Digital Twin in Mining Industry: A Study on Automation Commissioning Efficiency and Safety Implementation of a Stacker Machine in an Open-Pit Mine

El-Bazi, Nabil; Hadraoui, Hicham El; Laayati, Oussama; Maghraoui, Adila El; Chebak, Ahmed; Mabrouki, Mustapha

doi:10.1109/gpecom58364.2023.10175788

Cited by 2 publications

(3 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is the synergy between monitoring systems and technology of data that makes the position of research notable, creating a paradigm shift for the industry. The fusion of Electrical and Computer Engineering (ECE) and AI not only brings better control and predictive capabilities but also the capacity to simulate and optimize processes in a riskfree digital environment which is needed to conduct tests on "what if" scenarios [26]. It amplifies the perks of the monitoring systems and provides a great impact on industry applications, from observing mechanical processes on the factory floors to monitoring big industrial activities [24].…”

Section: Monitoring Systemmentioning

confidence: 99%

“…By leveraging the FDI model, we gain a comprehensive overview of the operational processes within the open-pit mine's value chain [26], encompassing factory operations, manufacturing lines, processes, and equipment. This model empowers us to analyze At its heart, the ICOM (input, control, output, mechanism) parameters, foundational to the smart manufacturing system (SMS), dictate its operational dynamics.…”

Section: Mine Value Chain Parameters Surveymentioning

confidence: 99%

“…By leveraging the FDI model, we gain a comprehensive overview of the operational processes within the open-pit mine's value chain [26], encompassing factory operations, manufacturing lines, processes, and equipment. This model empowers us to analyze performance measures, organizational structures, tools, systems, and associated data comprehensively.…”

Section: Mine Value Chain Parameters Surveymentioning

confidence: 99%

See 2 more Smart Citations

Scalable Compositional Digital Twin-Based Monitoring System for Production Management: Design and Development in an Experimental Open-Pit Mine

El Bazi,

Laayati,

Darkaoui

et al. 2024

Designs

Self Cite

View full text Add to dashboard Cite

While digital twins (DTs) have recently gained prominence as a viable option for creating reliable asset representations, many existing frameworks and architectures in the literature involve the integration of different technologies and paradigms, including the Internet of Things (IoTs), data modeling, and machine learning (ML). This complexity requires the orchestration of these different technologies, often resulting in subsystems and composition frameworks that are difficult to seamlessly align. In this paper, we present a scalable compositional framework designed for the development of a DT-based production management system (PMS) with advanced production monitoring capabilities. The conducted approach used to design the compositional framework utilizes the Factory Design and Improvement (FDI) methodology. Furthermore, the validation of our proposed framework is illustrated through a case study conducted in a phosphate screening station within the context of the mining industry.

show abstract

Section: Monitoring Systemmentioning

confidence: 99%

Section: Mine Value Chain Parameters Surveymentioning

confidence: 99%

“…By leveraging the FDI model, we gain a comprehensive overview of the operational processes within the open-pit mine's value chain [26], encompassing factory operations, manufacturing lines, processes, and equipment. This model empowers us to analyze performance measures, organizational structures, tools, systems, and associated data comprehensively.…”

Section: Mine Value Chain Parameters Surveymentioning

confidence: 99%

See 1 more Smart Citation

Scalable Compositional Digital Twin-Based Monitoring System for Production Management: Design and Development in an Experimental Open-Pit Mine

El Bazi,

Laayati,

Darkaoui

et al. 2024

Designs

Self Cite

View full text Add to dashboard Cite

show abstract

DTFL‐DF: Digital twin architecture powered by federated learning decision forest to mitigate fire accidents in mining industry

Kamalakannan,

Sriramulu,

Ramamurthi

2024

Systems Engineering

View full text Add to dashboard Cite

Automation is the guiding principle of this new era, and despite the problems that humanity faces as a result of automation, technology has greatly benefitted people by streamlining challenging jobs across many industries. The mining business, where there are frequently unforeseen mishaps, is one such industry that requires complete automation. In this work, a new simulative processing environment termed DTFL‐DF—Digital twin federated learning decision forest a digital twin environment that is tailored to handle unforeseen fire incidents—is offered as a means of avoiding these unplanned catastrophes in the mining industry. Although the design presented here is intended for usage in the mining sector, it can also be applied to other sectors. The overall technological contribution of this study is to guarantee the processing of real‐time data in order to successfully handle mission‐critical operations without relying on past data. This is accomplished by adapting the digital twin's original design and distributing the processing environment within the edge‐fog layer. Results analysis in the form of robustness analysis, performance evaluation of the classification model, etc. provides strong support for the suggested methodology. For handling the decentralized training procedure, a brand‐new algorithm termed FL‐DF is put forth in order to speed up classification and prevent any sort of catastrophe.

show abstract

Digital Twin in Mining Industry: A Study on Automation Commissioning Efficiency and Safety Implementation of a Stacker Machine in an Open-Pit Mine

Cited by 2 publications

References 21 publications

Scalable Compositional Digital Twin-Based Monitoring System for Production Management: Design and Development in an Experimental Open-Pit Mine

Scalable Compositional Digital Twin-Based Monitoring System for Production Management: Design and Development in an Experimental Open-Pit Mine

DTFL‐DF: Digital twin architecture powered by federated learning decision forest to mitigate fire accidents in mining industry

Contact Info

Product

Resources

About