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Modeling, analysis, and optimization of dimensional accuracy of FDM-fabricated parts using definitive screening design and deep learning feedforward artificial neural network

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Advances in Manufacturing 2021年第1期9卷 115-129页

作者： Omar Ahmed Mohamed Syed Hasan Masood jahar lal bhowmik School of Engineering Deakin UniversityGeelongAustralia Department of Mechanical Engineering Higher Institute of Engineering TechnologyBani WalidLibya Department of Mechanical and Product Design Engineering Swinburne University of TechnologyHawthornVIC 3122Australia Department of Health Science and Biostatistics Swinburne University of TechnologyHawthornVIC 3122Australia

Additive manufacturing(AM)technologies such as fused deposition modeling(FDM)rely on the quality of manufactured products and the process ***,the dimensional accuracy and stability of any AM process is essential for ensuring that customer specifications are satisfied at the highest standard,and variations are controlled without significantly affecting the functioning of processes,machines,and product *** study aims to investigate the effects of FDM fabrication conditions on the dimensional accuracy of cylindrical *** this study,a new class of experimental design techniques for integrated second-order definitive screening design(DSD)and an artificial neural network(ANN)are proposed for designing experiments to evaluate and predict the effects of six important operating *** determining the optimum fabrication conditions to obtain better dimensional accuracies for cylindrical parts,the time consumption and number of complex experiments are reduced considerably in this *** optimum fabrication conditions generated through a second-order DSD are verified with experimental *** results indicate that the slice thickness,part print direction,and number of perimeters significantly affect the percentage of length difference,whereas the percentage of diameter difference is significantly affected by the raster-to-raster air gap,bead width,number of perimeters,and part print ***,the results demonstrate that a second-order DSD integrated with an ANN is a more attractive and promising methodology for AM applications.

关键词： Artificial neural network(ANN) OptimizationDefinitive screening design(DSD) Analysis of variance(ANOVA) Fused deposition modeling(FDM) Dimensional accuracy

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Optimization of fused deposition modeling process parameters:a review of current research and future prospects

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Advances in Manufacturing 2015年第1期3卷 42-53页

作者： Omar A.Mohamed Syed H.Masood jahar L.bhowmik Department of Mechanical and Product Design Engineering Faculty of ScienceEngineering and TechnologySwinburne University of TechnologyHawthornMelbourneAustralia Department of Psychological Sciences and Statistics Faculty of HealthArts and DesignSwinburne University of TechnologyHawthornMelbourneAustralia

Fused deposition modeling （FDM） is one of the most popuIar additive manufacturing technologies for various engineering applications. FDM process has been introduced commercially in early 1990s by Stratasys Inc., USA. The quality of FDM processed parts mainly depends on careful selection of process variables. Thus, identifica- tion of the FDM process parameters that significantly affect the quality of FDM processed parts is important. In recent years, researchers have explored a number of ways to improve the mechanical properties and part quality using various experimental design techniques and concepts. This article aims to review the research carried out so far in determining and optimizing the process parameters of the FDM process. Several statistical designs of experiments and optimization techniques used for the determination of optimum process parameters have been examined. The trends for future FDM research in this area are described.

关键词： Fused deposition modeling (FDM) -Experimental design. Additive manufacturing. Processparameters. Mechanical properties.Part quality

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Influence of peach(Prunus persica Batsch)phenological stage on the short-term changes in oxidizable and labile pools of soil organic carbon and activities of carbon-cycle enzymes in the North-Western Himalayas

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Pedosphere 2020年第5期30卷 638-650页

作者： Sovan DEBNATH Brij Lai ATTRI Anil KUMAR Arun KISHOR Raj NARAYAN Kanchan SINHA Arpan bhowmik Anil SHARMA Desh Beer SINGH Indian Council of Agricultural Research(lCAR)-Central Institute of Temperate Horticulture Regional StationMukteshwarNainitalUttarakhand 263138(India) Department of Agricultural Chemistry and Soil Science Faculty of AgricultureBidhan Chandra Krishi ViswavidyalayaMohanpurWest Bengal 741252(India) Indian Council of Agricultural Research(ICAR)-Directorate of Mushroom Research SolanHimachal Pradesh 173213(India) A Indian Council of Agricultural Research(ICAR)-Indian Agricultural Statistics Research Institute New Delhi 110012(India) Department of Agricultural Statistics Faculty of AgricultureBidhan Chandra Krishi ViswavidyalayaMohanpurWest Bengal 741252(India) Indian Council of Agricultural Research(ICAR)-Central Institute of Temperate Horticulture SrinagarJammu and Kashmir 190007(India)

The labile organic carbon(C)and C-related enzymes are sensitive indicators capturing alterations of soil organic matter(SOM),even in a short-time *** the effects of crop husbandry and land use change on these attributes have been well studied,there is no consensus about how plant phenology may impact *** study aimed to determine the short-term effect o f six distinct phenological stages(PS-1:full bloom;PS-2:fruit set;PS-3:pit hardening;PS-4:physiological maturity;PS-5:60 d after physiological maturity;and PS-6:fall)o f peach on the changes in soil organic carbon(SOC)fractions of different oxidizability,labile C pools,and C-cycle enzyme activities in soils,for two consecutive years(2015 and 2016)in the North-Western Himalayas(NWH).Peach rhizosphere soils were sampled at the topsoil(0-15 cm)and subsoil(16-30 cm)layers,along with rhizosphere soils from adjacent perennial grasses,which served as a *** for most of the assessed parameters,including very labile C,labile C,microbial biomass C,permanganate oxidizable C,dissolved organic C,mineralizable C,amylase activity,and carboxymethyl-cellulase activity,were significantly(P<0.05)higher at PS-3 than at other phenological stages of ***,a sudden decline in these soil variables was recorded at PS-5,followed by a slight buildup at PS-6,particularly in the topsoil of the peach ***-term changes in organic C fractions of different oxidizability,influenced by peach phenological stage,significantly(P<0.05)affected C management index,C pool index,and lability *** the C management index and lability index showed their highest values at PS-3 and their lowest values at PS-5,clearly indicating short-term accretion and depletion of SOC,in tandem with the peach phenological *** component analysis suggested that a composite of soil indicators,including microbial biomass C,dissolved organic C,amylase,and invertase,could help detect short-term changes in SOC *** i

关键词： carbon fractions fruit orchard Indian Himalaya plant phenology rhizosphere soil soil biological indicators

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