The concept of the digital twin of the production system in the process of digital transformation of the production process model in power engineering

Author(s):  
A. V. Rechkalov ◽  
A. V. Artuhov ◽  
G.G. Kulikov ◽  
V. N. Novikov

2021 ◽  
Vol 11 (10) ◽  
pp. 4620
Author(s):  
Niki Kousi ◽  
Christos Gkournelos ◽  
Sotiris Aivaliotis ◽  
Konstantinos Lotsaris ◽  
Angelos Christos Bavelos ◽  
...  

This paper discusses a digital twin-based approach for designing and redesigning flexible assembly systems. The digital twin allows modeling the parameters of the production system at different levels including assembly process, production station, and line level. The approach allows dynamically updating the digital twin in runtime, synthesizing data from multiple 2D–3D sensors in order to have up-to-date information about the actual production process. The model integrates both geometrical information and semantics. The model is used in combination with an artificial intelligence logic in order to derive alternative configurations of the production system. The overall approach is discussed with the help of a case study coming from the automotive industry. The case study introduces a production system integrating humans and autonomous mobile dual arm workers.



2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bayu Rima Aditya ◽  
Ridi Ferdiana ◽  
Sri Suning Kusumawardani

PurposeExisting literature has reported a barrier list that could affect the implementation of digital transformation in higher education, yet the research question of how to identify barriers remained unanswered. Thus, this study intended to address this gap.Design/methodology/approachThe research design adopted a mixed-methods approach based on the problem-centered design science research (DSR) process model for the development and evaluation of framework.FindingsThis study proposed a systematic framework of three sets of components: (1) the initial set of barriers; (2) the barrier rating scheme and (3) the barrier scoring matrix. The three-component of the framework is to identify and prioritize barriers to the successful implementation of digital transformation in higher education.Research limitations/implicationsThe evaluation of the framework was only based on an expert opinion.Practical implicationsThis study provided a direction to the policymakers for designing sensible strategies to increase the chances of a successful digital transformation in higher education.Originality/valueThis study contributes to the knowledge body by offering a more systematic understanding of barriers to digital transformation in higher education.



2021 ◽  
Vol 1 (2) ◽  
pp. 46-51
Author(s):  
Dwi Ayu Lestari, Vikha Indira Asri

Scheduling is defined as the process of sequencing the manufacture of a product as a whole on several machines. All industries need proper scheduling to manage the allocation of resources so that the production system can run quickly and precisely as of it can produce optimal product. PT. Sari Warna Asli Unit V is one of the companies that implements a make to order production system with the FCFS system. Thus, scheduling the production process at this company is also known as job shop production scheduling. The methods used in this research are the CDS method, the EDD method and the FCFS method. The purpose of this research is to minimize the production time and determine the best method that can be applied to the company. The results of this research showed that the makespan obtained in the company's scheduling system with FCFS rules was 458 minutes, and the results of scheduling using the CDS method obtained a makespan value of 329 minutes, then the best production scheduling method that had the smallest makespan value was the CDS method.



2019 ◽  
Vol 31 (5) ◽  
pp. 1391-1396
Author(s):  
Gordana Stojmenović ◽  
Lyubcho Varamezov

Business in modern business conditions requires a continuous process of improvement and investment in all activities in the company. In order to survive on the market, resist the challenges of competition, but also the demands of customers, companies are constantly innovating the production process in an effort to improve all the company's activities. One of the production systems that proved to be suitable for continuous improvement and improvement of the production process is Lean production system. It represents the way companies react to the challenges of the present and the future. The Lean production system offers a variety of instruments, and for their implementation and application, managers are at all levels of responsibility and responsibility. Bearing this in mind, it can be said that the Lean production system is part of the management accounting. In addition, it represents a complete philosophy of thinking and action, which results in significant results by adequate application. The condition and the assumption that this management philosophy will lead to proper effectiveness and efficiency and enable them to continually improve in the function of maximizing profits is the authorization of employees to engage in the process of continuous improvement and decision-making. Lean is based on certain principles and philosophies, including customer value, value flow mapping, continuous flow, system requirements, and continuous improvements. Lean focuses on the added value. Lean's principle is a continuous search for perfection, perfection in production and business cooperation, with complete elimination of losses. Companies that implement the Lean Concept are constantly looking for ways to continually improve their efficiency, reduce costs and improve the quality of their products.



2021 ◽  
Author(s):  
Zhongyu Zhang ◽  
Zhenjie Zhu ◽  
Jinsheng Zhang ◽  
Jingkun Wang

Abstract With the drastic development of the globally advanced manufacturing industry, transition of the original production pattern from traditional industries to advanced intelligence is completed with the least delay possible, which are still facing new challenges. Because the timeliness, stability and reliability of them is significantly restricted due to lack of the real-time communication. Therefore, an intelligent workshop manufacturing system model framework based on digital twin is proposed in this paper, driving the deep inform integration among the physical entity, data collection, and information decision-making. The conceptual and obscure of the traditional digital twin is refined, optimized, and upgraded on the basis of the four-dimension collaborative model thinking. A refined nine-layer intelligent digital twin model framework is established. Firstly, the physical evaluation is refined into entity layer, auxiliary layer and interface layer, scientifically managing the physical resources as well as the operation and maintenance of the instrument, and coordinating the overall system. Secondly, dividing the data evaluation into the data layer and the processing layer can greatly improve the flexible response-ability and ensure the synchronization of the real-time data. Finally, the system evaluation is subdivided into information layer, algorithm layer, scheduling layer, and functional layer, developing flexible manufacturing plan more reasonably, shortening production cycle, and reducing logistics cost. Simultaneously, combining SLP and artificial bee colony are applied to investigate the production system optimization of the textile workshop. The results indicate that the production efficiency of the optimized production system is increased by 34.46%.



2021 ◽  
Author(s):  
Eric Rebentisch ◽  
Donna H. Rhodes ◽  
Antonio Lucas Soares ◽  
Ricardo Zimmerman ◽  
Sergio Tavares


2019 ◽  
Vol 57 (20) ◽  
pp. 6315-6334 ◽  
Author(s):  
Kai Ding ◽  
Felix T.S. Chan ◽  
Xudong Zhang ◽  
Guanghui Zhou ◽  
Fuqiang Zhang


2019 ◽  
Vol 106 (5-6) ◽  
pp. 1787-1810 ◽  
Author(s):  
Kyu Tae Park ◽  
Jehun Lee ◽  
Hyun-Jung Kim ◽  
Sang Do Noh


2010 ◽  
Vol 102-104 ◽  
pp. 776-780 ◽  
Author(s):  
Xiu Lin Li ◽  
Jian Sha Lu ◽  
Guo Zhong Chai ◽  
Hong Tao Tang

To deal with problem of manufacturing system stability caused by uncertain factors in discrete production process, holon was introduced to manufacturing execution system (MES). A distributed manufacturing control architecture based on holon was established. This architecture using cooperation mechanism based stigmergy to realize agility, autonomy and intelligence of system control. Based on the architecture, holon driven agents to visit production elements, acquiring dynamic information of production process. Model design of production factors as order, resource, raw material, product and management factors as optimize, execution was described amply. Finally, workflow of this system was depicted with an example of uncertain order factor.



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