Efficiency of Tool Steel Cutting by Water Jet with Recycled Abrasive Materials

被引:17
作者
Perec, Andrzej [1 ]
Radomska-Zalas, Aleksandra [1 ]
Fajdek-Bieda, Anna [1 ]
Kawecka, Elzbieta [1 ]
机构
[1] Jacob Paradies Univ, Fac Technol, PL-66400 Gorzow Wielkopolski, Poland
关键词
abrasive water jet; AWJ; cutting depth; process efficiency; molybdenum tool steel; response surface method; RSM; modeling; optimization; NUMERICAL-ANALYSIS; OPTIMIZATION; MACHINABILITY; SUPERALLOY; SIMULATION; SURFACE; TIME;
D O I
10.3390/ma15113978
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
High-pressure water jet machining is characterized by wide possibilities of cutting diverse materials together with multi-layer materials with dissimilar properties, accurate cutting complex profiles, as well as conducting them in uncommon conditions, especially in cases of thick materials. An additional advantage of water jet technology is its environmental friendliness. This paper presents tests of the cutting performance of tool steel with the use of an abrasive water jet (AWJ). The state-of-the-art has shown insufficient scientific evidence in AWJ tool steels cutting using recycled abrasive materials. Therefore, the main motivation for this paper was to carry out research from an environment aspect. The reuse of abrasives and the use of recycled materials have immense potential to reduce processing costs while remaining environmentally friendly. The RSM method was used for modeling and optimization. A response surface design (RSM) is a package of an advanced design-of-experiment (DOE) approaches that support better understanding and optimize response, exploring the relationships between several explanatory variables and one or more response variables. Based on this research, feed rate is the key factor influencing the depth of cut, while the water nozzle diameter has a secondary effect, and the concentration of abrasive has the least influence on the depth of cut. High level of variance (the percentage of variability in the reaction that is interpreted by the formula) confirms that the models fit well to the investigational data.
引用
收藏
页数:16
相关论文
共 50 条
[21]   EXPERIMENTAL RESEARCH INTO MARBLE CUTTING BY ABRASIVE WATER JET [J].
Perec, Andrzej ;
Radomska-Zalas, Aleksandra ;
Fajdek-Bieda, Anna .
FACTA UNIVERSITATIS-SERIES MECHANICAL ENGINEERING, 2022, 20 (01) :145-156
[22]   Research on the method of stacked cutting of abrasive water jet [J].
Miao, Xiaojin ;
Wu, Meiping ;
Song, Lei ;
Ye, Feng ;
Qiang, Zhengrong .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2019, 103 (1-4) :597-604
[23]   Investigation of process parameters influence in abrasive water jet cutting of D2 steel [J].
Yuvaraj, Natarajan ;
Kumar, Murugasen Pradeep .
MATERIALS AND MANUFACTURING PROCESSES, 2017, 32 (02) :151-161
[24]   Determination of vibration frequency depending on abrasive mass flow rate during abrasive water jet cutting [J].
Hreha, Pavol ;
Radvanska, Agata ;
Hloch, Sergej ;
Perzel, Vincent ;
Krolczyk, Grzegorz ;
Monkova, Katarina .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2015, 77 (1-4) :763-774
[25]   Study of Cutting Composite Materials with Low Pressure Abrasive-water Jet [J].
Zou Zhenglong .
MECHANICAL AND ELECTRONICS ENGINEERING III, PTS 1-5, 2012, 130-134 :1480-1483
[26]   Abrasive suspension water jet cutting optimization using orthogonal array design [J].
Perec, Andrzej .
INTERNATIONAL CONFERENCE ON MANUFACTURING ENGINEERING AND MATERIALS, ICMEM 2016, 2016, 149 :366-373
[27]   A study on the abrasive water jet cutting for granite [J].
Liu, Y ;
Chen, X .
ADVANCES IN ABRASIVE TECHNOLOGY VI, 2004, 257-258 :527-532
[28]   Modelling of the abrasive water jet cutting process [J].
Deam, RT ;
Lemma, E ;
Ahmed, DH .
WEAR, 2004, 257 (9-10) :877-891
[29]   PARAMETRIC INVESTIGATION OF ABRASIVE WATER JET CUTTING OF TITANIUM ALLOY [J].
Mahmood, Khalid .
PROCEEDINGS OF ASME 2024 19TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, MSEC2024, VOL 2, 2024,
[30]   The optimal cutting times of multipass abrasive water jet cutting [J].
Xiaojin Miao ;
Zhengrong Qiang ;
Meiping Wu ;
Lei Song ;
Feng Ye .
The International Journal of Advanced Manufacturing Technology, 2018, 97 :1779-1786