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J. Manuf. Mater. Process., Volume 4, Issue 3 (September 2020) – 34 articles

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Open AccessArticle
An Agent-Based System for Automated Configuration and Coordination of Robotic Operations in Real Time—A Case Study on a Car Floor Welding Process
J. Manuf. Mater. Process. 2020, 4(3), 95; https://doi.org/10.3390/jmmp4030095 - 18 Sep 2020
Abstract
This paper investigates the feasibility of using an agent-based framework to configure, control and coordinate dynamic, real-time robotic operations with the use of ontology manufacturing principles. Production automation agents use ontology models that represent the knowledge in a manufacturing environment for control and [...] Read more.
This paper investigates the feasibility of using an agent-based framework to configure, control and coordinate dynamic, real-time robotic operations with the use of ontology manufacturing principles. Production automation agents use ontology models that represent the knowledge in a manufacturing environment for control and configuration purposes. The ontological representation of the production environment is discussed. Using this framework, the manufacturing resources are capable of autonomously embedding themselves into the existing manufacturing enterprise with minimal human intervention, while, at the same time, the coordination of manufacturing operations is achieved without extensive human involvement. The specific framework was implemented, tested and validated in a feasibility study upon a laboratory robotic assembly cell with typical industrial components, using real data derived from a car-floor welding process. Full article
(This article belongs to the Special Issue Cyber Physical Production Systems)
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Open AccessArticle
Simulation-Based Multi-Criteria Optimization of Parallel Heat Treatment Furnaces at a Casting Manufacturer
J. Manuf. Mater. Process. 2020, 4(3), 94; https://doi.org/10.3390/jmmp4030094 - 17 Sep 2020
Abstract
This paper presents the development and evaluation of a digital method for multi-criteria optimized production planning and control of production equipment in a case-study of an Austrian metal casting manufacturer. Increased energy efficiency is a major requirement for production enterprises, especially for energy [...] Read more.
This paper presents the development and evaluation of a digital method for multi-criteria optimized production planning and control of production equipment in a case-study of an Austrian metal casting manufacturer. Increased energy efficiency is a major requirement for production enterprises, especially for energy intensive production sectors such as casting. Despite the significant energy-efficiency potential through optimized planning and the acknowledged application potential for sophisticated simulation-based methods, digital tools for practical planning applications are still lacking. The authors develop a planning method featuring a hybrid (discrete-continuous) simulation-based multi-criteria optimization (a multi-stage hybrid heuristic and metaheuristic method) for a metal casting manufacturer and apply it to a heat treatment process, that requires order batching and sequencing/scheduling on parallel machines, considering complex restrictions. The results show a ~10% global goal optimization potential, including traditional business goals and energy efficiency, with a ~6% energy optimization. A basic feasibility demonstration of applying the method to synchronize energy demand with fluctuating supply by considering flexible energy prices is conducted. The method is designed to be included in the planning loop of metal casting companies: receiving orders, machine availability, temperature data and (optional) current energy market price-data as input and returning an optimized plan to the production-IT systems for implementation. Full article
(This article belongs to the Special Issue Cyber Physical Production Systems)
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Open AccessArticle
Vacuum Hot Pressing of Oxide Dispersion Strengthened Ferritic Stainless Steels: Effect of Al Addition on the Microstructure and Properties
J. Manuf. Mater. Process. 2020, 4(3), 93; https://doi.org/10.3390/jmmp4030093 - 14 Sep 2020
Viewed by 107
Abstract
The present article investigates the fabrication of oxide dispersion strengthened (ODS) ferritic stainless steel (FSS). Three different ODS alloys with three different Al contents were fabricated, where the presence of Al-based oxides play a crucial role in determining the size of the oxide [...] Read more.
The present article investigates the fabrication of oxide dispersion strengthened (ODS) ferritic stainless steel (FSS). Three different ODS alloys with three different Al contents were fabricated, where the presence of Al-based oxides play a crucial role in determining the size of the oxide particles. Due to Ostwald ripening, the samples with Al show coarser oxide particles compared to the alloy without Al, which hampers the density of the fabricated samples and, hence, have reduced hardness levels. The present results suggest that the composition of the oxide present in ODS plays a crucial role in determining the properties of these samples. Full article
(This article belongs to the Special Issue Powder Metallurgy and Additive Manufacturing/3D Printing of Materials)
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Open AccessArticle
Combining Simulation and Machine Learning as Digital Twin for the Manufacturing of Overmolded Thermoplastic Composites
J. Manuf. Mater. Process. 2020, 4(3), 92; https://doi.org/10.3390/jmmp4030092 - 11 Sep 2020
Viewed by 195
Abstract
The design and development of composite structures requires precise and robust manufacturing processes. Composite materials such as fiber reinforced thermoplastics (FRTP) provide a good balance between manufacturing time, mechanical performance and weight. In this contribution, we investigate the process combination of thermoforming FRTP [...] Read more.
The design and development of composite structures requires precise and robust manufacturing processes. Composite materials such as fiber reinforced thermoplastics (FRTP) provide a good balance between manufacturing time, mechanical performance and weight. In this contribution, we investigate the process combination of thermoforming FRTP sheets (organo sheets) and injection overmolding of short FRTP for automotive structures. The limiting factor in those structures is the bond strength between the organo sheet and the overmolded thermoplastic. Within this process chain, even small deviations of the process settings (e.g., temperature) can lead to significant defects in the structure. A cyber physical production system based framework for a digital twin combining simulation and machine learning is presented. Based on parametric Finite-Element-Method (FEM) studies, training data for machine learning methods are generated and a FEM surrogate is developed. A comparison of different data-driven methods yields information on the estimation accuracy of task-specific data-driven methods. Finally, in accordance with experimental cross tension tests, the investigated FEM surrogate model is able to predict the interface bond strength quality in dependence of the process settings. The visualization into different quality domains qualifies the presented approach as decision support. Full article
(This article belongs to the Special Issue Cyber Physical Production Systems)
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Open AccessArticle
The Dimensional Accuracy of Thin-Walled Parts Manufactured by Laser-Powder Bed Fusion Process
J. Manuf. Mater. Process. 2020, 4(3), 91; https://doi.org/10.3390/jmmp4030091 - 11 Sep 2020
Viewed by 140
Abstract
Laser-Powder Bed Fusion brings new possibilities for the design of parts, e.g., cutter shafts with integrated cooling channels close to the contour. However, there are new challenges to dimensional accuracy in the production of thin-walled components, e.g., heat exchangers. High degrees of dimensional [...] Read more.
