Sustainability in wood products: a new perspective for handling natural diversity

M Schubert, G Panzarasa, I Burgert - Chemical Reviews, 2022 - ACS Publications
Wood is a renewable resource with excellent qualities and the potential to become a key
element of a future bioeconomy. The increasing environmental awareness and drive to …

Artificial intelligence (AI) in augmented reality (AR)-assisted manufacturing applications: a review

CK Sahu, C Young, R Rai - International journal of production …, 2021 - Taylor & Francis
Augmented reality (AR) has proven to be an invaluable interactive medium to reduce
cognitive load by bridging the gap between the task-at-hand and relevant information by …

Data analytics in quality 4.0: literature review and future research directions

A Bousdekis, K Lepenioti, D Apostolou… - International Journal of …, 2023 - Taylor & Francis
The quality level in manufacturing processes increasingly concerns manufacturing firms, as
they respond to pressures such as increasing complexity and variety of products, more …

Machine learning-based inverse design methods considering data characteristics and design space size in materials design and manufacturing: a review

J Lee, D Park, M Lee, H Lee, K Park, I Lee, S Ryu - Materials Horizons, 2023 - pubs.rsc.org
In the last few decades, the influence of machine learning has permeated many areas of
science and technology, including the field of materials science. This toolkit of data driven …

Accelerating the prediction of CO2 capture at low partial pressures in metal-organic frameworks using new machine learning descriptors

IB Orhan, TC Le, R Babarao, AW Thornton - Communications chemistry, 2023 - nature.com
Abstract Metal-Organic frameworks (MOFs) have been considered for various gas storage
and separation applications. Theoretically, there are an infinite number of MOFs that can be …

How can artificial intelligence enhance car manufacturing? A Delphi study-based identification and assessment of general use cases

Q Demlehner, D Schoemer, S Laumer - International Journal of Information …, 2021 - Elsevier
The latest boom of artificial intelligence (AI) has left the information management community
in strong need of structure-providing, high-level overview works. Such works are supposed …

Machine learning-supported manufacturing: A review and directions for future research

B Ördek, Y Borgianni, E Coatanea - Production & Manufacturing …, 2024 - Taylor & Francis
The evolution of manufacturing systems toward Industry 4.0 and 5.0 paradigms has pushed
the diffusion of Machine Learning (ML) in this field. As the number of articles using ML to …

Prediction of O2/N2 Selectivity in Metal–Organic Frameworks via High-Throughput Computational Screening and Machine Learning

IB Orhan, H Daglar, S Keskin, TC Le… - ACS Applied Materials …, 2021 - ACS Publications
Machine learning (ML), which is becoming an increasingly popular tool in various scientific
fields, also shows the potential to aid in the screening of materials for diverse applications. In …

Four Rs Framework for the development of a digital twin: The implementation of Representation with a FDM manufacturing machine

J Osho, A Hyre, M Pantelidakis, A Ledford… - Journal of Manufacturing …, 2022 - Elsevier
This work considers the conceptualization and design of a 4 Rs framework for creating a
general purpose, modular Digital Twin. The 4 Rs, correspond to the 4 different phases of a …

The interpretive model of manufacturing: a theoretical framework and research agenda for machine learning in manufacturing

A Sharma, Z Zhang, R Rai - International Journal of Production …, 2021 - Taylor & Francis
Manufacturing is undergoing a paradigmatic shift as it assimilates and is transformed by
machine learning and other cognitive technologies. A new paradigm usually necessitates a …