Manufacturing Characteristics Research Articles

Manufacturing Feature Recognition with a Sparse Voxel-based Convolutional Neural Network

Abstract Automated manufacturing feature recognition is a crucial link between computer-aided design and manufacturing, facilitating process selection and other downstream tasks in computer-aided process planning. While various methods such as graph-based, rule-based, and neural networks have been proposed for automatic feature recognition, they suffer from poor scalability or computational inefficiency. Recently, voxel-based convolutional neural networks have shown promise in solving these challenges but incur a tradeoff between computational cost and feature resolution. This paper investigates a computationally efficient sparse voxel-based convolutional neural network for manufacturing feature recognition, specifically, an octree-based sparse voxel convolutional neural network. This model is trained on a large-scale manufacturing feature dataset, and its performance is compared to a voxel-based feature recognition model (FeatureNet). The results indicate that the octree-based model yields higher feature recognition accuracy (99.5% on the test dataset) with 44% lower GPU memory consumption than a voxel-based model of comparable resolution. In addition, increasing the resolution of the octree-based model enables recognition of finer manufacturing features. These results indicate that a sparse voxel-based convolutional neural network is a computationally efficient deep learning model for manufacturing feature recognition to enable process planning automation. Moreover, the sparse voxel-based neural network demonstrated comparable performance to a boundary representation-based feature recognition neural network, achieving similar accuracy in single feature recognition without having access to the exact 3D shape descriptors

Red Deer Antler Artefacts from Gordineşti II- ”Stînca goală” and Vynnyky-”Zhupan”: Shape-and-Trace Formation Processes in Natural, Functional and Depositional Contexts

The paper scrutinizes the red deer hard tissues from the contexts attributed to the Trypillia Culture’s final phases. Having once been reported elsewhere, the objects under study are this time conceptualized in terms of shape-and trace formation processes, with an eye to incorporating them into research advances under the topic of the late Trypillia transformation, including typological affiliation, radiocarbon dating, archaeoecology, subsistence studies, etc. Particular attention is paid to artefacts that lack the overwhelming power of the tiniest wear marks, but do display extensive topographic features of manufacture and use. The formalized shape-and-trace aspects for the antler artefacts are proposed, which are considered to be suitable rather for a morphological than for a morphographicsystematization of a prehistoric antler assemblage. An interpretative application of the shape-and-trace approach for the sake of clarification of both past currents in morphogenesis of artefacts and praxis of their use is only possible in a systemic context of knowledge about habitats and lifestyles of the past.

МАГИЧЕСКОЕ ОРУЖИЕ ГЕРОЕВ ЭПОСА «НАРТЫ»

The article examines the archaic cult of the god of iron and the patron saint of metal Tlepsh, the emergence of metallurgy, the creation of the first weapons and armor made of metal, which are reflected in the Adyghe heroic epic Narts. The relevance of the article is due to the fact that the heroic epic Narts is almost not considered in the scientific literature as a source of information for the study of objects and tools, the creation of the first weapon, the addition of a complex of weapons and armor of horsemen. The purpose of the study is to compare the weapons of the heroes of the Nart epic, endowed with magical properties, having certain qualitative characteristics, technological features of manufacture, with the materials of archaeological sites of the Northwestern Caucasus. To achieve these goals, a comparative historical research method was used to determine the features of the origin and composition of various types of offensive and defensive weapons, reflecting the stages of development of blacksmithing and weapons production in a historical context. The transformation of the Chthonic «fire» god into the patron saint of iron and blacksmithing of the nart Tlepsha translates in the legends of the Nart epic the historical and economic prerequisites for the origin of metalworking in the Early Iron Age, the creation of the first tools and weapons of the sleds, which became models for creating the best defensive and offensive weapons in Eurasia. The archaeological sites of the Northwestern Caucasus confirm the continuous development of metallurgy and metalworking since ancient times and the creation of highly artistic bronze, gold, and silver products. The initiated research on this topic has a long–term perspective and requires continued work on the study of the original texts of the Adyghe heroic epic «Narts» for comparison with archaeological artifacts found in the Northwestern Caucasus.