Laser-Powder Bed Fusion brings new possibilities for the design of parts, e.g., cutter shafts with integrated cooling channels close to the contour. However, there are new challenges to dimensional accuracy in the production of thin-walled components, e.g., heat exchangers. High degrees of dimensional accuracy are necessary for the production of functional components. The aim is to already achieve these during the process, to reduce post-processing costs and time. In this work, thin-walled ring specimens of H13 tool steel are produced and used for the analysis of dimensional accuracy and residual stresses. Two different scanning strategies were evaluated. One is a stripe scan strategy, which was automatically generated and provided by the machine manufacturer, and a (manually designed) sectional scan strategy. The ring segment strategy is designed by manually segmenting the geometry, which results in a longer preparation time. The samples were printed in different diameters and analyzed with respect to the degree of accuracy and residual stresses. The dimensional accuracy of ring specimens could be improved by up to 81% with the introduced sectional strategy compared to the standard approach. Full article
(This article belongs to the Special Issue Powder Metallurgy and Additive Manufacturing/3D Printing of Materials)
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Open AccessArticle
Macroanalysis of Hand Scraping
J. Manuf. Mater. Process. 2020, 4(3), 90; https://doi.org/10.3390/jmmp4030090 - 11 Sep 2020
Viewed by 141
Abstract
Hand scraping is a manual metalworking method that is still used in many industries to obtain good planarity, low friction and good gliding properties of metal and plastic surfaces. However, it is characterized by low productivity and requires skilled and well-trained workers. This [...] Read more.
Hand scraping is a manual metalworking method that is still used in many industries to obtain good planarity, low friction and good gliding properties of metal and plastic surfaces. However, it is characterized by low productivity and requires skilled and well-trained workers. This macroanalysis focuses on the strategy and procedure of the workers during the scraping operation. Forces and tool positions were acquired simultaneously and the resulting surfaces were measured after each scraping pass. Results show that in most instances differences between individual workers’ scraping styles are more significant than between consecutive scraping passes. This research was conducted in order to gather sufficient insight into the hand scraping method to take steps towards its automation. Full article
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Open AccessFeature PaperArticle
Simulation of Smart Factory Processes Applying Multi-Agent-Systems—A Knowledge Management Perspective
J. Manuf. Mater. Process. 2020, 4(3), 89; https://doi.org/10.3390/jmmp4030089 - 09 Sep 2020
Viewed by 190
Abstract
The implementation of Industry 4.0 and smart factory concepts changes the ways of manufacturing and production and requires the combination and interaction of different technologies and systems. The need for rapid implementation is steadily increasing as customers demand individualized products which are only [...] Read more.
The implementation of Industry 4.0 and smart factory concepts changes the ways of manufacturing and production and requires the combination and interaction of different technologies and systems. The need for rapid implementation is steadily increasing as customers demand individualized products which are only possible if the production unit is smart and flexible. However, an existing factory cannot be transformed easily into a smart factory, especially not during operational mode. Therefore, designers and engineers require solutions which help to simulate the aspired change beforehand, thus running realistic pre-tests without disturbing operations and production. New product lines may also be tested beforehand. Data and the deduced knowledge are key factors of the said transformation. One idea for simulation is applying artificial intelligence, in this case the method of multi-agent-systems (MAS), to simulate the inter-dependencies of different production units based on individually configured orders. Once the smart factory is running additional machine learning methods for feedback data of the different machine units may be applied for generating knowledge for improvement of processes and decision making. This paper describes the necessary interaction of manufacturing and knowledge-based solutions before showing an MAS use case implementation of a production line using Anylogic. Full article
(This article belongs to the Special Issue Cyber Physical Production Systems)
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Open AccessArticle
Pattern Recognition in Multivariate Time Series: Towards an Automated Event Detection Method for Smart Manufacturing Systems
J. Manuf. Mater. Process. 2020, 4(3), 88; https://doi.org/10.3390/jmmp4030088 - 05 Sep 2020
Viewed by 341
Abstract
This paper presents a framework to utilize multivariate time series data to automatically identify reoccurring events, e.g., resembling failure patterns in real-world manufacturing data by combining selected data mining techniques. The use case revolves around the auxiliary polymer manufacturing process of drying and [...] Read more.
This paper presents a framework to utilize multivariate time series data to automatically identify reoccurring events, e.g., resembling failure patterns in real-world manufacturing data by combining selected data mining techniques. The use case revolves around the auxiliary polymer manufacturing process of drying and feeding plastic granulate to extrusion or injection molding machines. The overall framework presented in this paper includes a comparison of two different approaches towards the identification of unique patterns in the real-world industrial data set. The first approach uses a subsequent heuristic segmentation and clustering approach, the second branch features a collaborative method with a built-in time dependency structure at its core (TICC). Both alternatives have been facilitated by a standard principle component analysis PCA (feature fusion) and a hyperparameter optimization (TPE) approach. The performance of the corresponding approaches was evaluated through established and commonly accepted metrics in the field of (unsupervised) machine learning. The results suggest the existence of several common failure sources (patterns) for the machine. Insights such as these automatically detected events can be harnessed to develop an advanced monitoring method to predict upcoming failures, ultimately reducing unplanned machine downtime in the future. Full article
(This article belongs to the Special Issue AI Applications in Smart and Advanced Manufacturing)
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Open AccessReview
A Review on Strain Gradient Plasticity Approaches in Simulation of Manufacturing Processes
J. Manuf. Mater. Process. 2020, 4(3), 87; https://doi.org/10.3390/jmmp4030087 - 03 Sep 2020
Viewed by 176
Abstract
Predicting the performances of a manufactured part is extremely important, especially for industries in which there is almost no room for uncertainties, such as aeronautical or automotive. Simulations performed by means of numerical methods such as Finite Element Methods represent a powerful instrument [...] Read more.
