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This paper aims to develop a lightweight convolutional neural network, WearNet , to realise automatic scratch detection for components in contact sliding such as those in metal forming. To this end, a large surface scratch dataset obtained from cylinder-on-flat sliding tests was used to train the WearNet with appropriate training parameters such as learning rate, gradient algorithm and mini-batch size. A comprehensive investigation on the network response and decision mechanism was also conducted to show the capability of the developed WearNet . It was found that compared with the existing networks, WearNet can realise an excellent classification accuracy of 94.16% with a much smaller model size and faster detection speed. Besides, WearNet outperformed other state-of-the-art networks when a public image database was used for network evaluation. The application of WearNet in an embedded system further demonstrated such advantages in the detection of surface scratches in sheet metal forming processes.

Due to the change from mass production to mass personalized production and the resulting intrinsic product flexibility, the automotive industry, among others, is looking for cost-efficient and resource-saving production methods to combining global just-in-time production. In addition to geometric manufacturing flexibility, additive manufacturing offers a resource-saving application for rapid prototyping and small series in predevelopment. In this study, the FDM process is utilized to manufacture the tooling to draw a small series of sheet metal parts in combination with the rubber pad forming process. Therefore, a variety of common AM polymer materials (PETG, PLA, and ABS) is compared in compression tests, from which PLA is selected to be applied as sheet metal forming die. For the rubber pad forming process, relevant processing parameters, i.e., press force and rubber cushion hardness, are studied with respect to forming depth. The product batch is examined by optical evaluation using a metrological system. The scans of the tool and sheet metal parts confirm the mechanical integrity of the additively manufactured die from polymer and thus the suitability of this approach for small series in sheet metal drawing processes, e.g., for automotive applications.

Lightweight sheet metals are attractive for aerospace and automotive applications due to their exceptional properties, such as low density and high strength. Sheet metal forming (SMF) is a key technology to manufacturing lightweight thin-walled complex-shaped components. With the development of SMF, numerical simulation and theoretical modelling are promoted to enhance the performance of new SMF technologies. Thus, it is extraordinarily valuable to present a comprehensive review of historical development in SMF followed by state-of-the-art advanced characterization and modelling approaches for lightweight metallic materials. First, the importance of lightweight materials and their relationship with SMF followed by the historical development of SMF are reviewed. Then, the progress of advanced finite element technologies for simulating metal forming with lightweight alloys is covered. The constitutive modelling of lightweight alloys with an explanation of state-of-the-art advanced characterization to identify the constitutive parameters are presented. Then, the formability of sheet metals with major influencing factors, the techniques for measuring surface strains in SMF and the experimental and modelling approaches for determining the formability limits are clarified. Finally, the review is concluded by affording discussion of the present and future trends which may be used in SMF for lightweight metallic materials.

Consistent and reasonable characterization of the material behavior under the coupled effects of strain, strain rate and temperature on the material flow stress is remarkably crucial in order to design as well as optimize the process parameters in the metal forming industrial practice. The objective of this work was to formulate an appropriate flow stress model to characterize the flow behavior of AISI-1045 medium carbon steel over a practical range of deformation temperatures (650–950 ∘ C) and strain rates (0.05–1.0 s − 1 ). Subsequently, the Johnson-Cook flow stress model was adopted for modeling and predicting the material flow behavior at elevated temperatures. Furthermore, surrogate models were developed based on the constitutive relations, and the model constants were estimated using the experimental results. As a result, the constitutive flow stress model was formed and the constructed model was examined systematically against experimental data by both numerical and graphical validations. In addition, to predict the material damage behavior, the failure model proposed by Johnson and Cook was used, and to determine the model parameters, seven different specimens, including flat, smooth round bars and pre-notched specimens, were tested at room temperature under quasi strain rate conditions. From the results, it can be seen that the developed model over predicts the material behavior at a low temperature for all strain rates. However, overall, the developed model can produce a fairly accurate and precise estimation of flow behavior with good correlation to the experimental data under high temperature conditions. Furthermore, the damage model parameters estimated in this research can be used to model the metal forming simulations, and valuable prediction results for the work material can be achieved.

Incremental sheet forming of titanium and its alloys has a significant role in modern manufacturing techniques because it allows for the production of high-quality products with complex shapes at low production costs. Stamping processes are a major contributor to plastic working techniques in industries such as automotive, aerospace and medicine. This article reviews the development of the single-point incremental forming (SPIF) technique in titanium and its alloys. Problems of a tribological and microstructural nature that make it difficult to obtain components with the desired geometric and shape accuracy are discussed. Great emphasis is placed on current trends in SPIF of difficult-to-form α-, α + β- and β-type titanium alloys. Potential uses of SPIF for forming products in various industries are also indicated, with a particular focus on medical applications. The conclusions of the review provide a structured guideline for scientists and practitioners working on incremental forming of titanium and titanium alloy sheets. One of the ways to increase the formability and minimize the springback of titanium alloys is to treat them at elevated temperatures. The main approaches developed for introducing temperature into a workpiece are friction heating, electrical heating and laser heating. The selection of an appropriate lubricant is a key aspect of the forming process of titanium and its alloys, which exhibit unfavorable tribological properties such as high adhesion and a tendency to adhesive wear. A review of the literature showed that there are insufficient investigations into the synergistic effect of rotational speed and tool rotation direction on the surface roughness of workpieces.

