Abstract:PurposeThe purpose of this paper is to conduct a systematic bibliometric analysis of reconfigurable manufacturing system (RMS) articles using VOSviewer to identify their research themes and future research trends and investigate their interconnectivity. This paper also aims to identify prominent authors, publishers, organizations, countries and their collaborations in the RMS domain.Design/methodology/approachIn this study, the Scopus database is used to retrieve 454 RMS articles published between 1988 and 202… Show more
“…Meet the expected design security goals, one is whether authorized user access is normal; the other is whether illegal user access is blocked [17]. (2) Test whether the operation of the functional modules of the system meets the expected design and operation goals, such as basic operations such as additions, deletions, and changes, and data normative judgments.…”
In order to promote, restrict, regulate, and balance the accounting work of electric power enterprises, the author proposes an electric power enterprise accounting system based on sensor monitoring and cloud computing. Through the method of integrating information technology on the basis of accounting computerization, through a sensor and modular design analysis, an accounting information management system model is formed. The accounting information management system based on cloud computing combines accounting and management functions. The system test results show that the accounting information management system is in a state of 480 concurrent users, the average response time of a data query is 4.3 seconds, and the average response time of a data access is 5.1 seconds. The average value of the execution data scale per second is 103.52. Conclusion. In order to further improve the accounting software of electric power enterprises, develop management accounting software, and effectively perform the functions of management accounting.
“…Meet the expected design security goals, one is whether authorized user access is normal; the other is whether illegal user access is blocked [17]. (2) Test whether the operation of the functional modules of the system meets the expected design and operation goals, such as basic operations such as additions, deletions, and changes, and data normative judgments.…”
In order to promote, restrict, regulate, and balance the accounting work of electric power enterprises, the author proposes an electric power enterprise accounting system based on sensor monitoring and cloud computing. Through the method of integrating information technology on the basis of accounting computerization, through a sensor and modular design analysis, an accounting information management system model is formed. The accounting information management system based on cloud computing combines accounting and management functions. The system test results show that the accounting information management system is in a state of 480 concurrent users, the average response time of a data query is 4.3 seconds, and the average response time of a data access is 5.1 seconds. The average value of the execution data scale per second is 103.52. Conclusion. In order to further improve the accounting software of electric power enterprises, develop management accounting software, and effectively perform the functions of management accounting.
“…Information technologies and Industry 4.0 are largely assisting in the automation of the manufacturing of healthcare-related products, whereas RMS is assisting in the adjustment of production capacity and required flexibility (Qi et al 2021 ). The RMS core characteristics (Modularity, Integrability, Customization, Convertibility, Diagnosability, and Scalability) provide the required flexibility to the manufacturing system and allow it to adjust production capacity in response to market demand (Pansare et al 2021b ). In addition, Psarommatis ( 2021 ) used several Industry 4.0 technologies for zero defect manufacturing (ZDM), including Cyber-Physical System (CPS), Artificial Intelligence (AI), Big Data, Cloud Manufacturing, etc.…”
The Covid-19 pandemic has had a significant impact on manufacturing industries and supply chains. Manufacturing industries are struggling to repurpose their production activities and ramp up the supply chain to bridge the demand–supply gap. A framework that can cover Industry 4.0 technologies and reconfigurable manufacturing system (RMS) practices is desperately needed. The current study focuses primarily on the framework that could assist managers in decision-making and the stepwise adoption of RMS during repurposing. The extensive literature review was conducted to identify the prominent Industry 4.0 technologies and RMS practices. To compute the weights of selected practices, the novel Pythagorean fuzzy analytical hierarchy process (AHP) was used; while the Pythagorean fuzzy combined compromise solution (CoCoSo) method was used to prioritize the selected performance metrics. To test the robustness of the developed framework, a sensitivity analysis was carried out. According to the findings, smart factory adoption (SFA) practices were the most significant among the major criteria, followed by reconfiguration practices (RCP), soft computing practices (SCP), sustainable & circular economy practices (SCE), and quality practices (QPS). SFA's advanced technologies and SCP's computer algorithms certainly assist in the repurposing of production activities (RPO). The results of the sensitivity analysis demonstrated the robustness of the developed framework. The developed framework will be useful during RPO, and the identified practices can make a significant contribution. Advanced technologies and sustainable practices can help to improve the organization's work culture. Managers will be able to evaluate the organization's performance with the help of identified performance metrics. The work presented here may be the first attempt to develop a framework for RPO in a pandemic situation.
“…This problem remained unexplored in the concerned literature. The presented problem has multiple applications in the real-life situations, ranging from reconfigurable supply chain [64], single-unit process plans [65], multi-unit process plans [66], reconfiguration in emergency response systems [67], integrated production scheduling and process control [68], and performance evaluation of reconfigurable integrated manufacturing system (RIMS) [3]. Table 5 summarizes the applications of the on-hand problem.…”
Section: Managerial Implicationsmentioning
confidence: 99%
“…It has become the focus of researchers as well as practitioners in the context of Industry 4.0 (I4.0) and as part of the Next Generation Manufacturing Systems (NGMSs) [2]. The RMS is built on the core characteristics of scalability, customization, integrability, modularity and diagnosability [3]. These characteristics play an important role in making the production system responsive and reconfigurable.…”
Reconfigurable manufacturing systems are complex systems that are prone to malfunctions and performance decay. Thus, such systems need to be safeguarded against quality issues and decline in production efficiency to ensure the optimal health of machines. The product quality and health of a reconfigurable manufacturing system can be analyzed by using the diagnosability characteristic. This study examines the diagnosability characteristic in a multi-stage reconfigurable manufacturing system. The aim is to understand the impact of time-based diagnostics on the functionality performance of a reconfigurable manufacturing system and the level of inventory used during production. The diagnosability is analyzed regarding product variation and system diagnosability. A mathematical model is proposed, and it is subsequently applied in deterministic and stochastic settings. The deterministic setting is examined through a set of two problem-specific heuristics. The stochastic setting, subject to the gamma process, is examined by using a simulation-based optimization approach. The results suggest that the use of line replacement units can restore a reconfigurable system to optimal functionality, reduce the level of inventory, and complete production in minimum time at the expense of additional cost. Finally, a conclusion and future research avenues are provided.
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