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Keywords = hot stamping process chain

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27 pages, 9960 KiB  
Article
Energy-Oriented Modeling of Hot Stamping Production Line: Analysis and Perspectives for Reduction
by Qiong Liu, Quan Zuo, Lei Li, Chen Yang, Jianwen Yan and Yuhang Xu
Energies 2024, 17(22), 5798; https://doi.org/10.3390/en17225798 - 20 Nov 2024
Viewed by 1199
Abstract
This research aims to develop a comprehensive mathematical model to analyze the energy usage of essential equipment in the hot stamping production line (HSPL) and identify opportunities for improving energy efficiency. This involves refining existing models and parameters related to energy consumption in [...] Read more.
This research aims to develop a comprehensive mathematical model to analyze the energy usage of essential equipment in the hot stamping production line (HSPL) and identify opportunities for improving energy efficiency. This involves refining existing models and parameters related to energy consumption in hot stamping to ensure precise energy usage monitoring throughout the HSPL. The main focus is on accurately calculating and validating the energy consumption efficiency of equipment within a product’s production cycle on the roller hearth furnace’s HSPL. The model has proven to be highly accurate in predicting energy consumption for various equipment. The average energy consumption of the HSPL in the case study is calculated as 0.597 kwh/kg, and the actual measurement is 0.625 kwh/kg. However, it revealed significant deviation in the cooling system, primarily due to the incorrect water pump head parameters utilization. As per the model’s calculations, most energy consumption is attributed to the furnace (77.51%), followed by the press (10.92%), chillers (6.86%), cooling systems (2.76%), and robots (1.95%). Actual measurements and model calculations highlight mismatches between equipment power ratings and actual demand, resulting in average operating power significantly lower than the rated power. In line with efforts to promote low-carbon manufacturing, practical approaches are being explored to conserve energy and enhance overall process efficiency by refining process parameters, reducing quenching duration, improving SPM on the production line, and adjusting load matching. Full article
(This article belongs to the Section K: State-of-the-Art Energy Related Technologies)
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10 pages, 5415 KiB  
Proceeding Paper
Industry 4.0: Correlation Analysis Applied to the Hot Stamping of AA7075 B-Pillars Pre-Assembled Using Friction Stir Welding
by Mohamad Idriss, Guillaume D’Amours, François Nadeau, Danick Gallant and Ryan Myers
Eng. Proc. 2023, 43(1), 15; https://doi.org/10.3390/engproc2023043015 - 14 Sep 2023
Viewed by 945
Abstract
In this study, 220 AA7075-T6 B-pillars were fabricated using a thoroughly instrumented hot-stamping press under varied conditions. Feature engineering work identified nineteen attributes of the hot-stamping process as impacting four characteristics of the obtained B-pillars: electrical conductivity (%IACS), mechanical strength, distortion, and the [...] Read more.
In this study, 220 AA7075-T6 B-pillars were fabricated using a thoroughly instrumented hot-stamping press under varied conditions. Feature engineering work identified nineteen attributes of the hot-stamping process as impacting four characteristics of the obtained B-pillars: electrical conductivity (%IACS), mechanical strength, distortion, and the presence of visible defects. Pearson correlation suggests an important correlation between the heating phase and the mechanical strength, as well as the %IACS values. As for distortion, the influence of the stamping phase is more obvious. Finally, no correlation was obtained between the hot stamping attributes and the presence of visible cracks. This is mainly due to the pre-assembly phase, i.e., Friction Stir Welding, which will be considered in future works. Full article
(This article belongs to the Proceedings of The 15th International Aluminium Conference)
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24 pages, 7386 KiB  
Article
ANN-Based Inverse Goal-Oriented Design Method for Targeted Final Properties of Materials
by Waqas Ahmad, Guoxin Wang and Yan Yan
Appl. Sci. 2022, 12(7), 3420; https://doi.org/10.3390/app12073420 - 28 Mar 2022
Cited by 2 | Viewed by 2234
Abstract
Designing materials for targeted materials properties is the key to tackle the demands for personalized consumer products. The deficiency in the existing linear and nonlinear correlation methods attributed to simplifying assumptions and idealizations, nondeterministic simulations, and limited experimental data due to heavy computational [...] Read more.