Predicting the performances of a manufactured part is extremely important, especially for industries in which there is almost no room for uncertainties, such as aeronautical or automotive. Simulations performed by means of numerical methods such as Finite Element Methods represent a powerful instrument in achieving high level of predictability. However, some particular combinations of manufactured materials and manufacturing processes might lead to unfavorable conditions in which the classical mathematical models used to predict the behavior of the continuum are not anymore able to deliver predictions that are in good agreement with experimental evidence. Since the first evidences of the shortcomings of the classical model were highlighted, many non-classical continuum mechanics theories have been developed, and most of them introduce dependencies at different levels with the Plastic Strain Gradient. This manuscript aims at gathering the milestone contributions among the Strain Gradient Plasticity Theories developed so far, with the object of exploring the way they interface with the requirements posed by the challenges in simulating manufacturing operations. Finally, the most relevant examples of the applications of Strain Gradient Plasticity Theories for manufacturing simulations have been reported from literature. Full article
(This article belongs to the Special Issue Optimization and Simulation of Solid State Manufacturing Processes)
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Open AccessArticle
Machine Tool Component Health Identification with Unsupervised Learning
J. Manuf. Mater. Process. 2020, 4(3), 86; https://doi.org/10.3390/jmmp4030086 - 02 Sep 2020
Viewed by 213
Abstract
Unforeseen machine tool component failures cause considerable losses. This study presents a new approach to unsupervised machine component condition identification. It uses test cycle data of machine components in healthy and various faulty conditions for modelling. The novelty in the approach consists of [...] Read more.
Unforeseen machine tool component failures cause considerable losses. This study presents a new approach to unsupervised machine component condition identification. It uses test cycle data of machine components in healthy and various faulty conditions for modelling. The novelty in the approach consists of the time series representation as features, the filtering of the features for statistical significance, and the use of this feature representation to train a clustering model. The benefit in the proposed approach is its small engineering effort, the potential for automation, the small amount of data necessary for training and updating the model, and the potential to distinguish between multiple known and unknown conditions. Online measurements on machines in unknown conditions are performed to predict the component condition with the aid of the trained model. The approach was exemplarily tested and verified on different healthy and faulty states of a grinding machine axis. For the accurate classification of the component condition, different clustering algorithms were evaluated and compared. The proposed solution demonstrated encouraging results as it accurately classified the component condition. It requires little data, is straightforward to implement and update, and is able to precisely differentiate minor differences of faults in test cycle time series. Full article
(This article belongs to the Special Issue AI Applications in Smart and Advanced Manufacturing)
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Open AccessArticle
Learning-Based Prediction of Pose-Dependent Dynamics
J. Manuf. Mater. Process. 2020, 4(3), 85; https://doi.org/10.3390/jmmp4030085 - 31 Aug 2020
Viewed by 257
Abstract
The constantly increasing demand for both, higher production output and more complex product geometries, which can only be achieved using five-axis milling processes, requires elaborated analysis approaches to optimize the regarded process. This is especially necessary when the used tool is susceptible to [...] Read more.
The constantly increasing demand for both, higher production output and more complex product geometries, which can only be achieved using five-axis milling processes, requires elaborated analysis approaches to optimize the regarded process. This is especially necessary when the used tool is susceptible to vibrations, which can deteriorate the quality of the machined workpiece surface. The prediction of tool vibrations based on the used NC path and process configuration can be achieved by, e.g., applying geometric physically-based process simulation systems prior to the machining process. However, recent research showed that the dynamic behavior of the system, consisting of the machine tool, the spindle, and the milling tool, can change significantly when using different inclination angles to realize certain machined workpiece shapes. Intermediate dynamic properties have to be interpolated based on measurements due to the impracticality of measuring the frequency response functions for each position and inclination angle that are used along the NC path. This paper presents a learning-based approach to predict the frequency response function for a given pose of the tool center point. Full article
(This article belongs to the Special Issue Machine Tool Dynamics)
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Open AccessArticle
Strategies for Increasing the Productivity of Pulsed Laser Cladding of Hot-Crack Susceptible Nickel-Base Superalloy Inconel 738 LC
J. Manuf. Mater. Process. 2020, 4(3), 84; https://doi.org/10.3390/jmmp4030084 - 29 Aug 2020
Viewed by 284
Abstract
A novel repair strategy based on decoupled heat source for increasing the productivity of wire-assisted pulsed laser cladding of the γ’-precipitation strengthening nickel-base superalloys Inconel 738 low carbon (IN 738 LC, base material) and Haynes 282 (HS 282, filler material) is presented. The [...] Read more.
