Innovative Digital Manufacturing Curriculum for Industry 4.0

Promyoo, Rapeepan; Alai, Shashank; El-Mounayri, Hazim

doi:10.1016/j.promfg.2019.06.092

Cited by 38 publications

(14 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The applications are found in wide range of field, including unmanned systems (Giles et al, 2019), electric vehicles (Draxler et al, 2019), military technologies (Sarathi et al, 2021) and others. The primary MBSE aim is to define functional and nonfunctional requirements in a way that linkages between functional, logical and physical architecture were traceably across all levels of abstraction (Promyoo et al, 2019).…”

Section: Overview Of Mbse Within Industry 40mentioning

confidence: 99%

Towards a Model-Based Systems Engineering Approach for Robotic Manufacturing Process Modelling with Automatic FMEA Generation

et al. 2022

View full text Add to dashboard Cite

The process of generating FMEA following document-centric approach is tedious and susceptible to human error. This paper presents preliminary methodology for robotic manufacturing process modelling in MBSE environment with a scope of automating multiple steps of the modelling process using ontology. This is followed by the reasoning towards automatic generation of process FMEA from the MBSE model. The proposed methodology allows to establish robust and self-synchronising links between process-relevant information, reduce the likelihood of human error, and scale down time expenses.

show abstract

Section: Overview Of Mbse Within Industry 40mentioning

confidence: 99%

Towards a Model-Based Systems Engineering Approach for Robotic Manufacturing Process Modelling with Automatic FMEA Generation

et al. 2022

View full text Add to dashboard Cite

show abstract

“…They propose a decoupling algorithm for the coupling optimization problem and apply it to establish the production line based on the digital twin. 36 Promyoo et al 4 employed real-time control and the system's performance parameters at runtime to improve a digital Twin-based manufacturing framework named model-based systemsdriven product development (i.e., system-driven product development, SDPD). A team from Beihang University and Sara Moghadaszadeh's team attempt to improve the accuracy of the model, reflecting and predicting system performance by increasing the dimension (3-D to 5-D) of the model based on digital twin technology.…”

Section: Further Challenges Of the Employment Of Digital Twinmentioning

confidence: 99%

“…The Digital Twin is thought to be an ideal concept related to Industry 4.0. 4,5 Internet of things, Machine learning, and Artificial Intelligence are creating a new integrated environment mentioned as Digital Twin. Digital Twin is a simulation process that applies physical models, sensor updates, operation historical data, integrates multi-disciplinary, multi-physical factors, multiscale, and multi-probability.…”

Section: Introductionmentioning

confidence: 99%

Multi‐dimensional digital twin of energy storage system for electric vehicles: A brief review

2021

View full text Add to dashboard Cite

This article proposes a Digital Twin (DT) framework for the whole life cycle of batteries. Specifically, in the stage of R&D, Digital twin can integrate the data of all technical fields into one model to optimize the battery's performance.During the manufacturing and production phase, DT can establish a digital production line and workshop to improve it. In the operation stage, aiming at various fault features in the battery operation process, with the assistance of large data samples, digital twin simulation is used to determine the fault status of the equipment accurately, to realize the self-perception, judgment, error correction, early warning and other functions of the equipment. The article also proposes a Postoperation phase to recycle the battery to resolve the battery materials shortage problem. The critical research direction is a futuristic plan of battery communication with a charging Station, Battery Swapping System, Smart Grid, and Renewable resources. This sophisticated DT can comprehensively improve the energy system's entire life cycle management. Moreover, it can help perceive customer demand and offer an efficient operation mode to reduce running costs.

show abstract

“…The first step in good teaching became finding out and understanding each student's sense of direction" [266]. Learning organisations should therefore develop their programmes in order to become increasingly agile in the face of these changes and at the same time remain as close as possible to both CAD technologies [268]- [271] and the 4.0 industrial world [272]. This agility is nowadays also required by learners, either during initial training or lifelong training:…”

Section: Are 'Gamification' and 'Learning By Doing' Approaches Potent...mentioning

confidence: 99%

Coevolution of digitalisation, organisations and Product Development Cycle

Roucoules

Anwer

2021

CIRP Annals

View full text Add to dashboard Cite

Innovative Digital Manufacturing Curriculum for Industry 4.0

Cited by 38 publications

References 3 publications

Towards a Model-Based Systems Engineering Approach for Robotic Manufacturing Process Modelling with Automatic FMEA Generation

Towards a Model-Based Systems Engineering Approach for Robotic Manufacturing Process Modelling with Automatic FMEA Generation

Multi‐dimensional digital twin of energy storage system for electric vehicles: A brief review

Coevolution of digitalisation, organisations and Product Development Cycle

Contact Info

Product

Resources

About