Sheet metal forming (SMF) is one of the most popular technologies for obtaining finished products in almost every sector of industrial production, especially in the aircraft, automotive, food and home appliance industries. Parallel to the development of new forming techniques, numerical and empirical approaches are being developed to improve existing and develop new methods of sheet metal forming. Many innovative numerical algorithms, experimental methods and theoretical contributions have recently been proposed for SMF by researchers and business research centers. These methods are mainly focused on the improvement of the formability of materials, production of complex-shaped parts with good surface quality, speeding up of the production cycle, reduction in the number of operations and the environmental performance of manufacturing. This study is intended to summarize recent development trends in both the numerical and experimental fields of conventional deep-drawing, spinning, flexible-die forming, electromagnetic forming and computer-controlled forming methods like incremental sheet forming. The review is limited to the considerable changes that have occurred in the SMF sector in the last decade, with special attention given to the 2015–2020 period. The progress observed in the last decade in the area of SMF mainly concerns the development nonconventional methods of forming difficult-to-form lightweight materials for automotive and aircraft applications. In evaluating the ecological convenience of SMF processes, the tribological aspects have also become the subject of great attention.

Friction is an unfavourable phenomenon in deep-drawing forming processes because it hinders the deformation processes and causes deterioration of the surface quality of drawpieces. One way to reduce the unfavourable effect of friction in deep-drawing processes is to use lubricants with the addition of hard particles. For this reason, this article presents the results of friction tests of dual-phase HCT600X+Z steel sheets using the flat die strip drawing test. Sunflower oil and rapeseed oil with the addition of 1, 5 and 10 wt.% of silicon dioxide (SiO2) particles were used as lubricants. Tests were also carried out in dry friction conditions and lubricated conditions using SiO2-modified oils and oils without the addition of particles, as a reference. Tests were carried out at different pressure values between 2 and 8 MPa. The effect of friction on the change in sheet surface roughness was also examined. For the entire range of pressures analysed, pure sunflower oil showed lower efficiency in reducing the coefficient of friction compared to pure rapeseed oil. In the pressure range of 4–8 MPa, the lubricants with 5 wt.% and 10 wt.% of particles were more effective in reducing friction than the biolubricant with the addition of 1 wt.% of SiO2. The lowest average roughness was observed for lubrication with sunflower oil containing 5 wt.% of particles. In relation to rapeseed oil, the addition of 10 wt.% of SiO2 provided a sheet surface with the lowest average roughness.

Flexible metal forming processes are novel ways to meet the growing needs for maintaining economic feasibility in mass production and customization. The flexible forming processes inherently have more process parameters to control than conventional processes, and thus they may be less economical. However, owing to the rapid development of computing technology over the last two decades, the numerical simulation approach has gained significant attention for optimizing the process parameters. Based on the numerical analysis, sophisticated theories have also been developed to describe the material deformation characteristics during forming processes. In this paper, incremental sheet metal forming, incremental bulk forming, and flexible roll forming are briefly overviewed with regard to innovative techniques for numerical simulations of various flexible metal forming processes.

Flexibility is crucial in forming processes as it allows the production of different product shapes without changing equipment or tooling. Single-point incremental forming (SPIF) provides this flexibility, but often results in excessive sheet metal thinning. To solve this problem, a pre-forming phase can be introduced to ensure a more uniform thickness distribution. This study represents advances in this field by developing a generalised approach that uses a multilayer perceptron artificial neural network (MLP ANN) to predict thinning results from the input parameters and employs a genetic algorithm (GA) to optimise these parameters. This study specifically addresses advanced high-strength steels (AHSSs) and provides insights into their formability and the optimisation of the forming process. The results demonstrate the effectiveness of the proposed method in minimising sheet metal thinning and represent a significant advance in flexible forming technologies applicable to a wide range of materials and industrial applications.

Single point incremental forming (SPIF) is becoming more and more widely used in the metal industry due to its high production flexibility and the possibility of obtaining larger material deformations than during conventional sheet metal forming processes. This paper presents the results of the numerical modeling of friction stir rotation-assisted SPIF of commercially pure 0.4 mm-thick titanium sheets. The aim of this research was to build a reliable finite element-based thermo-mechanical model of the warm forming process of titanium sheets. Finite element-based simulations were conducted in Abaqus/Explicit software (version 2019). The formability of sheet metal when forming conical cones with a slope angle of 45° was analyzed. The numerical model assumes complex thermal interactions between the forming tool, the sheet metal and the surroundings. The heat generation capability was used to heat generation caused by frictional sliding. Mesh sensitivity analysis showed that a 1 mm mesh provides the best agreement with the experimental results of total forming force (prediction error 3%). It was observed that the higher the size of finite elements (2 mm and 4 mm), the greater the fluctuation of the total forming force. The maximum temperature recorded in the contact zone using the FLIR T400 infrared camera was 157 °C, while the FE-based model predicted this value with an error of 1.3%. The thinning detected by measuring the drawpiece with the ARGUS non-contact strain measuring system and predicted by the FEM model showed a uniform thickness in the drawpiece wall zone. The FE-based model overestimated the minimum and maximum wall thicknesses by 3.7 and 5.9%, respectively.