A novel repair strategy based on decoupled heat source for increasing the productivity of wire-assisted pulsed laser cladding of the γ’-precipitation strengthening nickel-base superalloys Inconel 738 low carbon (IN 738 LC, base material) and Haynes 282 (HS 282, filler material) is presented. The laser beam welding process is supported by the hot-wire technology. The additional energy is utilized to increase the deposition rate of the filler material by increasing feeding rates and well-defining the thermal management in the welding zone. The simultaneous application of laser pulse modulation allows the precise control of the temperature gradients to minimize the hot-crack formation. Accompanying investigations such as high-speed recordings and numerical simulations allow a generalized statement on the influence of the adapted heat management on the resulting weld seam geometry (dilution, aspect ratio and wetting angle) as well as the formation of hot-cracks and lack of fusion between base and filler material. Statistical analysis of the data—the input parameters like laser pulse energy, pulse shape, hot-wire power and wire-feeding rate in conjunction with the objectives like dilution, aspect ratio, wetting angle and hot-cracking behavior—revealed regression functions to predict certain weld seam properties and hence the required input parameters. Full article
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Open AccessArticle
Relative Density of SLM-Produced Aluminum Alloy Parts: Interpretation of Results
J. Manuf. Mater. Process. 2020, 4(3), 83; https://doi.org/10.3390/jmmp4030083 - 24 Aug 2020
Viewed by 250
Abstract
Micrographic image analysis, tomography and the Archimedes method are commonly used to analyze the porosity of Selective Laser Melting (SLM)-produced parts and then to estimate the relative density. This article deals with the limitation of the relative density results to conclude on the [...] Read more.
Micrographic image analysis, tomography and the Archimedes method are commonly used to analyze the porosity of Selective Laser Melting (SLM)-produced parts and then to estimate the relative density. This article deals with the limitation of the relative density results to conclude on the quality of a part manufactured by additive manufacturing and focuses on the interpretation of the relative density result. To achieve this aim, two experimental methods are used: the image analysis method, which provides local information on the distribution of porosity, and the Archimedes method, which provides access to global information. To investigate this, two different grades of aluminum alloy, AlSi7Mg0.6 and AM205, were used in this study. The study concludes that an analysis of the metallographic images to calculate the relative density of the part depends on the areas chosen for the analysis. In addition, the results show that the Archimedes method has limitations, particularly related to the choice of reference materials for calculating relative density. It can be observed, for example, that, depending on the experimental conditions, the calculation can lead to relative densities higher than 100%, which is inconsistent. This article shows that it is essential that a result of relative density obtained from Archimedes measurements be supplemented by an indication of the reference density used. Full article
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Open AccessArticle
Partition of Primary Shear Plane Heat in Orthogonal Metal Cutting
J. Manuf. Mater. Process. 2020, 4(3), 82; https://doi.org/10.3390/jmmp4030082 - 13 Aug 2020
Viewed by 284
Abstract
When assessing the effect of metal cutting processes on the resulting surface layer, the heat generated in the chip formation zone that is transferred into the workpiece is of major concern. Models have been developed to estimate temperature distributions in machining processes. However, [...] Read more.
When assessing the effect of metal cutting processes on the resulting surface layer, the heat generated in the chip formation zone that is transferred into the workpiece is of major concern. Models have been developed to estimate temperature distributions in machining processes. However, most of them need information on the heat partition as input for the calculations. Based on analytical and numerical models, it is possible to determine the fraction of shear plane heat transferred into the workpiece for orthogonal cutting conditions. In the present work, these models were utilized to gain information on the significant influencing factors on heat partition, based on orthogonal cutting experiments, experimental results from the literature, and a purely model-based approach. It could be shown that the heat partition does not solely depend on the cutting velocity, the uncut chip thickness, and the thermal diffusivity—combined in the dimensionless thermal number—but the shear angle also has to be taken into account, as already proposed by some researchers. Furthermore, developed numerical models show that a more realistic representation of the process kinematics, e.g., regarding chip flow and temperature-dependent material properties, do not have a relevant impact on the heat partition. Nevertheless, the models still assume an idealized orthogonal cutting process and comparison to experimental-based findings on heat partition indicates a significant influence of the cutting edge radius and the friction on the flank face of the tool. Full article
(This article belongs to the Special Issue Advances in Modelling of Machining Operations)
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Open AccessArticle
Suppression of Polycrystalline Diamond Tool Wear with Mechanochemical Effects in Micromachining of Ferrous Metal
J. Manuf. Mater. Process. 2020, 4(3), 81; https://doi.org/10.3390/jmmp4030081 - 11 Aug 2020
Viewed by 305
Abstract
A mechanochemical effect is investigated to reduce diamond tool wear by means of applying a surfactant to low-carbon magnetic iron during diamond turning. Orthogonal microcutting demonstrates the manifestation of the mechanochemical effect through the reduction of cutting forces by 30%, which supports the [...] Read more.
A mechanochemical effect is investigated to reduce diamond tool wear by means of applying a surfactant to low-carbon magnetic iron during diamond turning. Orthogonal microcutting demonstrates the manifestation of the mechanochemical effect through the reduction of cutting forces by 30%, which supports the notion of lower cutting temperatures for reduced tribo-chemical wear. This is affirmed by the reduction in tool flank wear by up to 56% with the mechanochemical effect during diamond turning. While wear suppression increases by 9.4–16.15% with feeds from 5–20 μm/rev, it is not proportional to the reduction in cutting forces (31–39.8%), which suggests that the reduction in cutting energy does not directly correspond with the reduction in heat energy to sustain tribo-chemical tool wear. The strain localization during chip formation is proposed to serve as a heat source that hinders the wear mitigation efficiency. Finite element simulations demonstrate the heat generation during strain localization under the mechanochemical effect, which counteracts the reduced heat conversion from the plastic deformation and the transfer from tool–chip contact. Hence, this paper demonstrates the effectiveness of the mechanochemical method and its ability to reduce tool wear, but also establishes its limitations due to its inherent nature for heat generation. Full article
(This article belongs to the Special Issue Progress in Precision Machining)
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Open AccessArticle
Minimisation of Heating Time for Full Hardening in Hot Stamping Using Direct Resistance Heating
J. Manuf. Mater. Process. 2020, 4(3), 80; https://doi.org/10.3390/jmmp4030080 - 07 Aug 2020
Viewed by 360
Abstract
To obtain enough hardness of the die-quenched products after hot stamping using direct resistance heating, the effects of the electrifying condition and initial microstructure of the quenchable steel sheet on hardness were examined in a hot bending experiment. The steel sheet was heated [...] Read more.
