scholarly journals Corrigendum to “digital twins-based smart manufacturing system design in industry 4.0: A review’’ [J. Manuf. Syst. 60 (2021) 119–137]

2021 ◽  
Author(s):  
Jiewu Leng ◽  
Dewen Wang ◽  
Weiming Shen ◽  
Xinyu Li ◽  
Qiang Liu ◽  
...  
Keyword(s):  
System Design ◽  
Industry 4.0 ◽  
Manufacturing System ◽  
Smart Manufacturing ◽  
Digital Twins ◽  
Manufacturing System Design

Digital twins-based smart manufacturing system design in Industry 4.0: A review

2021 ◽  
Vol 60 ◽  
pp. 119-137
Author(s):  
Jiewu Leng ◽  
Dewen Wang ◽  
Weiming Shen ◽  
Xinyu Li ◽  
Qiang Liu ◽  
...  
Keyword(s):  
System Design ◽  
Industry 4.0 ◽  
Manufacturing System ◽  
Smart Manufacturing ◽  
Digital Twins ◽  
Manufacturing System Design

Sustaining the Competitive Edge of Small to Medium Size Enterprises Through Innovative Manufacturing System Design

2014 ◽  
Author(s):  
Mohamed A. Gadalla
Keyword(s):  
System Design ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Smart Manufacturing ◽  
Medium Size ◽  
Market Conditions ◽  
Competitive Edge ◽  
Manufacturing System Design ◽  
Smart Manufacturing Systems

Increasing Small to Medium size Enterprises (SME’s) competitive edge requires continuously developing creative and novel methods and solutions. This paper presents a novel design for a manufacturing system named Smart Manufacturing Systems (SMS). The new design can be viewed as a modification to the Flexible Manufacturing System (FMS) to better suits continuously changing market conditions, which may lead a company to develop a more sustainable competitive edge. The new design address several issues in manufacturing system design that affect the competitiveness of the system such as: merger of different manufacturing processes, non-productive times, and to be able to performing economically under different market conditions.

scholarly journals Digital Twins Collaboration for Automatic Erratic Operational Data Detection in Industry 4.0

2021 ◽  
Vol 11 (7) ◽  
pp. 3186
Author(s):  
Radhya Sahal ◽  
Saeed H. Alsamhi ◽  
John G. Breslin ◽  
Kenneth N. Brown ◽  
Muhammad Intizar Ali
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Interaction Mechanism ◽  
Semantic Knowledge ◽  
Smart Manufacturing ◽  
Data Detection ◽  
Workflow Model ◽  
Digital Twins ◽  
Potential Failure ◽  
Operational Data

Digital twin (DT) plays a pivotal role in the vision of Industry 4.0. The idea is that the real product and its virtual counterpart are twins that travel a parallel journey from design and development to production and service life. The intelligence that comes from DTs’ operational data supports the interactions between the DTs to pave the way for the cyber-physical integration of smart manufacturing. This paper presents a conceptual framework for digital twins collaboration to provide an auto-detection of erratic operational data by utilizing operational data intelligence in the manufacturing systems. The proposed framework provide an interaction mechanism to understand the DT status, interact with other DTs, learn from each other DTs, and share common semantic knowledge. In addition, it can detect the anomalies and understand the overall picture and conditions of the operational environments. Furthermore, the proposed framework is described in the workflow model, which breaks down into four phases: information extraction, change detection, synchronization, and notification. A use case of Energy 4.0 fault diagnosis for wind turbines is described to present the use of the proposed framework and DTs collaboration to identify and diagnose the potential failure, e.g., malfunctioning nodes within the energy industry.

Efficacy Investigation of Virtual Reality Teaching Module in Manufacturing System Design Course

2018 ◽  
Vol 141 (1) ◽  
Author(s):  
Junfeng Ma ◽  
Raed Jaradat ◽  
Omar Ashour ◽  
Michael Hamilton ◽  
Parker Jones ◽  
...  
Keyword(s):  
Virtual Reality ◽  
System Design ◽  
User Experience ◽  
Queuing Theory ◽  
Manufacturing System ◽  
Knowledge Gain ◽  
Teaching Module ◽  
Manufacturing System Design ◽  
System Usability ◽  
Complex Engineering

Manufacturing system design is a complex engineering field that requires cooperated and aggregated multiple-disciplinary theoretical and practical support. Thereby, the concepts and topics in manufacturing system design courses are not easy to grasp by students. Advances in virtual reality (VR) technology present a new opportunity that can provide the implementation of complex engineering theory from industrial real-life practice in a virtual 3D model. The authors developed a unique queuing theory VR teaching module that can be used in a manufacturing system design course. The module uses Oculus Rift headset, Oculus Touch, and unity 3D software package. The efficacy of this VR teaching module is measured through simulation sickness, system usability, and user experience tools. The statistical analysis shows that VR teaching module is a user-friendly and efficient tool for delivering queueing theory. Approximately 91.7% of the participants experienced below moderate level simulation sickness and none of them withdrew from the study; 91.67% had “above average” satisfaction in terms of system usability. The average user experience was found to be 3.625 out 6. The results also show that the system usability has impact on students' knowledge gain but not motivation, while user experience can affect student's knowledge gain and motivation. VR teaching module outperforms the traditional teaching module in terms of knowledge gain and motivation. Overall, the findings of the study confirm the efficacy of VR technology in teaching queuing theory.

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