[HTML][HTML] Leveraging AI for energy-efficient manufacturing systems: Review and future prospectives
Energy poses a significant challenge in the industrial sector, and the abundance of data
generated by Industry 4.0 technologies offers the opportunity to leverage Artificial …
generated by Industry 4.0 technologies offers the opportunity to leverage Artificial …
Reinforcement learning for sustainable energy: A survey
K Ponse, F Kleuker, M Fejér, Á Serra-Gómez… - arXiv preprint arXiv …, 2024 - arxiv.org
The transition to sustainable energy is a key challenge of our time, requiring modifications in
the entire pipeline of energy production, storage, transmission, and consumption. At every …
the entire pipeline of energy production, storage, transmission, and consumption. At every …
Energy-aware flow shop scheduling with uncertain renewable energy
This paper investigates an energy-aware flow shop scheduling problem with on-site
renewable and grid energy resources. To deal with the uncertainty of renewable energy …
renewable and grid energy resources. To deal with the uncertainty of renewable energy …
Editorial for the special issue: AI and data-driven decisions in manufacturing
Manufacturing organizations are increasingly using information technologies to better
understand their shop floor operations. These technologies include radio frequency …
understand their shop floor operations. These technologies include radio frequency …
Data-driven linear quadratic tracking based temperature control of a big area additive manufacturing system
Designing efficient closed-loop control algorithms is a key issue in Additive Manufacturing
(AM), as various aspects of the AM process require continuous monitoring and regulation …
(AM), as various aspects of the AM process require continuous monitoring and regulation …
Dynamic confidence-based constraint adjustment in distributional constrained policy optimization: enhancing supply chain management through adaptive …
Y Boutyour, A Idrissi - Journal of Intelligent Manufacturing, 2024 - Springer
In this study, we introduce the dynamic confidence-based constraint adjustment (DCCA)
approach, an innovative enhancement to the distributional constrained policy optimization …
approach, an innovative enhancement to the distributional constrained policy optimization …
Change is safer: a dynamic safety stock model for inventory management of large manufacturing enterprise based on intermittent time series forecasting
L Fan, Z Song, W Mao, T Luo, W Wang, K Yang… - Journal of Intelligent …, 2024 - Springer
As a key issue of inventory management for enterprise after-sales service, safety stock is
dedicated to ensuring maintenance reliability while keeping low inventory cost. Existing …
dedicated to ensuring maintenance reliability while keeping low inventory cost. Existing …
Construction and Application of Energy Footprint Model for Digital Twin Workshop Oriented to Low-Carbon Operation
L Zhang, C Zhuang, Y Tian, M Yao - Sensors, 2024 - mdpi.com
To address the difficulty of accurately characterizing the fluctuations in equipment energy
consumption and the dynamic evolution of whole energy consumption in low-carbon …
consumption and the dynamic evolution of whole energy consumption in low-carbon …
Active Inference Meeting Energy-Efficient Control of Parallel and Identical Machines
We investigate the application of active inference in developing energy-efficient control
agents for manufacturing systems. Active inference, rooted in neuroscience, provides a …
agents for manufacturing systems. Active inference, rooted in neuroscience, provides a …
Dynamic integrated simulative layout planning and production control for matrix production in a semiconductor environment
Increasing complexity, emerging manufacturing objectives and rising costs of manufacturing
equipment result in the needs for faster product development and for a more effectively use …
equipment result in the needs for faster product development and for a more effectively use …