To obtain enough hardness of the die-quenched products after hot stamping using direct resistance heating, the effects of the electrifying condition and initial microstructure of the quenchable steel sheet on hardness were examined in a hot bending experiment. The steel sheet was heated up to 900 °C in 3 to 10 s. The required heating time was shortened by normalising heat treatment due to the fine grain size of the sheet. The standard deviation of the hardness of the sheet heated to 900 °C in 3.2 s without temperature holding at the austenitising temperature was 12 HV, whereas the deviation reduced to 5 HV for temperature holding at the austenitising temperature of 3 s. Full article
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Open AccessArticle
Real-Time Laser Tracker Compensation of Robotic Drilling and Machining
J. Manuf. Mater. Process. 2020, 4(3), 79; https://doi.org/10.3390/jmmp4030079 - 06 Aug 2020
Viewed by 314
Abstract
Due to their flexibility, low cost and large working volume, 6-axis articulated industrial robots are increasingly being used for drilling, trimming and machining operations, especially in aerospace manufacturing. However, producing high quality components has demonstrated to be difficult, as a result of the [...] Read more.
Due to their flexibility, low cost and large working volume, 6-axis articulated industrial robots are increasingly being used for drilling, trimming and machining operations, especially in aerospace manufacturing. However, producing high quality components has demonstrated to be difficult, as a result of the inherent problems of robots, including low structural stiffness and low positional accuracy. These limit robotic machining to non-critical components and parts with low accuracy and surface finish requirements. Studies have been carried out to improve robotic machine capability, specifically positioning accuracy and vibration reduction. This study includes the description of the hardware, software and methodologies developed to compensate robot path errors in real time using a single three-degrees-of-freedom (DOF) laser tracker, as well as the experimental results with and without compensation. Performance tests conducted include ballbar dynamic path accuracy test, a series of drilling case studies and a machining test. The results demonstrate major improvements in path accuracy, hole position accuracy and hole quality, as well as increases in accuracy of a machined aluminum part. Full article
(This article belongs to the Special Issue Advanced Manufacturing and Machining Processes)
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Open AccessArticle
In-Process Monitoring of Changing Dynamics of a Thin-Walled Component During Milling Operation by Ball Shooter Excitation
J. Manuf. Mater. Process. 2020, 4(3), 78; https://doi.org/10.3390/jmmp4030078 - 03 Aug 2020
Viewed by 389
Abstract
During the milling of thin-walled workpieces, the natural frequencies might change radically due to the material removal. To avoid resonant spindle speeds and chatter vibration, a precise knowledge of the instantaneous modal parameters is necessary. Many different numerical methods exist to predict the [...] Read more.
During the milling of thin-walled workpieces, the natural frequencies might change radically due to the material removal. To avoid resonant spindle speeds and chatter vibration, a precise knowledge of the instantaneous modal parameters is necessary. Many different numerical methods exist to predict the changes; however, small unmodelled effects can lead to unreliable results. The natural frequencies could be measured by human experts based on modal analysis for an often interrupted process; however, this method is not acceptable during production. We propose an online measurement method with an automatic ball shooter device which can excite a wide frequency range of the flexible workpiece. The method is presented for the case of blade profile machining. The change of the natural frequencies is predicted based on analytical models and finite element simulations. The measurement response for the impulse excitation of the ball shooter device is compared to the results of impulse modal tests performed with a micro hammer. It is shown that the ball shooter is capable of determining even the slight variation of the natural frequencies during the machining process and of distinguishing the slight change caused by different clamping methods. An improved FE model is proposed to include the contact stiffness of the fixture. Full article
(This article belongs to the Special Issue Machine Tool Dynamics)
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Open AccessCommunication
Hemming with Pre-Bent Inner Sheet for Joining Ultra-High Strength Steel Sheets of Automobile Parts
J. Manuf. Mater. Process. 2020, 4(3), 77; https://doi.org/10.3390/jmmp4030077 - 25 Jul 2020
Viewed by 402
Abstract
In order to join two ultra-high strength steel sheets with low ductility for automobile parts, a joining process by hemming with a pre-bent inner sheet was developed. In this joining, the pre-bent inner sheet instead of the conventional flat inner sheet was used [...] Read more.
In order to join two ultra-high strength steel sheets with low ductility for automobile parts, a joining process by hemming with a pre-bent inner sheet was developed. In this joining, the pre-bent inner sheet instead of the conventional flat inner sheet was used to relax the deformation concentration of the outer sheet. Although 780 MPa steel sheets were joined without the pre-bent inner sheet, a fracture in the outer sheet occurred in joining the 980 MPa sheets due to the low ductility of the sheets. The 980 MPa and 1180 MPa sheets were successfully joined by hemming with the pre-bent inner sheet. In this process, the deformation of the upper sheet was relaxed by contacting with the inner sheet, and then the strain on the outer surface reduced. Although softening around a weld nugget occurred by heating in the conventional welded joint, work-hardening occurred in the hemmed joint. The joint strength was investigated and then the peel strength of the hemmed sheets was about a half of the welded one. It was found that the hemming process with the pre-bent inner sheet was effective for joining ultra-high strength steel sheets with low ductility. Full article
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Open AccessArticle
Investigation and Modeling of the Preheating Effects on Precipitation and Hot Flow Behavior for Forming High Strength AA7075 at Elevated Temperatures
J. Manuf. Mater. Process. 2020, 4(3), 76; https://doi.org/10.3390/jmmp4030076 - 23 Jul 2020
Viewed by 333
Abstract
Preheating is the first but critical step for hot stamping high strength precipitate hardened aluminum alloys. To thoroughly understand the effects of preheating conditions—i.e., preheating rate and heating temperature—on the strength and hot deformation of aluminum alloys, a series of thermal–mechanical tests was [...] Read more.