Characterization of the structural features of Ti-6Al-4V hollow-strut lattices fabricated by laser powder bed fusion

Hollow-strut metal lattices are novel cellular materials. Compared to their solid-strut counterparts, their powder bed fusion additive manufacturing (PBF-AM) features remain largely uninvestigated. This work focuses on characterizing the hollow-strut internal channel and nodal profiles, the defects and microstructures of the hollow-strut thin walls, and the inner surface conditions of the LPBF-manufactured body-centred cubic (BCC) Ti-6Al-4V hollow-strut lattices with different relative densities. BCC lattices are selected because of the low inclination angle (35.26°) of their constituent struts. These low-inclination hollow struts are designed using a recent model developed for PBF of inclined solid struts, together with considerations to prevent powder occlusion and ensure easy removal of powder particles. Detailed characterization indicates that our design considerations resulted in high-quality hollow-strut BCC Ti-6Al-4V lattices, which provide useful design insights for PBF-AM of hollow-strut metal lattices. In terms of microstructure, the Ti-6Al-4V hollow-strut thin walls (≤ 0.5 mm thick) exhibited different microstructures compared with Ti-6Al-4V solid struts, due to the heat accumulation effect in the inner channels. The implications are discussed for in-situ microstructure control.

Simulation Model of a Steelmaking-Continuous Casting Process Based on Dynamic-Operation Rules.

The steelmaking-continuous casting process (SCCP) is a complex manufacturing process which exhibits the distinct features of process manufacturing. The SCCP involves a variety of production elements, such as multiple process routes, a wide array of smelting and auxiliary devices, and a variety of raw and auxiliary materials. The production-simulation of SCCP holds a natural advantage in being able to accurately depict the intricate production behavior involved, and this serves as a crucial tool for optimizing the production operation of the SCCP. This paper thoroughly considers the various production elements involved in the SCCP, such as the fluctuation of the converter smelting cycle, fluctuation of heat weight, and ladle operation. Based on the Plant Simulation software platform, a dynamic simulation model of the SCCP is established and detailed descriptions are provided regarding the design of an SCCP using dynamic-operation rules. Additionally, a dynamic operational control program for the SCCP is developed using the SimTalk language, one which ensures the continuous operation of the caster in the SCCP, using the discrete simulation platform. The effectiveness of the proposed dynamic simulation model is verified by the total completion time of the production plan, the transfer time of the heat among the different processes, and the frequency of ladle turnover. The simulation's results indicate that the dynamic simulation model has a satisfactory effect in simulating the actual production process. On this basis, the application effects of different schedules are compared and analyzed. Compared with a heuristic schedule, the optimized schedule based on the "furnace-machine coordinating" mode reduces the weighted value of total completion time by 8.7 min, reduces the weighted value of transfer waiting time by 45.5 min, and the number of rescheduling times is also reduced, demonstrating a better application effect and verifying the optimizing effect of the "furnace-machine coordinating" mode on the schedule.

FEATURES OF MANUFACTURING AND CALCULATION OF GEARS FOR NEW APPLICATIONS (REVIEW)

FEATURES OF MANUFACTURING AND CALCULATION OF GEARS FOR NEW APPLICATIONS (REVIEW)

Assessing and controlling microstructure heterogeneity in fusion-based additive manufacturing

Abstract One of the de*ining features of fusion-based additive manufacturing (AM) is the localized melting of metal by a high-energy source, which fuses the material together point by point and layer by layer into a 3D object. The rapid solidi*ication velocity, directional thermal gradients, and site-speci*ic thermal build-ups produced by this process yield parts with complex and heterogeneous microstructure. This heterogeneity is a double-edged sword. On the one hand, it leads to large property scatter and casts uncertainty over parts performance, hindering the adoption of additive technologies by the industry. On the other hand, it may impart exceptional mechanical properties and new functionalities, which are not found in conventionally produced materials. In this paper, we present two ongoing research endeavours aimed at mitigating the detrimental effects of microstructure heterogeneity in AM, and at capitalizing on the opportunities it offers in the design of novel metal alloys, respectively. The *irst consists of developing a high-throughput characterization technique to enable large-scale microstructure analysis of AM builds. The second consists of a new strategy to control the material’s microstructure site-speci*ically during laser powder bed fusion.

