AIMC Topic: Industry

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VKAD: A novel fault detection and isolation model for uncertainty-aware industrial processes.

Neural networks : the official journal of the International Neural Network Society
Fault detection and isolation (FDI) are essential for effective monitoring of industrial processes. Modern industrial processes involve dynamic systems characterized by complex, high-dimensional nonlinearities, posing significant challenges for accur...

Exploring the drivers of digital transformation in Chinese port and shipping enterprises: A machine learning approach.

PloS one
With the transition to a global green low-carbon economy, the urgency for digital transformation in the port and shipping industry has become increasingly prominent in making enterprises more efficient and sustainable. This study focuses on how Chine...

Industrial-grade collaborative robots for motor rehabilitation after stroke and spinal cord injury: a systematic narrative review.

Biomedical engineering online
BACKGROUND: There is a growing interest in exploring industrial-grade collaborative robots (cobots) for rehabilitation. This review explores their application for motor rehabilitation of the upper and lower extremities after a stroke and spinal cord ...

Leveraging industry 4.0 technologies and industrial symbiosis: Advancing circular economy practices in BRICS economies.

Journal of environmental management
In addressing the dynamics of a circular economy (CE), Industry 4.0 technologies (IN4.0T) and Industrial Symbiosis (IS) necessitate meticulous management strategies to optimize their advantageous impacts on circular practices. The present study inves...

Industrial applications of large language models.

Scientific reports
Large language models (LLMs) are artificial intelligence (AI) based computational models designed to understand and generate human like text. With billions of training parameters, LLMs excel in identifying intricate language patterns, enabling remark...

Identifying and addressing challenges in gross pollutant trap maintenance: perspectives from the Australian stormwater industry.

Marine pollution bulletin
A common approach to removing pollution from stormwater is through the installation of gross pollutant traps (GPTs). However, GPTs are often not maintained effectively, leading to pollution accumulation and additional pollution bypassing into natural...

Uncovering soil heavy metal pollution hotspots and influencing mechanisms through machine learning and spatial analysis.

Environmental pollution (Barking, Essex : 1987)
Soil heavy metal (HM) pollution is a significant and widespread environmental issue in China, highlighting the need to quantify influencing factors and identify priority concern areas for effective prevention and management. Based on published litera...

Scalable and energy-efficient task allocation in industry 4.0: Leveraging distributed auction and IBPSO.

PloS one
Industry 4.0 has transformed manufacturing with the integration of cutting-edge technology, posing crucial issues in the efficient task assignment to multi-tasking robots within smart factories. The paper outlines a unique method of decentralizing au...

Deep learning based approaches for intelligent industrial machinery health management and fault diagnosis in resource-constrained environments.

Scientific reports
Industry 4.0 represents the fourth industrial revolution, which is characterized by the incorporation of digital technologies, the Internet of Things (IoT), artificial intelligence, big data, and other advanced technologies into industrial processes....

Achieving pollution abatement and carbon reduction synergistically: How can industrial robots play a role?

Journal of environmental management
Intelligent manufacturing and green development are pivotal issues in China's pursuit of high-quality economic growth. As the core carrier of artificial intelligence-driven production transformations, industrial robots' role in synergizing enterprise...