Preheating is the first but critical step for hot stamping high strength precipitate hardened aluminum alloys. To thoroughly understand the effects of preheating conditions—i.e., preheating rate and heating temperature—on the strength and hot deformation of aluminum alloys, a series of thermal–mechanical tests was performed to determine the post-hardness evolution and hot flow behaviors. Typical microstructures with different preheating conditions were also observed through transmission electron microscopy (TEM), with which a unified model of both hot flow and strength based on key microstructural variables was developed, enabling the successful prediction of macroscopic properties using different preheating strategies. The results have shown that for high strength AA7075 at the T6 condition, the dominant mechanism of precipitate evolution with increasing temperature is the coarsening of precipitates first, followed by dissolution when they exceed a critical temperature. A higher heating rate results in a slower coarsening and a relatively higher strength level. In addition, the flow stress of hot deformation is also higher using a quick heating rate, with more significant softening and reduced ductility. Full article
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Open AccessArticle
Predicting the Ultimate Tensile Strength of Friction Stir Welds Using Gaussian Process Regression
J. Manuf. Mater. Process. 2020, 4(3), 75; https://doi.org/10.3390/jmmp4030075 - 22 Jul 2020
Viewed by 284
Abstract
In the work described here, Gaussian process regression was applied to predict the ultimate tensile strength of friction stir welds through data evaluation and to therefore avoid destructive testing. For data generation, a total of 54 welding experiments were conducted in the butt [...] Read more.
In the work described here, Gaussian process regression was applied to predict the ultimate tensile strength of friction stir welds through data evaluation and to therefore avoid destructive testing. For data generation, a total of 54 welding experiments were conducted in the butt joint configuration using the aluminum alloy EN AW-6082-T6. Four tensile samples were taken from each of the 54 experiments and the resulting ultimate tensile strength of the weld seam segment was modeled as a function of the weld’s surface topography. Further models were created for comparison, which received either the process variables or the process parameters to predict the ultimate tensile strength. It was shown that the ultimate tensile strength can be accurately predicted based on the weld’s surface topography. Especially for low welding speeds, the correlation coefficients between the true and the predicted ultimate tensile strength were high. However, overall, even higher correlation coefficients could be achieved when providing the process variables or the process parameters to the model. In conclusion, it was shown that the developed Gaussian process regression model is a powerful approach for replacing destructive testing and for predicting ultimate tensile strength based solely on data that can be collected non-destructively. Full article
(This article belongs to the Special Issue AI Applications in Smart and Advanced Manufacturing)
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Open AccessArticle
Process Data-Based Knowledge Discovery in Additive Manufacturing of Ceramic Materials by Multi-Material Jetting (CerAM MMJ)
J. Manuf. Mater. Process. 2020, 4(3), 74; https://doi.org/10.3390/jmmp4030074 - 22 Jul 2020
Cited by 1 | Viewed by 374
Abstract
Multi-material jetting (CerAM MMJ, previously T3DP) enables the additive manufacturing of ceramics, metals, glass and hardmetals, demonstrating comparatively high solid contents of the processed materials. The material is applied drop by drop onto a substrate. The droplets can be adapted to the component [...] Read more.
Multi-material jetting (CerAM MMJ, previously T3DP) enables the additive manufacturing of ceramics, metals, glass and hardmetals, demonstrating comparatively high solid contents of the processed materials. The material is applied drop by drop onto a substrate. The droplets can be adapted to the component to be produced by a large degree of freedom in parameterization. Thus, large volumes can be processed quickly and fine structures can be displayed in detail, based on the droplet size. Data-driven methods are applied to build process knowledge and to contribute to the optimization of CerAM MMJ manufacturing processes. As a basis for the computational exploitation of mass sensor data from the technological process chain for manufacturing a component with CerAM MMJ, a data management plan was developed with the help of an engineering workflow. Focusing on the process step of green part production, droplet structures as intermediate products of 3D generation were described by means of droplet height, droplet circularity, the number of ambient satellite particles, as well as the associated standard deviations. First of all, the weighting of the factors influencing the droplet geometry was determined by means of single factor preliminary tests, in order to be able to reduce the number of factors to be considered in the detailed test series. The identification of key influences (falling time, needle lift, rising time, air supply pressure) permitted an optimization of the droplet geometry according to the introduced target characteristics by means of a design of experiments. Full article
(This article belongs to the Special Issue Additive Manufacturing and Device Applications)
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Open AccessArticle
Performance Characterization of Laser Powder Bed Fusion Fabricated Inconel 718 Treated with Experimental Hot Isostatic Processing Cycles
J. Manuf. Mater. Process. 2020, 4(3), 73; https://doi.org/10.3390/jmmp4030073 - 21 Jul 2020
Viewed by 600
Abstract
Inconel 718 alloy fabricated by selective laser melting (SLM) (or laser powder-bed fusion (LPBF)) has been post-process heat-treated by stress-relief anneal at 1065 °C; stress-relief anneal (1065 °C) + solution treatment (at 720 °C) + aging (at 620 °C); hot isostatic pressing (HIP) [...] Read more.