Exploratory Studies of Mechanical Properties, Residual Stress, and Grain Evolution at the Local Regions near Pores in Additively Manufactured Metals.

Directed energy deposition (DED) is gaining widespread acceptance in various industrial applications since its unique manufacturing features allow the DED to print metallic parts with very complex geometries. However, DED inevitably generates a lot of internal pores which can limit the widespread applications of the DED technique. The current studies on DED porosity are mostly focused on analyzing pores' bulk-scale influences on mechanical properties and performances. Since DED pores have a micro-scale existence, with dimensions ranging from a few microns to several hundred microns, it is fundamental to explore the pores' influences on the micro-scale, including local mechanical properties, residual stress, and grains near pores. However, this important research direction has been neglected. The objective of this work is to fill the above gap in DED porosity research and acquire a fundamental understanding of the role of porosity on a microscopic scale. The authors used nanoindentation approaches to investigate internal pores' effects on mechanical properties and residual stress in local regions surrounding the pores. In addition, the grains near pores were observed through EBSD, and simulated with the Kinetic Monte Carlo model. The research findings can be provided for DED researchers and industrial practitioners as technical guidance. Most importantly, the research results can work as a good reference for tracing the source of bulk-scale mechanical performances and properties of DED parts with internal pores.

A heart-shaped bone artifact from Körtiktepe

Along with the emergence of sedentary life, the Pre-Pottery Neolithic (PPN) settlements brought revolutionary changes in production of material cultures as well as cultic and ritual activities, which are often argued to be associated with new waves of interactions between humans and their natural world. Körtiktepe of southeastern Turkey yielded by far the richest PPN assemblage in the world, standing among the very few earliest cultural and production centers which acted to be the predecessors of the development and spread of the Neolithic in West Asia. In this paper, we report a heart-shaped bone artifact which is one of the rarest finds in the extremely large cultural assemblage of Körtiktepe. The manufacture features indicate that the “heart-like” shape of this unique artifact was the product of intentional human activity. Overall archaeological context indicates its probable use as a bone pendant or amulet for the dead; providing the fact of its association with three early PPNA burials, many other ritual objects, and a large number of grave goods. Although difficult to argue for its association with the sense for “emotion”, “affection” or “love” in the present world, it is still significant that the unique specimen traces the symbolic presence and ritual use of the shape of a “heart” in West Asian prehistoric context back to the Early Pre-Pottery Neolithic of around 10000 cal BC.

FORMATION OF CONSUMER PROPERTIES OF ELASTIC LEATHER MATERIALS

For the effective use of leather material by the consumer, not only the physical and mechanical properties stipulated by the standard are taken into account, but also the hygienic and aesthetic ones, the role of which is determined by the technological features of manufacturing and operating conditions of the corresponding products. In this regard, there is a need for a comprehensive study of the consumer properties of leather materials, which determine their product quality and value for the consumer. The purpose of the study is to determine the technological features of the formation of consumer properties of elastic leather materials. At the same time, the following tasks were implemented: the filling and finish tanning of the leather semi-finished product of chrome tanning for the elastic material of the model and special purpose shoe upper; a coating is formed on the material for model shoes; consumer properties of leather material for model and special-purpose shoes are established. Research methods: consumer properties of leather materials were determined by a complex of physical-chemical, photographic and organoleptic methods. Research results. The influence of coating compositions based on polyurethane, polyacrylurethane and modified polyacrylate on the complex of physical-chemical and hygienic properties of leather material was investigated. It has been established that leathers with polyacrylic urethane finishing are characterized by high values of physical and mechanical and especially hygienic properties. Finishing of the frontside surface of the semi-finished product with the use of a polyacrylic urethane composition makes it possible to form a leather material of a wide range of colors with consumer properties that determine its intended use.

