Advances in Industrial and Manufacturing Engineering最新文献

The automotive industry is on the brink of transitioning to autonomous vehicles (AVs). This will require highly flexible assembly systems. This paper focuses on exploiting the capabilities of the technology base, e.g., sensors and image recognition, of AVs as assembly items and employing their self-driving function in assembly systems. This fundamentally new approach to matrix manufacturing systems based on autonomously navigating automated guided vehicles (AGVs) and the elimination of set assembly sequences is a growing topic of discussion. This study develops a conceptual framework, based on a systematic literature review and interviews with fifteen experts from three carmakers, for exploring the field of research and assessing the feasibility of employing the technology base of autonomous driving instead of AGVs. This study is intended for assembly planners and researchers of assembly systems in automotive manufacturing.

Electric vehicles driven by batteries are a key part of a sustainable mobility sector. Unfortunately, battery cell production is still associated with various negative environmental impacts, the use of critical raw materials and high manufacturing costs. The rising battery demand forces automotive original equipment manufacturers to drastically increase their capabilities over the next decades while fulfilling economical and ecological requirements. Continuous production technologies bear the potential to meet future battery cell demands by enabling higher throughputs compared to established batch processes. The control and optimization of continuous battery cell production steps with respect to product quality, manufacturing costs and environmental impacts is challenging due to high parameter spaces as well as temporal dependencies of production processes. Therefore, this study develops a controller that performs real-time optimization by proposing set parameters leading to desired quality, minimal costs and impacts of manufacturing activity. The controller is implemented using a deep learning model incorporating sequential information of the production process. A continuous mixing process with data acquired from a battery cell pilot line is used to validate the outlined controller. As result, the implementation for this use case achieves a relative error of 7.63% across all controllable parameters.

There is a lack of a universal Augmented Reality platform which can be used in manufacturing engineering and other education fields to display models, processes, animations and simulations alike. Such a platform has been developed as part of this contribution and enables instructors to manage online courses, teaching units and even entire study programs. To enhance the teaching in the classroom by using Augmented Reality visualizations, a new application has been developed, which runs on iOS as well as Android systems and displays the various objects along with additional information uploaded by the instructors. A novel storage format was devised which reduces the storage size of various models significantly wherefore performance on the phone's end is improved. Various common 3D file formats, such as STL, OFF and OBJ, can be imported and automatically converted to this new format. The same applies for results from FEM software Abaqus, MoldFlow and HyperXtrude. Results formatted to be analyzed by the popular pre-/post-processor GiD can also be uploaded at no additional expense. The users of the smartphone app can view, inspect and interact with the models and animations. The platform and app are designed for an easy-to-use setup by the educators and an intuitive use by the students.

This study examines the thermal conditions during laser beam welding of 100Cr6 high-strength steel using a TruDisk5000 disc laser with a continuous adjustable power range of 100–5000 W. Two parameter sets, characterized by laser power and welding speeds, were analyzed by thermal-metallurgical FE simulations to determine their impact on the thermal conditions during welding. The results show a significant shift in heat coupling, with conduction transitioning to deep penetration welding. As a result of the high welding speeds and reduced energy input, extremely high heating rates up to 2∙10⁴ K s⁻¹ (set A) respectively 4∙10⁵ K s⁻¹ (set B) occur. Both welds thus concern a range of temperature state values for which conventional Time-Temperature-Austenitization (TTA) diagrams are currently not defined, requiring calibration of the material models through general assumptions. Also, the change in energy input and welding speed causes significantly steep temperature gradients with a slope of approximately 5∙10³ K mm⁻¹ and strong drops in the temperature rates, particularly in the heat affected zone. The temperature cycles also show very different cooling rates for the respective parameter sets, although in both cases they are well below a cooling time t_8/5 of 1 s, so that the phase transformation always leads to the formation of martensite. Since the investigated parameters are known to cause a loss of technological strength and conditionally result in cold cracks, these results will be used for further detailed experimental and numerical investigation of microstructure, hydrogen distribution, and stress-strain development at different restraint conditions.

The aims of this publication is to study the physical and chemical conditions of formation of self-hardening aluminum phosphate binders based on orthophosphoric acid and fine-grained aluminum powder, research of its chemical structure and properties of core mixtures for foundry production.

The methods used in the work are: X-ray phase analysis on the Rigaku Ultima IV, differential thermogravimetric analysis on the STA 449 C. Orthophosphoric acid 85% concentration and finely dispersed aluminum powder were used as materials. Samples of core mixtures were made on the basis of quartz sand with an average particle size of 0.2 … 0.3 mm.

As a result of the experiments, it was established that in the system of orthophosphoric acid and finely dispersed aluminum powder, a chemical interaction occurs at ambient temperature, which leads to the formation of a phosphate binder. It has been confirmed that it is aluminum orthophosphate in the form of berlinite, and it does not undergo phase transformations, namely it is thermally stable when heated from 20 to 1000 оС. A significant advantage for core mixtures in foundry production is that the chemical interaction in this system does not begin immediately after mixing the components, but after 5 … 10 min, which is explained by the presence of protective oxide or hydroxide films on the aluminum particles. This ensures the period of technological suitability of the core mixture, and subsequently ensures its self-hardening.

