Review of Design of Process Parameters for Squeeze Casting

Abstract

Abstract Squeeze casting (SC) is an advanced net manufacturing process with many advantages for which the quality and properties of the manufactured parts depend strongly on the process parameters. Unfortunately, a universal efficient method for the determination of optimal process parameters is still unavailable. In view of the shortcomings and development needs of the current research methods for the setting of SC process parameters, by consulting and analyzing the recent research literature on SC process parameters and using the CiteSpace literature analysis software, manual reading and statistical analysis, the current state and characteristics of the research methods used for the determination of SC process parameters are summarized. The literature data show that the number of publications in the literature related to the design of SC process parameters generally trends upward albeit with significant fluctuations. Analysis of the research focus shows that both “mechanical properties” and “microstructure” are the two main subjects in the studies of SC process parameters. With regard to materials, aluminum alloys have been extensively studied. Five methods have been used to obtain SC process parameters: Physical experiments, numerical simulation, modeling optimization, formula calculation, and the use of empirical values. Physical experiments are the main research methods. The main methods for designing SC process parameters are divided into three categories: Fully experimental methods, optimization methods that involve modeling based on experimental data, and theoretical calculation methods that involve establishing an analytical formula. The research characteristics and shortcomings of each method were analyzed. Numerical simulations and model-based optimization have become the new required methods. Considering the development needs and data-driven trends of the SC process, suggestions for the development of SC process parameter research have been proposed.

Keywords

• Squeeze casting
• Process parameter design
• Process parameter optimization
• Data-driven
• Neural network
• Research method analysis