{"title":"Experimental investigation and modelling of the kerf profile in submerged milling by macro abrasive waterjet","authors":"R. Ravi, Deepu Kumar T. N., D. Srinivasu","doi":"10.1115/1.4062547","DOIUrl":null,"url":null,"abstract":"\n Towards achieving control over the kerfing through abrasive waterjet submerged milling, there is a need to (i) understand the influence of the water column height on the kerf quality and (ii) develop a model for the prediction of the kerf characteristics. This study performs detailed experimentation to assess the kerf quality enhancement in submerged milling relative to the in-air on Al6061. From the modelling perspective, there are very limited efforts in developing a comprehensive model that includes both the jet flow dynamics and material removal models - this is the missing link. Towards this, a comprehensive model is proposed and validated for the prediction of kerf in in-air and submerged conditions by considering (i) jet dynamics and (ii) jet-material interaction. From the experimental results, it is observed that by adopting the submerged milling, the damaged region, top kerf width and edge radius got reduced by 20.3%, 13.53%, and 22.7%, respectively. However, this enhancement in the kerf quality is associated with a reduction in the centreline erosion depth (hmax) by 12.33% and a material removal rate by 24.52%. The material removal mechanism is more uniform and directed in the submerged milling, whereas in-air is random. The proposed model predicted the kerf cross-sectional profile in submerged milling and in-air with a mean absolute error of 60 μm and 57 μm, squared Pearson correlation coefficient of 0.97 and 0.99, and the hmax with a maximum error of 1.3% and 1.4%.","PeriodicalId":16299,"journal":{"name":"Journal of Manufacturing Science and Engineering-transactions of The Asme","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Manufacturing Science and Engineering-transactions of The Asme","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1115/1.4062547","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 0
Abstract
Towards achieving control over the kerfing through abrasive waterjet submerged milling, there is a need to (i) understand the influence of the water column height on the kerf quality and (ii) develop a model for the prediction of the kerf characteristics. This study performs detailed experimentation to assess the kerf quality enhancement in submerged milling relative to the in-air on Al6061. From the modelling perspective, there are very limited efforts in developing a comprehensive model that includes both the jet flow dynamics and material removal models - this is the missing link. Towards this, a comprehensive model is proposed and validated for the prediction of kerf in in-air and submerged conditions by considering (i) jet dynamics and (ii) jet-material interaction. From the experimental results, it is observed that by adopting the submerged milling, the damaged region, top kerf width and edge radius got reduced by 20.3%, 13.53%, and 22.7%, respectively. However, this enhancement in the kerf quality is associated with a reduction in the centreline erosion depth (hmax) by 12.33% and a material removal rate by 24.52%. The material removal mechanism is more uniform and directed in the submerged milling, whereas in-air is random. The proposed model predicted the kerf cross-sectional profile in submerged milling and in-air with a mean absolute error of 60 μm and 57 μm, squared Pearson correlation coefficient of 0.97 and 0.99, and the hmax with a maximum error of 1.3% and 1.4%.
期刊介绍:
Areas of interest including, but not limited to: Additive manufacturing; Advanced materials and processing; Assembly; Biomedical manufacturing; Bulk deformation processes (e.g., extrusion, forging, wire drawing, etc.); CAD/CAM/CAE; Computer-integrated manufacturing; Control and automation; Cyber-physical systems in manufacturing; Data science-enhanced manufacturing; Design for manufacturing; Electrical and electrochemical machining; Grinding and abrasive processes; Injection molding and other polymer fabrication processes; Inspection and quality control; Laser processes; Machine tool dynamics; Machining processes; Materials handling; Metrology; Micro- and nano-machining and processing; Modeling and simulation; Nontraditional manufacturing processes; Plant engineering and maintenance; Powder processing; Precision and ultra-precision machining; Process engineering; Process planning; Production systems optimization; Rapid prototyping and solid freeform fabrication; Robotics and flexible tooling; Sensing, monitoring, and diagnostics; Sheet and tube metal forming; Sustainable manufacturing; Tribology in manufacturing; Welding and joining