Identification of Barriers to Sustainable Manufacturing Implementation—The Perspective of Manufacturers of Parts and Components for Agricultural Transport

Sustainable manufacturing involves executing manufacturing processes in a way that follows the sustainable development principles, striving to combine economic, ecologic and social goals. The expected benefits of sustainable manufacturing are a lower cost and an improved environmental impact and well-being of employees. The main goal of the research was to identify barriers to the implementation of sustainable manufacturing principles. Achieving the main goal required the implementation of partial goals: (G1) designing the research tool based on the specific features of sustainable manufacturing identified based on the literature research; (G2) identifying of barriers that limit and/or prevent the implementation of sustainable manufacturing; and (G3) assessing the significance of individual factors limiting (preventing) implementation. The research was conducted in the agricultural transport sector and the subjects of the research were manufacturers of parts and subassemblies for agricultural transport. The ranking of limitations and barriers enables the definition of recommendations for companies willing to implement sustainable manufacturing concepts.

A Machine-Learning-Based Approach to Analyse the Feature Importance and Predict the Electrode Mass Loading of a Solid-State Battery

Solid-state batteries are currently developing into one of the most promising battery types for both the electrification of transport and for energy storage applications due to their high energy density and safe operating behaviour. The performance of solid-state batteries is largely determined by the manufacturing process, particularly in the production of electrodes. However, efficiently analysing the effects of key manufacturing features and predicting the mass loading of electrodes in the early stages of battery manufacturing remain a major challenge. In this study, a machine-learning-based approach is proposed to effectively analyse the importance of manufacturing features and accurately predict the mass loading of electrodes. Specifically, the importance of four key features during the manufacturing process of solid-state batteries is first quantified and analysed using a machine-learning-based method to analyse the importance of features. Then, four effective machine-learning-based regression methods, including decision tree, boosted decision tree, support vector regression and Gaussian process regression, are used to predict the mass loading of the electrodes in the mixing and coating stages. The comparative results show that the developed machine-learning-based approach is able to provide a satisfactory prediction of the electrode mass loading of a solid-state battery with 0.995 R2 while successfully quantifying the importance of four key features in the early manufacturing stages. Due to the advantages of its data-driven nature, the developed machine-learning-based approach can efficiently assist engineers in monitoring/predicting the electrode mass loading of solid-state batteries and analysing/quantifying the importance of manufacturing features of interest. This could benefit the production of solid-state batteries for further energy storage applications.

Optimal Design of Lower Limb Rehabilitation System Based on Parallel and Serial Mechanisms

This paper presents the structure and model of a hybrid modular structure of a robotic system for lower limb rehabilitation. It is made of two modules identical in structure, including an active 3-PRRR manipulator for moving the patient’s foot and a passive orthosis based on the RRR mechanism for supporting the lower limb. A mathematical model has been developed to describe the positions for the links of the active and passive mechanisms of two modules, as a function of the angles in the joints of the passive orthosis, considering constraints for attaching the active manipulators to the moving platform and their configurations. A method has been formulated for a parametric synthesis of the hybrid robotic system proposed with modular structure, taking into account the generated levels of parametric constraints depending on the ergonomic and manufacturability features. The proposed design is based on a criterion in the form of a convolution, including two components, one of which is based on minimizing unattainable points of the trajectory, considering the characteristics of anthropometric data, and the other is based on the compactness of the design. The results of the mathematical modeling are discussed as well as the analysis results towards a prototype validation.

Automated Design of Experiments supporting Feature-based Optimisation of Manufacturing Processes

This paper presents a novel process design to enhance time and cost-efficient AI training in manufacturing. As an alternative to time and resource expensive trial-and-error loops, the data basis of the proposed design enables data-driven parameter selection, where the parameter range in which the optimal solution is likely to reside, can be explored in a reproducible and systematical manner. A full-factorial DOE is generated and implemented from within the CAM software. Necessary production artefacts, like NC code, bill-of-material or work plan, are supplied per experiment. The heterogeneous data of different product life cycle phases are collected and related to the according manufacturing feature (i.e., drilling, face-milling, etc.). From within the CAM software, the NC-Code is manipulated to enable the identification of features during production, using feature markers. Instantiated as Siemens NX CAM extension, the novel design was tested on a 5-axis milling and drilling process on aluminium parts. The automated data set generation with feature correlation between different live-cycle phases was verified. As a result, the design supports feature optimization strategies for decision support systems - either as input for CAD/CAM, PLM, ERP and MES.

