Sökning: onr:"swepub:oai:DiVA.org:mdh-64546" >
Cognitive Digital T...
Cognitive Digital Twin in Manufacturing : A Heuristic Optimization Approach
-
- Rehman, Atiq Ur (författare)
- Mälardalens universitet,Inbyggda system
-
- Ahmed, Mobyen Uddin, Dr, 1976- (författare)
- Mälardalens universitet,Inbyggda system
-
- Begum, Shahina, 1977- (författare)
- Mälardalens universitet,Inbyggda system
-
(creator_code:org_t)
- Springer Science and Business Media Deutschland GmbH, 2023
- 2023
- Engelska.
-
Ingår i: IFIP Advances in Information and Communication Technology. - : Springer Science and Business Media Deutschland GmbH. - 9783031341069 ; , s. 441-453
- Relaterad länk:
-
https://urn.kb.se/re...
-
visa fler...
-
https://doi.org/10.1...
-
visa färre...
Abstract
Ämnesord
Stäng
- Complex systems that link virtualization and simulation platforms with actual data from industrial processes are vital for the next generation of production. Digital twins are such systems that have several advantages, notably in manufacturing where they can boost productivity throughout the whole manufacturing life-cycle. Enterprises will be able to creatively, efficiently, and effectively leverage implicit information derived from the experience of current production processes, thanks to cognitive digital twins. The development of numerous technologies has made the digital twin notion more competent and sophisticated throughout time. This article proposes a heuristic approach for cognitive digital twin technology as the next development in a digital twin that will aid in the realization of the goal of Industry 4.0. In creating cognitive digital twins, this article suggests the use of a heuristic approach as a possible route to allowing cognitive functionalities. Here, heuristic optimization is proposed as a feature selection tool to enhance the cognitive capabilities of a digital twin throughout the product design phase of production. The proposed approach is validated using the use-case of Power Transfer Unit (PTU) production, which resulted in an improvement of 8.83% in classification accuracy to predict the faulty PTU in the assembly line. This leads to an improved throughput of the PTU assembly line and also saves the resources utilized by faulty PTUs.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
Nyckelord
- Cognitive Digital Twins
- Cyber-Physical Systems
- Heuristic Optimization
- Industrial Manufacturing
- Assembly
- Cognitive systems
- Embedded systems
- Energy transfer
- Heuristic methods
- Life cycle
- Optimization
- Product design
- Simulation platform
- Assembly line
- Cognitive digital twin
- Cybe-physical systems
- Heuristics approaches
- Optimization approach
- Power transfer units
- Virtualizations
- Cyber Physical System
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
Hitta via bibliotek
Till lärosätets databas