refusing the occurrence of errors and delay within the system. Apart from this company the article also highlights the automatic ticket generating that has been adopted by several organisations (Wang et al., 2018). In order to measure and understand the potentialafterconsequencesoftheoperations,thestudyhasillustratedtheincident predication system and warning system for helping the operators to take preventive action in case of accidental events. Critical analysis of the Article Power control system is the major facilities within the power systems. The main purpose of the centre is ensuring the supervision and evaluation the position of the power
3ARTICLE CRITIQUE process in accordance to the suitable actions for ensuring flexibility of the power operations. It is evident from the article that the modern system of power is a complex issue that requires a huge amount of information for operating it (Lee et al., 2016). It is rather a struggle for the employees to implement effective planning for the complicated issues based on the huge information. It has been found from the article that the control centre needs to be managed 24 hours. In this regards, the risk may occur if the operators are shut down at night. The paper has suggested the use of an operating robot to assist the operators to handle the operations effectively. The smart operating ticket operations is a in depth learning that is based on the process to form an automatic regenerate the operations that are reliable. However, the strength of the smart operating system is that it helps the operator to detect the error within the process thereby helping in the recognition of the object, and topological evaluations of the organisation (Zander et al., 2015). On the contrary, the weakness shows that the relevant information of the system is very rare and the existing products cannot be replaced with smart software to generate operational tickets. Therefore, the software that is to be used is mainly based on limited rules that can be only used in case of simpler tasks in the power system. In this case, it has been found that most of the problem needs to be interacted from different perspectives due to the presence of the complex power system. For solving these issues AI needs to be used for the better performing operations. The AI-based power generation not only helps in the fast evaluation system, it also helps to provide the employees to encounter with different events taking place within the power process, with better decision assistance process (Gao et al., 2017). The system is designed with incident detection and waning process for predicting the status of the power process for warning the employees to take prior steps to manage the system. It has been discussed in the article that operational tickets generated by the smart process can help to reduce the errors within the operational and through this operators can also check the automatic compiling system thereby reducing workload.In this context, the article also points out relevant difficulties that might be faced by automatic generation if operational ticket (Wang et al., 2018). The difficulty is that the operational generation of tickets requires high experienced thinking and reasoning within the working procedure. Conclusion
4ARTICLE CRITIQUE Therefore, from the above article, it is evident that the paper illustrates the demands and the significant application of the AI power system within the power control centre in China.Based, on the theory of in-depth learning system, the article successfully introduced the development of smart operating AI system within power generations. Based on this system the paper lays down the simulation of each of the operations in details to gather the understanding of the system. Reference list Culler,D.,&Long,J.(2016).Aprototypesmartmaterialswarehouseapplication implementedusingcustommobilerobotsandopensourcevisiontechnology developed using emgucv.Procedia Manufacturing,5, 1092-1106.
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5ARTICLE CRITIQUE Gao, Z., Chin, C. S., Chiew, J. H. K., Jia, J., & Zhang, C. (2017). Design and Implementation of a Smart Lithium-Ion Battery System with Real-Time Fault Diagnosis Capability for Electric Vehicles.Energies,10(10), 1503. Lee, Y. T., Hsiao, W. H., Huang, C. M., & Seng-cho, T. C. (2016). An integrated cloud-based smart home management system with community hierarchy.IEEE Transactions on Consumer Electronics,62(1), 1-9. Wang, Q., Yang, X., Huang, Z., Ma, S., Li, Q., Wenzhong Gao, D., & Wang, F. (2018). A Novel Design Framework for Smart Operating Robot in Power System.IEEE/CAA Journal of Automatica Sinica,5 (2), 531 Wang, X. V., Wang, L., Mohammed, A., & Givehchi, M. (2017). Ubiquitous manufacturing system based on Cloud: A robotics application.Robotics and Computer-Integrated Manufacturing,45, 116-125. Zander, J., Mosterman, P. J., Padir, T., Wan, Y., & Fu, S. (2015). Cyber-physical systems can make emergency response smart.Procedia Engineering,107, 312-318.