Research on CNC programming and machining process based on CAD/CAM technology

Abstract Focusing on CNC process data, this paper provides an in-depth analysis, characterization and mining of macro machining processes by associating CAD and CAM models. The article introduces a Bayesian inference method to construct an association relationship between the manufacturing features of the query part and the macroscopic process of the manufactured part, which avoids the need for a direct similarity comparison between the geometry of the query part and the part to be manufactured. In addition, the study calculated the overall similarity between the query part and the CNC programming process data instances through the guidance of the process skeleton, thus realizing the precise evaluation from the CNC programming perspective. The algorithm for generating tool trajectories in multi-axis CNC programming is analyzed. By selecting representative surfaces and performing tool processing calculations, this study explores the process planning and tool parameter selection of usual parts of surfaces in multi-axis CNC programming machining. It optimizes the nonlinear error in tool trajectory processing by combining CAD/CAM technology. The results show that the optimized process proposed in this paper significantly improves the machining efficiency by 36.94%. In the cutting at tool corners, the maximum cutting force generated by the optimized machining process is only 190.3N, which is only 67.2% of the leading cutting force of the Cimatron process. In addition, when the engagement frequency is 780 Hz, the optimized process proposed in this paper has the smallest vibration amplitude, which is only 21.4% of the Cimatron strategy. Therefore, this study significantly improves the machining efficiency while ensuring the machining quality, which has important practical application value.

A new adsorptive 3D–printed sampling device for simultaneous determination of 63 urinary organic acids by LC–MS/MS

BackgroundThe detection and quantification of urinary metabolites play an important role in disease diagnosis. In most cases, urinary analyses are done with liquid urine samples, which must be quickly transported to the laboratory to avoid metabolites degradation that is associated with temperature fluctuations. Consequently, dried sampling devices have emerged to minimize analyte degradation. However, most commercial dried sampling devices are expensive, aggregate low volumes, and need better analytical sensitivity. Therefore, a new dry urine sampling device that is inexpensive, suitable for domestic sampling operation, and efficient for quantifying metabolites without requiring high–resolution instruments is proposed in the present study. ResultsThe newly designed dry urine sampling device was produced by 3D printing that efficiently determines 63 urinary organic acids using liquid chromatography coupled with mass spectrometry (LC–MS/MS). The system's efficiency was demonstrated with analytical figures of merit, such as precision, accuracy, and stability of analytes after the sampling and storing of ordinary urine samples. The limits of quantification ranged from 0.01 to 0.42 ng mL–1. Precision and accuracy tests showed relative standard deviations of less than 15 %. The urine stability in the sampling device was high within seven days without any significant degradation of the metabolites. The method was applied to the analysis of 10 human urine samples and compared to a conventional method without the use of the sampling device. The results showed no statistically significant differences, demonstrating the method's efficiency. SignificanceThe proposed 3–D printing device was developed with fast, low–cost manufacturing features and can be manufactured with different volumetric capacities, adaptable to the needs of each user. Furthermore, it is innovative because this is the first sampling device that is effective for the simultaneous storage and preservation of several important urinary metabolites. Thus, it is anticipated that its application would contribute significantly to the identification of metabolic disorders.

Development of a deviation package method for low-cost robust optimization in compressor blade design

Manufacture variations can greatly increase the performance variability of compressor blades. Current robust design optimization methods have a critical role in reducing the adverse impact of the variations, but can be affected by errors if the assumptions of the deviation models and distribution parameters are inaccurate. A new approach for robust design optimization without the employment of the deviation models is proposed. The deviation package method and the interval estimation method are exploited in this new approach. Simultaneously, a stratified strategy is used to reduce the computational cost and assure the optimization accuracy. The test case employed for this study is a typical transonic compressor blade profile, which resembles most of the manufacture features of modern compressor blades. A set of 96 newly manufactured blades was measured using a coordinate measurement machine to obtain the manufacture variations and produce a deviation package. The optimization results show that the scatter of the aerodynamic performance for the optimal robust design is 20% less than the baseline value. By comparing the optimization results obtained from the deviation package method with those obtained from widely-used methods employing the deviation model, the efficiency and accuracy of the deviation package method are demonstrated. Finally, the physical mechanisms that control the robustness of different designs were further investigated, and some statistical laws of robust design were extracted.

