The fast growth in the installation of industrial robots has had a major impact on the comparative advantage of nations and the division of labor in global value chains in the era of smart manufacturing. Using various econometric models and panel dat...
The last decade saw the emergence of highly autonomous, flexible, re-configurable Cyber-Physical Systems. Research in this domain has been enhanced by the use of high-fidelity simulations, including Digital Twins, which are virtual representations co...
Predictive maintenance in the car industry is an active field of research for machine learning and anomaly detection. The capability of cars to produce time series data from sensors is growing as the car industry is heading towards more connected and...
Modernization of society from a rural, hunter-gatherer setting into an urban and industrial habitat, with the associated dietary changes, has led to an increased prevalence of cardiometabolic and additional noncommunicable diseases, such as cancer, i...
Appropriate maintenance of industrial equipment keeps production systems in good health and ensures the stability of production processes. In specific production sectors, such as the electrical power industry, equipment failures are rare but may lead...
The successful implementation of Human-Robot Collaboration (HRC) has become a prominent feature of smart manufacturing environments. Key industrial requirements, such as flexibility, efficiency, collaboration, consistency, and sustainability, present...
The convergence of artificial intelligence and the Internet of Things (IoT) has made remarkable strides in the realm of industry. In the context of AIoT edge computing, where IoT devices collect data from diverse sources and send them for real-time p...
Environmental science and pollution research international
37318732
As an emerging technology, industrial intelligence focus on the integration of artificial intelligence and production, which creates a new access to achieve the goal of carbon emissions reduction. Using data on provincial panel data from 2006 to 2019...
Machine learning techniques have progressively emerged as important and reliable tools that, when combined with machine condition monitoring, can diagnose faults with even superior performance than other condition-based monitoring approaches. Further...
Small and medium-sized enterprises (SMEs) often encounter practical challenges and limitations when extracting valuable insights from the data of retrofitted or brownfield equipment. The existing literature fails to reflect the full reality and poten...