[HTML][HTML] Digital Twin: Benefits, use cases, challenges, and opportunities

M Attaran, BG Celik - Decision Analytics Journal, 2023 - Elsevier
Abstract Applications of Digital Twin technology have been growing at an exponential rate,
and it is transforming the way businesses operate. In the past few years, Digital Twins …

[HTML][HTML] Predictive maintenance using digital twins: A systematic literature review

R van Dinter, B Tekinerdogan, C Catal - Information and Software …, 2022 - Elsevier
Context Predictive maintenance is a technique for creating a more sustainable, safe, and
profitable industry. One of the key challenges for creating predictive maintenance systems is …

[HTML][HTML] Remaining Useful Life prediction and challenges: A literature review on the use of Machine Learning Methods

C Ferreira, G Gonçalves - Journal of Manufacturing Systems, 2022 - Elsevier
Abstract Approaches such as Cyber-Physical Systems (CPS), Internet of Things (IoT),
Internet of Services (IoS), and Data Analytics have built a new paradigm called Industry 4.0 …

Data mining in predictive maintenance systems: A taxonomy and systematic review

A Esteban, A Zafra, S Ventura - Wiley Interdisciplinary Reviews …, 2022 - Wiley Online Library
Predictive maintenance is a field of study whose main objective is to optimize the timing and
type of maintenance to perform on various industrial systems. This aim involves maximizing …

[HTML][HTML] Digital Twins and Industrial Internet of Things: Uncovering operational intelligence in industry 4.0

S Attaran, M Attaran, BG Celik - Decision Analytics Journal, 2024 - Elsevier
Abstract The Industrial Internet of Things (IIoT) and Digital Twins (DTs) are changing how
digital models and physical products interact. IIoT connects to intelligence in the physical …

The impact of digital twins on the evolution of intelligent manufacturing and Industry 4.0

M Attaran, S Attaran, BG Celik - Advances in Computational Intelligence, 2023 - Springer
As the adoption of Industry 4.0 advances and the manufacturing process becomes
increasingly digital, the Digital Twin (DT) will prove invaluable for testing and simulating new …

Data-driven implicit design preference prediction model for product concept evaluation via BP neural network and EEG

L **g, C Tian, S He, D Feng, S Jiang, C Lu - Advanced Engineering …, 2023 - Elsevier
Customer preference-involved product concept evaluation is a vital stage for develo**
new products. One of the key factors in this stage is to mine the potential relationships …

[HTML][HTML] A predictive maintenance model using long short-term memory neural networks and Bayesian inference

D Pagano - Decision Analytics Journal, 2023 - Elsevier
The fourth industrial revolution is a profound transformation utilizing emerging technologies
like smart automation, large-scale machine-to-machine communication, and the internet of …

An improved generic hybrid prognostic method for RUL prediction based on PF-LSTM learning

K Xue, J Yang, M Yang, D Wang - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Accurate estimation and prediction of the state-of-health (SOH) and remaining useful life
(RUL) are fundamental to optimal maintenance strategies formulation for prognostics and …

[HTML][HTML] Adoptable approaches to predictive maintenance in mining industry: An overview

O Dayo-Olupona, B Genc, T Celik, S Bada - Resources Policy, 2023 - Elsevier
The mining industry contributes to the expansion of the global economy by generating vital
commodities. For continuous production, the industry relies significantly on machinery and …