Machine learning methods was applied to combine experimental data with simulation analysis to systemati-cally optimize the temperature,cooling rate,alloy composition,etc.,during investment casting process.By collecting a large amount of casting process data,a prediction model for process parameter based on deep learning was con-structed to optimize the design of process parameters,and the model was validated through on-site experiments.The results indicate that the microstructure and mechanical properties of castings are significantly improved after optimizing casting process by machine learning methods,and the defect rates are reduced,enhancing productivity and economic benefits.In the context of machine learning,the casting quality score of the optimal parameter array is significantly higher than that of suboptimal parameter array in the comparison of parameter groups,and only one group of the opti-mal parameter array gets below 90 points,while the suboptimal parameter groups all get below 90 points.
In this study, near-liquidus squeeze casting AZ91D alloy was used to prepare differential support, and the microstructure and mechanical behavior under different applied pressure were investigated. Under the preset temperature, speed, and other process parameters, the effect of applied pressure on the microstructure and properties of formed parts was analyzed, and relevant mechanism was also discussed. The results showed that the ultimate tensile strength (UTS) and elongation (EL) of differential support can be improved by controlling real-time precision of the forming pressure. The dislocation density in the primary phase increased obviously with the pressure increasing from 80 MPa to 170 MPa, and even tangles appeared. When the applied pressure increased from 80 MPa to 140 MPa, the α-Mg grains were gradually refined, and the microstructure changed from rosette to globular shape. With increasing the applied pressure to 170 MPa, the grain could not be further refined. Similarly, its UTS and EL gradually increased with the applied pressure increasing from 80 MPa to 140 MPa. With increasing to 170 MPa, the UTS tended to be constant, but the EL gradually decreased. In other words, the UTS (229.2 MPa) and EL (3.43%) of the alloy reached the maximum when the applied pressure was 140 MPa, and the comprehensive mechanical properties were the best.
Taking water as a binder to solidify the sand mold,frozen casting is paid attention as a new green cast-ing method.The effects of freezing temperature and composition proportion of frozen casting sand on the strength and air permeability of frozen casting mold were investigated.The mold performance under different water and clay contents,cooling temperatures and sand mesh conditions was explored experimentally,and the mold transi-tion under different pouring temperatures were also systematically carried out.The results indicate that the over-all performance of frozen casting is superior to that of resin mold under the premise of low cost,which is more environmentally friendly with widely application,and possesses positive significance for promoting the goal of carbon peak and carbon neutrality.
伴随互联网的普及,网络经济成为推动社会经济发展的重要驱动力,与此同时,铸造企业营销也面临着新的机遇和挑战.传统的营销模式已经难以适应快速变化的市场环境,因此,铸造企业需要创新营销策略,提升市场竞争力.在网络经济背景下,铸造企业可以通过互联网平台建立线上销售渠道,实现产品的全球化推广.同时,通过大数据分析、人工智能等技术手段,铸造企业可以更好地把握消费者需求,精准定位目标市场,并提供个性化服务,满足消费者的多样化需求.但是,铸造企业在网络经济背景下进行营销创新也面临一些挑战.由于铸造产品的特殊性,传统的销售渠道很难直接转移到互联网平台上,铸造企业需审慎优化营销策略,确保其稳定发展.因此,深入探究网络经济背景下铸造企业的营销创新,对于促进企业的可持续发展具有重要意义,可以为制造业企业在网络经济时代寻找合适的营销路径提供参考.
Al-Cu alloys with different Cu content were fabricated by casting method,and the microstructure,damping properties and storage modulus of Al-Cu alloys were investigated.The results indicate that Al2Cu phase in the Al-3Cu and Al-4Cu alloys is fine and uniformly distributed,while large amounts of massive and stripped Al2Cu phases are distributed in Al-5.7Cu,Al-10Cu,and Al-20Cu alloys.Al-Cu alloys with high copper content exhibit desirable damping performance.The internal friction value of Al-20Cu alloy is 168％and 352.7％higher than that of Al-3Cu and 2024 Al alloy at 350 ℃,respectively.Al2Cu phase hinders the dislocation slip in Al ma-trix,leading to the increase of residual internal stress after deformation,and the increase of storage modulus of Al-Cu alloy with the increase of Cu content.The storage modulus of Al-5.7Cu,Al-10Cu,and Al-20Cu alloys are higher than that of 2024 Al alloy,and the EIF value of Al-20Cu alloy is 230％higher than that of 2024 Al alloy.
