Intelligent Optimization of Hard-Turning Parameters Using Evolutionary Algorithms for Smart Manufacturing

Mia, Mozammel; Królczyk, Grzegorz; Maruda, Radosław W.; Wojciechowski, Szymon

doi:10.3390/ma12060879

Cited by 66 publications

(42 citation statements)

References 19 publications

(24 reference statements)

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“…However, the axial depth of cut, cutting speed and feed per tooth have a slight influence on surface roughness within the investigated range. Mia et al [10] proposed the application of evolutionary-based algorithms (teaching-learning-based optimization and bacterial foraging optimization) for the optimization of the hardened high-carbon steel AISI 1060 turning process. It was found that teaching-learning-based optimization (TLBO) was found to be superior to the bacteria foraging optimization (BFO) in terms of better convergence and a shorter time of computation-hence, the TLBO is recommended during the optimization of hard turning processes.…”

Section: Ofmentioning

confidence: 99%

Advances in Hard–to–Cut Materials: Manufacturing, Properties, Process Mechanics and Evaluation of Surface Integrity

2020

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The rapid growth of a modern industry results in a growing demand for construction materials with excellent operational properties. However, the improved features of these materials can significantly hinder their manufacturing, therefore they can be defined as hard–to–cut. The main difficulties during the manufacturing/processing of hard–to–cut materials are attributed to their high hardness and abrasion resistance, high strength at room or elevated temperatures, increased thermal conductivity, as well as their resistance to oxidation and corrosion. Nowadays the group of hard–to–cut materials includes the metallic materials, composites, as well as ceramics. This special issue, “Advances in Hard–to–Cut Materials: Manufacturing, Properties, Process Mechanics and Evaluation of Surface Integrity” provides a collection of research papers regarding the various problems correlated with hard–to–cut materials. The analysis of these studies reveals primary directions regarding the developments in manufacturing methods, and the characterization and optimization of hard–to–cut materials.

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Section: Ofmentioning

confidence: 99%

Advances in Hard–to–Cut Materials: Manufacturing, Properties, Process Mechanics and Evaluation of Surface Integrity

2020

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“…Cutting tool behavior knowledge has proven to be key in optimizing the turning process. By changing these parameters accordingly, a process can be optimized to meet the expected results [39], such as in the study performed by Krishnan [40], which used the Taguchi method to predict the best parameters to attain the lowest surface roughness when turning IS2062 E250 Steel. The parameters that were varied (input parameters) were the cutting speed, depth of cut and feed rate.…”

Section: Introductionmentioning

confidence: 99%

Recent Advances in Turning Processes Using Coated Tools—A Comprehensive Review

Sousa

Silva

2020

Metals

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Turning continues to be the largest segment of the machining industry, which highlights the continued demand for turned parts and the overall improvement of the process. The turning process has seen quite an evolution, from basic lathes using solid tools, to complex CNC (Computer Numerical Control) multi-process machines, using, for the most part, coated inserts and coated tools. These coatings have proven to be a significant step in the production of high-quality parts and a higher tool life that have captivated the industry. Continuous improvement to turning coated tools has been made, with many researches focusing on the optimization of turning processes that use coated tools. In the present paper, a presentation of various recently published papers on this subject is going to be made, mentioning the various types of coatings that have recently been used in the turning process, the turning of hard to machine materials, such as titanium alloys and Inconel, as well as the interaction of these coatings with the turned surfaces, the wear patterns that these coatings suffer during the turning of materials and relating these wear mechanisms to the coated tool’s life expectancy. Some lubrication conditions present a more sustainable alternative to current methods used in the turning process; the employment of coated tool inserts under these conditions is a current popular research topic, as there is a focus on opting for more eco-friendly machining options.

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“…It is dependent on a larger machine and the dynamic errors' source on machine structure. Mia et al [18] presented intelligent optimization of hard-turning parameters. This paper proposed the evolutionary algorithms for cutting conditions.…”

Section: Introductionmentioning

confidence: 99%

Development of an Analyzing and Tuning Methodology for the CNC Parameters Based on Machining Performance

Chen

2020

Applied Sciences

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This paper proposes the development of a tuning methodology which can set the proper values of the Computer Numerical Control (CNC) parameters to achieve the required machining performance. For the conventional operators of machine tools, the CNC parameters were hard to be adjusted to optimal settings, which was a complicated and time-consuming task. To save time in finding optimal CNC parameters, the objective of this research was to develop a practical methodology to tune the CNC parameters effectively for easy implementation in the commercial CNC controller. Firstly, the effect of the CNC parameters in the CNC controller on the tool-path planning was analyzed via experiments. The machining performance was defined in the high-speed (HS) mode, the high-accuracy (HP) mode, and the high-surface-quality (HQ) mode, according to the dynamic errors of several specified paths. Due to the CNC parameters that have a particularly critical effect on the dynamic errors, the relationship between the CNC parameters and the dynamic errors was validated by the measured data. Finally, the tuning procedure defined the anticipated dynamic errors for the three machining modes with the actual machine. The CNC parameters will correspond with anticipated dynamics errors based on several specified paths. The experimental results showed that the HS mode was the fastest to complete the path, and the completion time of the HP and HQ modes were increased by 37% and 6%, respectively. The HP mode had the smallest dynamic errors than other modes, and the dynamic errors of the HS and HQ modes are increased by 66% and 16%. In the HQ mode, the motion oscillation was reduce significantly, and the tracking error of the HS and HP modes were increased by 85% and 28%. The advantage of the methodology is that it simplifies set-up steps of the CNC parameters, making it suitable for practical machine applications.

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Intelligent Optimization of Hard-Turning Parameters Using Evolutionary Algorithms for Smart Manufacturing

Cited by 66 publications

References 19 publications

Advances in Hard–to–Cut Materials: Manufacturing, Properties, Process Mechanics and Evaluation of Surface Integrity

Advances in Hard–to–Cut Materials: Manufacturing, Properties, Process Mechanics and Evaluation of Surface Integrity

Recent Advances in Turning Processes Using Coated Tools—A Comprehensive Review

Development of an Analyzing and Tuning Methodology for the CNC Parameters Based on Machining Performance

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