Xingzheng Chen

TL;DR: It is found that the economic activity is the greatest driving force to promote carbon emissions, while on the contrary, energy intensity is the biggest suppressor and optimizing industrial structure, improving the structure of energy and export-import trade and intensifying the development of clean energy can effectively restrain the growth of carbon emissions.

TL;DR: In this paper, a multi-objective parameter optimization model for maximizing energy efficiency and minimizing production cost is proposed and solved by the Adaptive Multiobjective Particle Swarm Optimization algorithm.

TL;DR: In this article, a process model of CNC machining is presented to scope the system boundaries for energy footprint and process efficiency, and a multi-objective optimization model is then proposed to explore the impact of cutting speed and feed rate on carbon emissions and processing time.

TL;DR: An energy efficiency monitoring and management system with the support of the newly emerging Internet of Things (IoT) technology is proposed and potential opportunities for energy consumption decrement and energy efficiency improvement can be identified.

TL;DR: Results indicate that the optimum cutting parameters of milling process vary with the energy boundaries whether considering the embodied energy of the auxiliary materials or not, and multi-objective optimization is an effective method to address the conflicts of the two objectives.