Inconel 718 alloy fabricated by selective laser melting (SLM) (or laser powder-bed fusion (LPBF)) has been post-process heat-treated by stress-relief anneal at 1065 °C; stress-relief anneal (1065 °C) + solution treatment (at 720 °C) + aging (at 620 °C); hot isostatic pressing (HIP) (at 1120–1200 °C); stress-relief anneal + HIP; and stress-relief anneal + HIP + solution treatment + aging. Microstructure analysis utilizing optical metallography revealed primarily equiaxed grain structures (having average diameters ranging from ~30 to 49 microns) containing annealing twins, and a high concentration of carbide precipitates in all HIP-related treatments in the grain boundaries and intragrain regions. However, no precipitates nucleated on the {111} coherent annealing twin boundaries because of their very low interfacial free energy in contrast to regular grain boundaries. The mechanical properties for the as-fabricated Inconel 718 exhibited a yield stress of 0.64 GPa, UTS of 0.98 GPa, and elongation of 26%. Following stress-relief anneal at 1065 °C, the yield stress dropped to 0.60 GPa, while the elongation increased to 43%. The associated grain structure was an irregular, somewhat elongated, recrystallized structure. This structure was preserved at a stress anneal at 1065 °C + solution treatment + aging, but grain boundary and intragrain precipitation resulted in a doubling of the yield stress to 1.3 GPa and a reduced elongation of 12.6%. The results of HIP-related post-process heat treatments involving temperatures above 1060 °C demonstrated that the yield stress and elongations could be varied from 1.07 to 1.17 GPa and 11.4% to 19%, respectively. Corresponding Rockwell C-scale hardness values also varied from 33 for the as-fabricated Inconel 718 to 53 for simple post-process HIP treatment at 1163 °C. Full article
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Open AccessArticle
The Basics of Time-Domain-Based Milling Stability Prediction Using Frequency Response Function
J. Manuf. Mater. Process. 2020, 4(3), 72; https://doi.org/10.3390/jmmp4030072 - 16 Jul 2020
Viewed by 375
Abstract
This study presents the fundamentals of the usage of frequency response functions (FRF) directly in time-domain-based methods. The methodology intends to combine the advantages of frequency- and time-domain-based techniques to determine the stability of stationary solutions of a given milling process. This is [...] Read more.
This study presents the fundamentals of the usage of frequency response functions (FRF) directly in time-domain-based methods. The methodology intends to combine the advantages of frequency- and time-domain-based techniques to determine the stability of stationary solutions of a given milling process. This is achieved by applying the so-called impulse dynamic subspace (IDS) method, with which the impulse response function (IRF) can be disassembled to separated singular IRFs that form the basis of the used transformation. Knowing the IDS state, the linear stability boundaries can be constructed and a measure of stability can be determined using the Floquet multipliers via the semidiscretization method (SDM). This step has a huge importance in parameter optimization where the multipliers can be used as objective functions, which is hardly achievable using frequency-domain-based methods. Here we present the basic idea of utilizing the IDS method and analyze its convergence properties. Full article
(This article belongs to the Special Issue Machine Tool Dynamics)
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Open AccessFeature PaperReview
Search for the Optimal Build Direction in Additive Manufacturing Technologies: A Review
J. Manuf. Mater. Process. 2020, 4(3), 71; https://doi.org/10.3390/jmmp4030071 - 14 Jul 2020
Viewed by 468
Abstract
By additive manufacturing technologies, an object is produced deposing material layer by layer. The piece grows along the build direction, which is one of the main manufacturing parameters of Additive Manufacturing (AM) technologies to be set-up. This process parameter affects the cost, quality, [...] Read more.
By additive manufacturing technologies, an object is produced deposing material layer by layer. The piece grows along the build direction, which is one of the main manufacturing parameters of Additive Manufacturing (AM) technologies to be set-up. This process parameter affects the cost, quality, and other important properties of the manufactured object. In this paper, the Objective Functions (OFs), presented in the literature for the search of the optimal build direction, are considered and reviewed. The following OFs are discussed: part quality, surface quality, support structure, build time, manufacturing cost, and mechanical properties. All of them are distinguished factors that are affected by build direction. In the first part of the paper, a collection of the most significant published methods for the estimation of the factors that most influence the build direction is presented. In the second part, a summary of the optimization techniques adopted from the reviewed papers is presented. Finally, the advantages and disadvantages are briefly discussed and some possible new fields of exploration are proposed. Full article
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Open AccessArticle
Electrohydrodynamic Atomization for Minimum Quantity Lubrication (EHDA-MQL) in End Milling Ti6Al4V Titanium Alloy
J. Manuf. Mater. Process. 2020, 4(3), 70; https://doi.org/10.3390/jmmp4030070 - 13 Jul 2020
Viewed by 503
Abstract
Titanium alloy Ti6Al4V is a difficult-to-machine material which is extensively used in the aerospace and medical industries. Machining titanium is associated with a short tool life and low productivity. In this paper, a new cooling-lubrication system based on electrohydrodynamic atomization was designed, manufactured [...] Read more.
Titanium alloy Ti6Al4V is a difficult-to-machine material which is extensively used in the aerospace and medical industries. Machining titanium is associated with a short tool life and low productivity. In this paper, a new cooling-lubrication system based on electrohydrodynamic atomization was designed, manufactured and tested and the relevant theory was developed. The major novelty of the system lies within the use of electrohydrodynamic atomization (EHDA) and a three-electrode setup for generating lubricant droplets. The system was tested and compared with that of flood, minimum quantity lubrication (MQL) and compressed air machining. The proposed system can extend the tool life by 6 and 22 times when compared with MQL and flood cooling, respectively. This is equivalent to more than 170 min tool life at 120 m/min cutting speed allowing for significant productivity gains in machining Ti6Al4V. Full article
(This article belongs to the Special Issue Advanced Manufacturing and Machining Processes)
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Open AccessArticle
Magnetic Pulse Welding and Spot Welding with Improved Coil Efficiency—Application for Dissimilar Welding of Automotive Metal Alloys
J. Manuf. Mater. Process. 2020, 4(3), 69; https://doi.org/10.3390/jmmp4030069 - 08 Jul 2020
Viewed by 386
Abstract
Lightweight structures in the automotive and transportation industry are increasingly researched. Multiple materials with tailored properties are integrated into structures via a large spectrum of joining techniques. Welding is a viable solution in mass scale production in an automotive sector still dominated by [...] Read more.
