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Grzegorz Królczyk

Bio: Grzegorz Królczyk is an academic researcher from Opole University of Technology. The author has contributed to research in topics: Machining & Surface roughness. The author has an hindex of 41, co-authored 198 publications receiving 4659 citations. Previous affiliations of Grzegorz Królczyk include University of Ljubljana & Opole University.

Papers published on a yearly basis

Papers
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Journal ArticleDOI
TL;DR: In this paper, a comprehensive analysis of literature pertaining to ecological trends in machining processes of difficult-to-cut materials (e.g. hard steels, Ti-based alloys, Ni based alloys) has been performed.

260 citations

Journal ArticleDOI
TL;DR: In this article, the effect of three sustainable techniques, along with the traditional flood cooling system, on prominent machining indices such as cutting temperature, surface roughness, chip characteristics and tool wear in plain turning of hardened AISI 1060 steel has been investigated.

202 citations

Journal ArticleDOI
TL;DR: In this paper, the influence of emulsion mist formation parameters and the nozzle distance from the tool-chip interface, on the droplet velocity at the nozzle outlet, on active medium atomization angle as well as on the diameter and number of droplets supplied to the cutting zone was analyzed.
Abstract: The paper analyses the influence of emulsion mist formation parameters and the nozzle distance from the tool–chip interface, on the droplet velocity at the nozzle outlet, on active medium atomization angle as well as on the diameter and number of droplets supplied to the cutting zone. The deformation coefficient of the droplets falling on the surface and the wetting angle have also been determined. In the work it has been proved that the strongest influence on the droplets diameter have the air flow and the distance of the nozzle from the cutting zone. It has been shown that larger angle of the stream splitting ensures that the droplets do not join each other in the air, and consequently assures small diameter on the surface. Additionally, the results show that the emulsion mass flow does not change the droplets diameters by more than 12%. It has been determined that smaller the droplets diameter is, higher content of active compounds in the tribofilms formed on the machined surface is present. In this way the paper presents the analysis and directions of MQCL adjustment trends needed to improve the machining performance.

183 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present a summary of the previously published research articles on minimum quantity lubrication (MQL) assisted machining and explore the benefits of the vegetable oil and nanofluid as a lubricant.
Abstract: In modern days, the conception of sustainability has progressively advanced and has begun receiving global interest. Thus, sustainability is an imperative idea in modern research. Considering the recent trend, this review paper presents a summary of the previously published research articles on minimum quantity lubrication (MQL) assisted machining. The requirement to stir towards sustainability motivated the researchers to revise the effects of substitute lubrication methods on the machining. Conventional lubri-cooling agents are still extensively employed when machining of engineering alloys, but the majority of the recent papers have depicted that the utilization of vegetable oil, nanofluids, and nanoplatelets in MQL system confers superior machining performances as compared to conventional lubrication technology. In actual, the definite principle of this manuscript is to re-examine modern advancements in the MQL technique and also explore the benefits of the vegetable oil and nanofluid as a lubricant. In brief, this paper is a testimony to the advancing capabilities of eco-friendly MQL technique which is a viable alternative to the flood lubrication technology, and the outcomes of this review work can be contemplated as a movement towards sustainable machining.

166 citations

Journal ArticleDOI
TL;DR: In this paper, the cutting force, specific energy, temperature, surface quality (i.e. surface roughness), and material removal rate under the impingement of liquid nitrogen (LN2) as mono-jet and dual-jets were investigated.

151 citations


Cited by
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Journal Article
TL;DR: This book by a teacher of statistics (as well as a consultant for "experimenters") is a comprehensive study of the philosophical background for the statistical design of experiment.
Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

13,333 citations

Journal ArticleDOI
TL;DR: A comprehensive analysis of surface texture metrology for metal additive manufacturing has been performed in this paper, where the results of this analysis are divided into sections that address specific areas of interest: industrial domain; additive manufacturing processes and materials; types of surface investigated; surface measurement technology and surface texture characterisation.
Abstract: A comprehensive analysis of literature pertaining to surface texture metrology for metal additive manufacturing has been performed. This review paper structures the results of this analysis into sections that address specific areas of interest: industrial domain; additive manufacturing processes and materials; types of surface investigated; surface measurement technology and surface texture characterisation. Each section reports on how frequently specific techniques, processes or materials have been utilised and discusses how and why they are employed. Based on these results, possible optimisation of methods and reporting is suggested and the areas that may have significant potential for future research are highlighted.

537 citations

Journal ArticleDOI
Xian Tao, Dapeng Zhang, Ma Wenzhi, Xilong Liu, De Xu 
TL;DR: This paper discusses the automatic detection of metallic defects with a twofold procedure that accurately localizes and classifies defects appearing in input images captured from real industrial environments using a novel cascaded autoencoder (CASAE) architecture.
Abstract: Automatic metallic surface defect inspection has received increased attention in relation to the quality control of industrial products. Metallic defect detection is usually performed against complex industrial scenarios, presenting an interesting but challenging problem. Traditional methods are based on image processing or shallow machine learning techniques, but these can only detect defects under specific detection conditions, such as obvious defect contours with strong contrast and low noise, at certain scales, or under specific illumination conditions. This paper discusses the automatic detection of metallic defects with a twofold procedure that accurately localizes and classifies defects appearing in input images captured from real industrial environments. A novel cascaded autoencoder (CASAE) architecture is designed for segmenting and localizing defects. The cascading network transforms the input defect image into a pixel-wise prediction mask based on semantic segmentation. The defect regions of segmented results are classified into their specific classes via a compact convolutional neural network (CNN). Metallic defects under various conditions can be successfully detected using an industrial dataset. The experimental results demonstrate that this method meets the robustness and accuracy requirements for metallic defect detection. Meanwhile, it can also be extended to other detection applications.

288 citations

Journal ArticleDOI
TL;DR: In this article, an early fault diagnostic technique based on acoustic signals was used for a single-phase induction motor, which can be also used for other types of rotating electric motors.

286 citations