Designing materials for targeted materials properties is the key to tackle the demands for personalized consumer products. The deficiency in the existing linear and nonlinear correlation methods attributed to simplifying assumptions and idealizations, nondeterministic simulations, and limited experimental data due to heavy computational time and cost, necessitates a design method that provides sufficient confidence to designers in decision making. To address this requirement, we propose, in this paper, an inverse goal-oriented materials design method supported by the design space exploration framework (DSEF). Keeping in view the accuracy and precision in the prediction confidence of machine learning-based methods, we developed an Artificial Neural Network based prediction model that supports DSEF. The proposed method for materials design can help designers to (1) explore PSPP spaces starting from end property requirements, (2) adjust the errors being propagated in the PSPP chain as well as in the predictions made by the model, and (3) timely adjust model parameters of the prediction model for accurate predictions. The efficacy of the method is illustrated for the hot stamping process to produce structural components from ultrahigh-strength steels (UHSS). The proposed method and prediction model are generic and applicable to any sequential manufacturing process to realize an end product. Full article
(This article belongs to the Special Issue Smart Resilient Manufacturing)
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15 pages, 6571 KiB  
Article
Characterisation and Comparison of Process Chains for Producing Automotive Structural Parts from 7xxx Aluminium Sheets
by Philipp A. Schuster, Johannes A. Österreicher, Georg Kirov, Christof Sommitsch, Olaf Kessler and Ermal Mukeli
Metals 2019, 9(3), 305; https://doi.org/10.3390/met9030305 - 7 Mar 2019
Cited by 31 | Viewed by 6273
Abstract
Due to their high specific strength, EN AW-7xxx aluminium alloys are promising materials for reducing the weight of automotive structural parts. However, their formability at room temperature is poor due to pronounced natural ageing. Therefore, we investigated hot stamping and W-temper forming for [...] Read more.
Due to their high specific strength, EN AW-7xxx aluminium alloys are promising materials for reducing the weight of automotive structural parts. However, their formability at room temperature is poor due to pronounced natural ageing. Therefore, we investigated hot stamping and W-temper forming for EN AW-7075 and a modified variant of EN AW-7021. For hot stamping of the modified EN AW-7021, a low-temperature stabilisation heat treatment (pre-aging at 80 °C for 1 h) was incorporated into the process chain design to inhibit natural ageing after forming. The process chains were compared with respect to dimensional accuracy, mechanical properties, microstructure, precipitation status (assessed by differential scanning calorimetry) and crashworthiness. It was found that hot stamping is suitable to form failure-free parts with good dimensional accuracy for both alloys while W-temper forming suffers from springback. Within a time-span of 21 days after forming, hardness values of hot stamped and stabilised parts did not increase significantly. Compared to non-stabilised parts, stabilised parts also showed significantly improved folding behaviour in quasi-static compression testing and absorbed approximately 15% more energy. Full article
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18 pages, 9304 KiB  
Article
Experimental Investigations of the In-Die Quenching Efficiency and Die Surface Temperature of Hot Stamping Aluminium Alloys
by Kailun Zheng, Junyi Lee, Wenchao Xiao, Baoyu Wang and Jianguo Lin
Metals 2018, 8(4), 231; https://doi.org/10.3390/met8040231 - 2 Apr 2018
Cited by 21 | Viewed by 6599
Abstract
The in-die quenching is a key stage in the hot stamping volume production chain which determines the post-formed strength of lightweight alloy components, tool life, and hot stamping productivity. In this paper, the performance of in-die quenching, reflected by the quenching efficiency (the [...] Read more.
The in-die quenching is a key stage in the hot stamping volume production chain which determines the post-formed strength of lightweight alloy components, tool life, and hot stamping productivity. In this paper, the performance of in-die quenching, reflected by the quenching efficiency (the time of work-piece held within stamping dies) and die surface temperature during the simulated hot stamping process of AA6082, was experimentally and analytically investigated. A range of in-die quenching experiments were performed for different initial work-piece and die temperatures, quenching pressures, work-piece thickness, and die clearances, under hot stamping conditions. In addition, a one-dimensional (1D) closed-form heat transfer model was used to calculate the die surface temperature evolution that is difficult to obtain during practical manufacture situations. The results have shown that the in-die quenching efficiency can be significantly increased by decreasing the initial work-piece and die temperatures. Die clearances are required to be designed precisely to obtain sufficiently high quenching rates and satisfying post-formed strength for hot-stamped panel components. This study systematically considered an extensive variety of influencing factors on the in-die quenching performance, which can provide practical guides for stamping tool designers and manufacture systems for hot-stamping volume production. Full article
(This article belongs to the Special Issue Material and Process Design for Lightweight Structures)
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