Composite Forming Technology for Braiding Grid-Enhanced Structures and Design of a New Weaving Mechanism

Three-dimensional weaving structures have high strength and resistance to interlayer shear due to their integrated manufacturing features. The traditional weaving equipment is generally huge and is not effective for weaving small-sized products. Therefore, this paper proposes a new composite forming technology and weaving mechanism based on grid-enhanced structures to braid small-sized preforms, combining the continuous fiber printing technology, the rope drive technology and the 3D weaving technology. This paper adopted the screw theory for forward and inverse kinematic analysis of the weaving mechanism and applied software Adams2020 for trajectory simulation analysis. The theoretical calculation results were basically consistent with the simulation results, which verified the rationality and feasibility of the designed weaving mechanism in small, enhanced grids.

Spirulina and its residual biomass as alternative sustainable ingredients: impact on the rheological and nutritional features of wheat bread manufacture

Introduction: Following consumers’ demand for healthier alternatives, Spirulina biomass has been included as a functional ingredient in different types of food as a sustainable alternative to improve physicochemical characteristics and nutritional aspects in the diet. This study aimed to explore the use of Spirulina biomass (SB) and residual biomass (RB) obtained after C-phycocyanin (C-PC) extraction in the production of wheat bread (WB).Methods: The dough rheology, texture, color, nutritional aspects, and bioaccessibility of the different manufactured bread samples were accessed to achieve this goal.Results and Discussion: This is the first research to exploit RB. It was possible to replace 3% of wheat flour for SB or RB in bread-making; this substitution did not impact the rheological characteristics of the dough, even though the pH increased with the addition of SB or RB (5.63 and 5.70, respectively). SB and RB addition improved bread volume and enhanced the nutritional profile, increasing the antioxidant capacity (DPPH and FRAP) compared to WB. Heavy metals (Ni, Cd, and Pb) were not found in any of the samples (<0.2 mg/100 g). The in vitro protein digestibility in bread was better than in SB and RB raw materials, which indicates that bread manufacturing may contribute to improving protein digestibility. In addition, SB needs greater appreciation for sustainable food practices worldwide and in Brazilian exploration, requiring management strategies with industry and society working together. Further studies are necessary, focusing on acceptability to understand the viability of these ingredients to target consumers’ preferences.

Surface Characterisation and Comparison of Polymeric Additive Manufacturing Features for an XCT Test Object

Additive manufacturing (AM) has experimented a huge development in recent years, improving the physical properties of parts produced by these technologies to the level of being capable of fabricating end-use functional products. High performance metals are widely used and studied; however, the reduction in material costs of polymers and their acceptable properties makes them suitable for common AM purposes. The intrinsic surface roughness of AM, as a consequence of the layer-by-layer technology, remains a challenge and its characterisation is necessary for quality control. X-Ray computed tomography (XCT), as a newly adapted evaluation technology for industrial applications, sets an opportunity for the dimensional measurement of AM parts, due to its capability of characterising the complex geometries that is possible to create with this manufacturing technologies. In this paper, a first approach to a surface characterisation of polymeric AM parts is presented. Several individual objects have been designed and manufactured using various polymeric AM technologies with different manufacturing principles (FDM, Polyjet, SLS) to build ramps with a range of surface roughness created by two main parameters (angle of inclination and layer thickness). Measurements have been carried out by an optical device (focal variation microscope, FVM), and a comparison with theoretical roughness values calculated following predictive models has been made, with the objective of analysing the behaviour of each surface. Results show that the influence of the angle of inclination is higher than the influence of layer thickness; post-processing, also, affects to the trueness of the real roughness comparing to the predicted one obtaining more unpredictable results.