Lightweight structures in the automotive and transportation industry are increasingly researched. Multiple materials with tailored properties are integrated into structures via a large spectrum of joining techniques. Welding is a viable solution in mass scale production in an automotive sector still dominated by steels, although hybrid structures involving other materials like aluminum are becoming increasingly important. The welding of dissimilar metals is difficult if not impossible, due to their differential thermo mechanical properties along with the formation of intermetallic compounds, particularly when fusion welding is envisioned. Solid-state welding, as with magnetic pulse welding, is of particular interest due to its short processing cycles. However, electromagnetic pulse welding is constrained by the selection of processing parameters, particularly the coil design and its life cycle. This paper investigates two inductor designs, a linear (I) and O shape, for the joining of sheet metals involving aluminum and steels. The O shape inductor is found to be more efficient both with magnetic pulse (MPW) and magnetic pulse spot welding (MPSW) and offers a better life cycle. Both simulation and experimental mechanical tests are presented to support the effect of inductor design on the process performance. Full article
(This article belongs to the Special Issue Impulse-Based Manufacturing Technologies)
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Open AccessArticle
Localized Laser Dispersing of Titanium-Based Particles for Improving the Tribological Performance of Hot Stamping Tools
J. Manuf. Mater. Process. 2020, 4(3), 68; https://doi.org/10.3390/jmmp4030068 - 08 Jul 2020
Viewed by 514
Abstract
Within the scope of this work, a new surface engineering technology named laser implantation has been investigated, in order to improve the tribological performance of hot stamping tools. This technique is based on manufacturing highly wear-resistant, separated, and elevated microfeatures by embedding hard [...] Read more.
Within the scope of this work, a new surface engineering technology named laser implantation has been investigated, in order to improve the tribological performance of hot stamping tools. This technique is based on manufacturing highly wear-resistant, separated, and elevated microfeatures by embedding hard ceramic particles into the tool surface via pulsed laser radiation. Hence, the topography and material properties of the tool are modified, which influences the thermal and tribological interactions at the blank-die interface. To verify these assumptions and to clarify the cause–effect relations, different titanium-based particles (TiB2, TiC, TiN) were laser-implanted and subsequently analyzed regarding to their geometrical shape and mechanical properties. Afterwards, quenching tests as well as tribological experiments were carried out by using titanium-diboride as the most promising implantation material for reducing the tribological load due to high hardness value of the generated implants. Compared to conventional tooling systems, the modified tool surfaces revealed a significantly higher wear resistance as well as reduced friction forces while offering the possibility to adjust the thermal interactions at the blank-die interface. Based on these results, a tailored tool surface modification can be pursued in future research work, in order to enhance the effectiveness of the hot stamping technology. Full article
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Open AccessArticle
Disturbance of the Regenerative Effect by Use of Milling Tools Modified with Asymmetric Dynamic Properties
J. Manuf. Mater. Process. 2020, 4(3), 67; https://doi.org/10.3390/jmmp4030067 - 06 Jul 2020
Viewed by 644
Abstract
Milling processes are often limited by self-excited vibrations of the tool or workpiece, generated by the regenerative effect, especially when using long cantilevered tools or machining thin-walled workpieces. The regenerative effect arises from a periodic modulation of the uncut chip thickness within the [...] Read more.
Milling processes are often limited by self-excited vibrations of the tool or workpiece, generated by the regenerative effect, especially when using long cantilevered tools or machining thin-walled workpieces. The regenerative effect arises from a periodic modulation of the uncut chip thickness within the frequencies of the eigenmodes, which results in a critical excitation in the consecutive cuts or tooth engagements. This paper presents a new approach for disturbing the regenerative effect by using milling tools which are modified with asymmetric dynamic properties. A four-fluted milling tool was modified with parallel slots in the tool shank in order to establish asymmetric dynamic characteristics or different eigenfrequencies for consecutive tooth engagements, respectively. Measurements of the frequency response functions at the tool tip showed a decrease in the eigenfrequencies as well as an increase in the dynamic compliance in the direction of the grooves. Milling experiments with a constant width of cut and constantly increasing axial depth of cut indicated a significant increase in the stability limit for the specific preparations of up to 69%. Full article
(This article belongs to the Special Issue Advanced Manufacturing and Machining Processes)
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Open AccessArticle
The Optimization of Machining Parameters for Milling Operations by Using the Nelder–Mead Simplex Method
J. Manuf. Mater. Process. 2020, 4(3), 66; https://doi.org/10.3390/jmmp4030066 - 05 Jul 2020
Viewed by 452
Abstract
The purpose of machining operations is to make specific shapes or surface characteristics for a product. Conditions for machining operations were traditionally selected based on geometry and surface finish requirements. However, nowadays, many researchers are optimizing machining parameters since high-quality products can be [...] Read more.
The purpose of machining operations is to make specific shapes or surface characteristics for a product. Conditions for machining operations were traditionally selected based on geometry and surface finish requirements. However, nowadays, many researchers are optimizing machining parameters since high-quality products can be produced using more expensive and advanced machines and tools. There are a few methods to optimize the machining process, such as minimizing unit production time or cost or maximizing profit. This research focused on maximizing the profit of computer numerical control (CNC) milling operations by optimizing machining parameters. Cutting speeds and feed are considered as the main process variables to maximize the profit of CNC milling operations as they have the greatest effect on machining operation. In this research, the Nelder–Mead simplex method was used to maximize the profit of CNC milling processes by optimizing machining parameters. The Nelder–Mead simplex method was used to calculate best, worst, and second-worst value based on an initial guess. The possible range of machining parameters was limited by several constraints. The Nelder–Mead simplex method yielded a profit of 3.45 ($/min) when applied to a commonly used case study model. Full article
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