1,720,978 research outputs found
About Fluence and Process Parameters on Maraging Steel Processed by Selective Laser Melting: Do They Convey the Same Information?
Full text linkIn this paper the influence of process parameters and fluence on mechanical properties of maraging steel in Selective Laser Melting (SLM) is studied. The results of the present work show that there exists a steady region of process parameters where fluence conveys all the information required to describe and predict density and tensile properties. We also show that in this region of the parameters, the choice of process parameters can be carried out considering other optimality criteria such as productivity, rather than maximization of density. To pursue this objective, a V-Alphabetical optimal design with fixed fluence levels was specifically designed for the experimentation. The used fluence levels and the corresponding process parameter combinations were tested on an industrial SLM system. To compare the informative content of fluence and the process parameters, two regression equation were estimated from experimental results for part density and tensile properties. The comparison of the regression models showed that the predictive ability of fluence and process parameters in the steady region is the same, however fluence allowed to obtain a higher precision. In conclusion, based on the experimental conditions studied, new process parameters are suggested using a productivity-based criteria
Process optimization via confidence region: a case study from micro-injection molding
Full text linkIn industrial research, experiments are designed to determine the optimal factor levels of the process parameters. Typically, experimental data are used to fit empirical models (for example, regression models) to derive one set of optimal conditions that maximize (or minimize) the response. Unfortunately, the optimization rarely provides a Confidence Interval for the location of the optimal solution, even though the optimal solution itself is subjected to variability. From a practitioner's point of view, identifying a region of possible optimal values provides high operational flexibility to adjust process parameters online during production. This paper provides a procedure for computing a confidence region for the optimal point based on experimental data, bootstrapping, and data depth. The procedure is validated using a case study from micro-injection molding, where the part weight is maximized under a constraint of the probability of flash formation. The proposed method considers that the objective function (part weight) and the constraint (probability of flash formation) are estimated from experimental data and subjected to sampling variability
Parametric modeling of cradle-to-gate carbon emissions from gas-atomized AISI 316L powders under closed-loop feedstock strategies
No full textThis study introduces a parametric framework for the cradle-to-gate assessment of carbon emissions associated with the production of gas-atomized AISI 316L stainless steel powders intended for use in additive manufacturing and other powder metallurgy processes. The model provides a detailed representation of upstream material flows and includes all major unit operations involved in powder production, such as feedstock preparation, gas atomization, sieving and blending, and packing. By varying the composition of the feedstock charged into the atomizer crucible, the framework enables the estimation of carbon emissions across a wide range of scenarios reflecting alternative sourcing strategies. The case study on AISI 316L highlights the environmental benefits of integrating closed-loop material flows, including the recirculation of off-specification powders and the direct use of compatible metallic scrap. Furthermore, broadening the acceptable powder size range significantly improves atomization yield, thereby reducing the specific carbon intensity of usable powder output. Such an approach lays the foundation for the development of robust decision-support tools for process planning in gas atomization, with direct implications for industrial-scale powder production
Optimization of cutting conditions using an evolutive online procedure
Full text linkThis paper proposes an online evolutive procedure to optimize the Material Removal Rate in a turning process considering a stochastic constraint. The usual industrial approach in finishing operations is to change the tool insert at the end of each machining feature to avoid defective parts. Consequently, all parts are produced at highly conservative conditions (low levels of feed and speed), and therefore, at low productivity. In this work, a framework to estimate the stochastic constraint of tool wear during the production of a batch is proposed. A simulation campaign was carried out to evaluate the performances of the proposed procedure. The results showed that it was possible to improve the Material Removal Rate during the production of the batch and keeping the probability of defective parts under a desired level
A Novel Assessment of the Thermo-Mechanical Behavior of Chemically Bonded 3D-Printed Sand Cores
No full textThermal and mechanical stability of sand cores is crucial for the success of castings, as the cores must resist the thermo-mechanical load of molten metal until its solidification, while maintaining the required dimensional and geometrical accuracy. Although sand 3D printing with binder jetting technology is a highly effective method for manufacturing sand cores, there is still no clear understanding in the literature of how printing configurations affect the thermo-mechanical behavior of the cores. To this aim, this work investigates the printing homogeneity of an industrial binder jetting machine under different configurations (part orientation and position in the building box) using data obtained from hot distortion test (HDT). From HDT curves, important curve features were extracted and analyzed; some of them showed statistical correlations, indicating that a single feature is not sufficient for comparing HDT curves. The analysis revealed a sensible difference in the thermo-mechanical behavior of the 3D-printed cores with the printing directions. In particular, the cores printed along the build direction exhibited both a statistical reduction of the breakage time and an increase of maximum deflection. Conversely, the HDT response of the cores across the different locations inside the printer building box revealed a much less significant difference. This method supports the optimization of the 3D printing process design, toward the improvement of the printability of highly complex core geometries
An Economical Approach to Stop an Experimental Campaign with the Aim of Reducing Cost
Full text linkNowadays, in a period of stagnation and economic crisis, the continuous improvement of the production technologies in order to optimize economic, energetic and productive resources is crucial. The increase in efficiency, measured in terms of cost reduction, is therefore a key problem that requires the attention of more and more companies and researchers. In particular, the productivity of a machining system and its related costs depend on the setup of the machining parameters. This choice plays a key role when the machining material is expensive, the production batch has a limited size and the tool to be used is new: typical examples are the aircraft and die/mold industries.
In order to optimally setup a machine, the study of the tool life according to the material and the machining parameters is critical. The expression of the tool life could be estimated using an appropriate experimental campaign, which should have a limited size in order to reduce the experimental costs. This approach becomes of primary importance when the production is not in series where the costs can be spread over a large number of pieces.
The aim of this paper is to propose a new methodology that stops the experimental campaign as soon as the expected gain in carrying on the experimentation does not justify the marginal cost of experimentation.
To prove our idea, a simple problem from the well-known turning cutting condition optimization is used and the optimization technique Response Surface Methodology is selected
Densification mechanism for different types of stainless steel powders in Selective Laser Melting
Full text linkSelective laser melting is a powder based additive manufacturing process where the metallic powder particles are melted by a high power laser
beam. Different types of stainless steel powders made by gas and water atomization were analyzed before processing, in particular regarding their
particle size distributions and morphology. Particle analysis was carried out using laser diffraction technologies and digital image analysis.
A suitable designed experiment has been carried out and the specimen density has been measured and linked to the properties of the powders.
Eventually the possibility to reach high density specimen by adjusting process parameters is discussed
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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