Topic: Optimization Algorithms for Clean and High Efficient Manufacturing Processes

Given the increasing concern about global warming, reducing greenhouse gas emissions and building a low-carbon world have garnered a global consensus. As a major source of energy consumption and carbon emissions, manufacturing consumes over 30% of total energy usage and accounts for over a third of global carbon emissions. Therefore, improving the efficiency of manufacturing processes while reducing carbon emissions is imperative. Achieving efficient and low-carbon manufacturing processes requires an adaptive, multi-dimensional, and multi-level architecture within shop floor manufacturing systems. This architectural framework should consider both efficiency and carbon emissions simultaneously. The research involves several key aspects: firstly, conducting research on optimizing the efficient and low-carbon application of workshop manufacturing systems in complex environments to improve their operational efficiency. Secondly, establishing a multi-level, distributed carbon emission model and its energy flow model of the workshop manufacturing system. These models reveal the process characteristics of the energy flow status. Additionally, the research endeavors to create an energy flow evaluation index system and investigate the techniques for energy efficiency improvement and optimization of process routes and process parameters. These efforts seek to reveal the correlation and interaction between efficiency and energy consumption. Furthermore, in pursuit of high efficiency and low carbon impact, the research aims to develop an operation optimization model of the workshop manufacturing system and study optimization technology for comprehensive operations of the manufacturing system. Overall, the aforementioned research holds great importance in enhancing competitiveness and fostering sustainable development capabilities within manufacturing enterprises.

Manufacturing system, low carbon manufacturing, manufacturing processes, shop scheduling, shop energy flow

31 Jul 2024