Research on Energy-Saving Production Scheduling Based on a Clustering Algorithm for a Forging Enterprise

Yifei Tong, Jingwei Li, Shai Li and Dongbo Li
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Yifei Tong: School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Jingwei Li: School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Shai Li: School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Dongbo Li: School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China

Sustainability, 2016, vol. 8, issue 2, 1-17

Abstract: Energy efficiency is a buzzword of the 21st century. With the ever growing need for energy efficient and low-carbon production, it is a big challenge for high energy-consumption enterprises to reduce their energy consumption. To this aim, a forging enterprise, DVR (the abbreviation of a forging enterprise), is researched. Firstly, an investigation into the production processes of DVR is given as well as an analysis of forging production. Then, the energy-saving forging scheduling is decomposed into two sub-problems. One is for cutting and machining scheduling, which is similar to traditional machining scheduling. The other one is for forging and heat treatment scheduling. Thirdly, former forging production scheduling is presented and solved based on an improved genetic algorithm. Fourthly, the latter is discussed in detail, followed by proposed dynamic clustering and stacking combination optimization. The proposed stacking optimization requires making the gross weight of forgings as close to the maximum batch capacity as possible. The above research can help reduce the heating times, and increase furnace utilization with high energy efficiency and low carbon emissions.

Keywords: energy-saving scheduling; energy efficiency; low carbon mission; forging production; dynamic clustering; stacking combination optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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