An experimental study on grinding of Zr-based bulk metallic glass

Bakkal, Mustafa; Serbest, Erdinc; Karipçin, İlker; Kuzu, Ali Taner; Karagüzel, Umut; Derin, Bora

doi:10.1007/s40436-015-0121-6

Cited by 14 publications

(9 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In general, SECsl decreases as the speed of the workpiece increases. A similar behavior was reported by Bakkal et al [23], who described that, in grinding, the ratio between tangential and normal forces increased as the speed of the workpiece increased.…”

Section: Resultssupporting

confidence: 87%

See 1 more Smart Citation

Model Based on an Effective Material-Removal Rate to Evaluate Specific Energy Consumption in Grinding

et al. 2019

View full text Add to dashboard Cite

Grinding energy efficiency depends on the appropriate selection of cutting conditions, grinding wheel, and workpiece material. Additionally, the estimation of specific energy consumption is a good indicator to control the consumed energy during the grinding process. Consequently, this study develops a model of material-removal rate to estimate specific energy consumption based on the measurement of active power consumed in a plane surface grinding of C45K with different thermal treatments and AISI 304. This model identifies and evaluates the dissipated power by sliding, ploughing, and chip formation in an industrial-scale grinding process. Furthermore, the instantaneous positions of abrasive grains during cutting are described to study the material-removal rate. The estimation of specific chip-formation energy is similar to that described by other authors on a laboratory scale, which allows to validate the model and experiments. Finally, the results show that the energy consumed by sliding is the main mechanism of energy dissipation in an industrial-scale grinding process, where it is denoted that sliding energy by volume unity decreases as the depth of cut and the speed of the workpiece increase.

show abstract

Section: Resultssupporting

confidence: 87%

“…In the chip-removal process, SEC is directly proportional to the relation between consumed power and Qw [23]. If Equation (1) is divided by Qw and reorganized, then Equation (2) is obtained as follows:P−PslQw=PplQw+SECch where SECch is the specific energy consumed by chip formation.…”

Section: Model Of Specific Energy Consumptionmentioning

confidence: 99%

Model Based on an Effective Material-Removal Rate to Evaluate Specific Energy Consumption in Grinding

et al. 2019

View full text Add to dashboard Cite

show abstract

“…As BMGs are known as difficult-to-machine materials, abrasive finishing processes have become a popular method for generating a final surface finish on BMGs. Bakkal et al ( 2015) [86] investigated the machinability of Zr-based bulk metallic glass (Zr52.5Ti5Cu17.9Ni14.6Al10) using grinding processes. Their study focused on the grindability of materials using a CBN wheel as well as conventional aluminum oxide wheel; the effect of grinding parameters such as feed rate, cutting speed, depth of cut, and type and size of abrasive were considered.…”

Section: Grinding Of Metallic Glassmentioning

confidence: 99%

Multi-Scale Traditional and Non-Traditional Machining of Bulk Metallic Glasses (BMGs)—Review of Challenges, Recent Advances, and Future Directions

Jahan,

Niraula,

Nafi

et al. 2024

Micromachines

View full text Add to dashboard Cite

Bulk metallic glasses (BMGs) are growing in popularity prominently due to their potential in micro-electromechanical systems (MEMSs) and aerospace applications. BMGs have unique mechanical properties, i.e., high strength, hardness, modulus of elasticity, and wear resistance, due to their disordered atomic structure. Due to their unique mechanical properties and amorphous structures, machining of BMGs remains a challenge. This paper aims to carry out a detailed literature review on various aspects of the machining of bulk metallic glasses using both conventional and non-conventional processes, including experimental approaches, modeling, statistical findings, challenges, and guidelines for machining this difficult-to-machine material. Conventional machining processes were found to be challenging for machining bulk metallic glasses due to their high hardness, brittleness, and tendency to convert their amorphous structure into a crystalline structure, especially at the machined surface and sub-surface. Although their high electrical conductivity makes them suitable for machining by non-conventional processes, they impose new challenges such as heat-affected zones and crystallization. Therefore, the successful machining of BMGs requires more in-depth analysis of cutting forces, tool wear, burr formation, surface finish, recast layers or heat-affected zones, crystallization, and mechanical property changes among different varieties of BMGs. This review paper provides guidelines emerging from in-depth analysis of previous studies, as well as offering directions for future research in the machining of BMGs.

show abstract

“…[235] The feed rate of the specimen is another important consideration to avoid devitrification. For Zr 52.5 Ti 5 Cu 17.9 Ni 14.6 Al 10 rods cut in dry conditions without coolant, [236] a higher feed rate of 4000 mm min À1 resulted in specimens that did not crystallize, even though the temperature that was reached during cutting was greater than the glass transition temperature. This effect can be attributed to the lower contact time between the specimen and the cutting tool.…”

Section: Machining and Cutting Techniquesmentioning

confidence: 99%

Latest Advances in Manufacturing and Machine Learning of Bulk Metallic Glasses

et al. 2023

View full text Add to dashboard Cite

In this review, two interrelated areas are focused on for the development of novel amorphous metallic alloys, namely, materials processing and machine learning techniques for the design of new alloy compositions. Findings, barriers, and opportunities are described, targeting powder production and sintering, additive manufacturing, and postprocessing techniques, followed by the latest developments in artificial intelligence algorithms for both the design of new alloys and for alloy classification tasks.

show abstract

An experimental study on grinding of Zr-based bulk metallic glass

Cited by 14 publications

References 19 publications

Model Based on an Effective Material-Removal Rate to Evaluate Specific Energy Consumption in Grinding

Model Based on an Effective Material-Removal Rate to Evaluate Specific Energy Consumption in Grinding

Multi-Scale Traditional and Non-Traditional Machining of Bulk Metallic Glasses (BMGs)—Review of Challenges, Recent Advances, and Future Directions

Latest Advances in Manufacturing and Machine Learning of Bulk Metallic Glasses

Contact Info

Product

Resources

About