Review of simulator training practices for industrial operators: How can individual simulator training be enabled?

Marcano, Laura; Haugen, Finn; Sannerud, Ronny; Komulainen, Tiina M.

doi:10.1016/j.ssci.2019.02.019

Cited by 25 publications

(13 citation statements)

References 77 publications

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“…The main environment is the modular dynamic modeling software. The modular architecture allows the development of scalable integrated systems of operator's training packages [38].…”

Section: Dynamic Modelingmentioning

confidence: 99%

“…The development environment, including executive dynamic modeling, can switch to different subprocesses such as simulation models, emulation models of control systems, emulation of programmable logic controllers, graphical user's interface, applications of outside suppliers (e.g., Excel) and many others [38,39]. The whole system is united by the common environment which synchronizes data transfer (Fig.…”

Section: Dynamic Modelingmentioning

confidence: 99%

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The concept of digital twins for tech operator training simulator design for mining and processing industry

Белоглазов¹,

Petrov²,

Bazhin³

2020

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According to the top-priority trends and challenges in the mineral sector, and as per the mining science strategy, it is highly critical to arrange enhanced control, prediction and safety of production objects and their functioning for the preservation of automation sustainability. Improved control of databases, regulatory bonds, management, logistics and principles of sustainable development in mining makes it possible to reduce technological deviations and accidents at large mining and processing plants. Most procedural violations and accidents in surface and underground mines occur because of the unskilled actions of process flow operators. Damage in this case can be considerable, especially as compared with the expenses connected with qualitative training and persistent development of personnel engaged with supervisory control and data acquisition for the efficient operation of SCADA-systems within the automation framework of mining and processing plants. Definition of digital systems and their interrelation with multilevel automated control can be incorrect. The review of new principles can awaken interest in the conceptual assessment of digitalization processes using such notions as: numerical models, simulator, and artificial intelligence. Often applied formulations and principles of a digital model are substituted without justification of functional connections. On the other hand, a digital system today can be assumed as robotic lines and other numerical models and smart technologies, for instance, machining stations with numerical program control. It is necessary to define the practical significance of conceptual modifications and digital transformation regarding objects of the mineral sector, using Big Data; to understand how a digital twin can influence a changeable process situation; to provide prompt prediction; to eliminate an accident; and to preserve the physical balance in the whole production system. Such intelligent and flexible productions particularly need computerbased simulators and digital twins based on technologies of Industry 4.0–extended and virtual reality on the basis of digital twins. Digital twins allow maximal simulation of real-life activity of process flow operators. The skills acquired by personnel after such simulation training enable operators to master the optimized procedure for functioning in emergency situations in mineral mining and processing. This paper exemplifies the remote training and control of process flows, which is of concern in the current international situation.

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“…The main environment is the modular dynamic modeling software. The modular architecture allows the development of scalable integrated systems of operator's training packages [38].…”

Section: Dynamic Modelingmentioning

confidence: 99%

Section: Dynamic Modelingmentioning

confidence: 99%

The concept of digital twins for tech operator training simulator design for mining and processing industry

Белоглазов¹,

Petrov²,

Bazhin³

2020

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“…Besides, it also links students to the learning material in a structured way through specially designed web-based student learning software and programs ( Arenas-Gaitán et al., 2018 ; Chaw and Tang, 2018 ; Isaac et al., 2019 ). These systems monitor learning activities and student performance by tracking system activities and showing statistics and strategies ( Al-Fraihat et al., 2020 ; Kite et al., 2020 ; Marcano et al., 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Moderating effects of academic involvement in web-based learning management system success: A multigroup analysis

Mehrolia

Alagarsamy

Sabari

2021

Heliyon

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While several educational institutions in India, in accordance to global practices, have adopted Web-Based Learning Management Systems (WLMS) to supplement classroom courses, it is largely seen that these WLMSs fail in their objectives, leading to little or no return on investments. The study aims to define the factors that affect students’ acceptance of a web-based learning management system and test the moderating effect of their academic involvement in the success of a WLMS. 477 valid questionnaires were collected from university/college students to empirically test the research model using the structural equation modelling approach. The results concludes that indirect and direct effects account for 49% of the variation in the intention to use, which is explained by technical system quality, information quality, educational quality, service quality of the technical support team and user satisfaction. High academic involvement moderates the impact of different service qualities of the WLMS on user satisfaction, intention to use the system, and success of the WLMS. Based on the findings, theoretical and managerial implications are discussed.

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“…[24] suggests evaluating the performance by testing it and determining its technical, functional, psychological and cognitive fidelity. If fly or driver simulators are developed and have a wide application [25], the industrial simulators are developed individually and are usually unique in its kind [26].…”

Section: Introductionmentioning

confidence: 99%

A Simulator for Educating the Digital Technologies Skills in Industry. Part One. Dynamic Simulation of Technological Processes

2021

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Digital technology is being introduced into all areas of human activity. However, there are a number of challenges in implementing these technologies. These include the delayed return on investment, the lack of visibility for decision-makers and, most importantly, the lack of human capacity to develop and implement digital technologies. Therefore, creating a digital training simulator for the industry is an actual task. This paper focuses on the first step in creating a digital training simulator for the industry: developing a dynamic process model. The process chosen is flotation, as it is one of the most common mineral processing methods. The simulation was performed in AVEVA Dynamic Simulation software. The model is based on a determination of reaction rate constants, for which, experiments were conducted on a laboratory pneumomechanical flotation machine with a bottom drive. The resulting model was scaled up to industrial size and its dynamic properties were investigated. In addition, the basic scheme of a computer simulator was considered, and the testing of the communication channels of a dynamic model with systems, equipment and software for digitalizing was conducted. The developed model showed acceptable results for its intended purpose, namely, an exact match to the technological process in terms of time. This helps to account for inertia and a fast response on all tested communication channels, as well as being acceptable for the real-time simulation speed of the solver.

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Review of simulator training practices for industrial operators: How can individual simulator training be enabled?

Cited by 25 publications

References 77 publications

The concept of digital twins for tech operator training simulator design for mining and processing industry

The concept of digital twins for tech operator training simulator design for mining and processing industry

Moderating effects of academic involvement in web-based learning management system success: A multigroup analysis

A Simulator for Educating the Digital Technologies Skills in Industry. Part One. Dynamic Simulation of Technological Processes

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