Lingling Li

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 article, a reverse engineering based approach is proposed to aid the remanufacturing processes of worn parts, which integrates 3D surface data collection, nominal model reconstruction, fine registration, extraction of additive/subtractive repair, tool path generation and actual machining process.

TL;DR: A two-stage knowledge-driven method by integrating data mining techniques and fuzzy logic theory for generalizing the energy-aware parametric optimization for multiple machining configurations, which has a high potential for enhancing energy efficiency and time efficiency in turning system.

TL;DR: A multi-objective parameter optimization method for energy efficiency in CNC milling process is presented and the parametric influence on specific energy consumption and production time are explicitly analyzed.

TL;DR: In this paper, an integrated approach of process planning and cutting parameter optimization is proposed to minimize the total energy consumption of CNC machining and to balance machine workloads in workshop.