In contrast to previously known aluminum phosphate binders, which required heating from 200 to 300 оС for their hardening, a self-hardening aluminum phosphate binders and the core mixture based on it were created for the first time.

With the amount of 2 … 3% of orthophosphoric acid and 1 … 2% of aluminum powder, after 1 h the strength indicators of the mixture based on quartz sand exceed 1 MPa, which is sufficient for the production of foundry cores.

Additive manufacturing (AM) is a promising technology for designing complex metallic pieces for different sectors with resource and time effectiveness. Titanium (Ti) is an essential critical material for AM development. AM can produce intricate and cost-effective components with Ti alloys for the transportation sector which would not be possible with conventional manufacturing (CM) technologies. This study assesses the impact of AM on the life cycle of Ti and its alloys by using review (numerical data, case examples) and dynamics simulation modelling. This article quantifies potential environmental benefits and examines aspects related to using Ti alloys in the automotive and aerospace industries. Mass flow, energy consumption and related greenhouse gas (GHG) emissions are assessed by making a comparison between subcategories of AM including binder jetting (BJT), directed energy deposition (DED), electron beam-based powder bed fusion (EB-PBF), and laser-based powder bed fusion (L-PBF) and CM processes including forging, milling, machining, and die casting. The results show that the AM subcategories considered potentially reduce manufacturing phase energy consumption and GHG emissions except for L-PBF. The findings highlight that an inclusive consideration of all life cycle phases is needed to fully identify potential benefits of AM for industries. Also, the scenario analysis in this study proposes the opportunity for saving mass and minimizing energy consumption and GHG emissions by optimizing the structural design and manufacturing processes for Ti components.

Some of the key issues with AWJ technology are high roughness, low depth of smooth zone, and grit embedment. When compared to the unsubmerged AWJ, the submerged AWJ gives less divergence and produces higher energy at the cross section of the jet. Hence, this study examined the effects of pressure, traverse rate, and standoff distance on roughness, depth of smooth zone, and grit embedment in both AWJ conditions. Here, single factor experiments are conducted for experimental investigation wherein one factor is varied and the others are kept constant. In comparison, the submerged AWJ gave significant improvement in the roughness and depth of the smooth zone at lower levels of pressure (150 and 200 MPa), higher levels of traverse rate (300 and 350 mm/min) and standoff distance (4, 5 and 6 mm). The significant difference in grit embedment was observed at lower levels of traverse rate (150 and 200 mm/min), higher levels of pressure (300 and 350 MPa), and all the levels of standoff distance (2, 3, 4, 5, and 6 mm). The grit embedment in the submerged condition was lower due to the removal of initially embedded grits due to flushing action produced by cavitation initiation.

This paper is focused on wire-arc additive manufacturing and has a twofold objective. First, to deliver an overall state-of-the-art review of the different aspects of modelling. Second, to provide a detailed analysis of the macro-scale finite element modelling. The methodology draws from the fundamentals of the macro, meso and micro-scale modelling of the process, to the main strategies and objectives behind the development of analytical, statistical, machine learning and finite element analyses of macro-scale modelling. The intention is to provide information on the pre-processing requirements, solution techniques and results that are currently being worked on by some of the leading researchers in the field. This will enable readers to understand the main challenges, relevance, and assumptions of the different published works. The theoretical and numerical aspects are intentionally kept in a clear and understandable level so that users of finite element computer programs having the know-how on wire-arc additive manufacturing can bridge the actual gap to the developers of the programs.

In deep hole machining operations with twist drills, whirling vibrations lead to a significant increase in hole diameter deviation and circularity error. In this article, a nonlinear physical model with special consideration of the contact area between the margins of the tool and the workpiece is developed to predict the hole circularity of drilling operations. Numerical simulations are used to study the geometry of the drilling tool to propose a new margin design. In an experimental study, it is shown that the newly developed margin geometry for twist drill tools decreases radial vibrations and leads to a significant improvement in hole diameter deviations and hole circularities.

The present study explores a combination of numerical and simulation approaches to generate a process map for identifying the regimes of conduction and keyhole modes of melting and verify the same with experimental data. Finite Element based simulation studies were conducted to determine the regions of conduction mode, keyhole mode, and transition by varying the laser power and speed. Single tracks and density cubes were processed based on the simulation results to confirm the melting modes and study its effect on microstructure and hardness. Increase in volumetric energy density (VED) causes a shift in microstructure of single tracks, from a mix of short columnar and equiaxed grains in conduction mode to long columnar grains in keyhole mode, with an overall increase in the grain size. The melt pool depth to width ratio also increases with VED. The VED based criteria alone cannot determine melting modes as the single-track samples at 81 J/mm³ exhibited both conduction mode (at 250 W) and keyhole mode (at 350 W). Almost all the printed cubes showed high density (>99.9%) irrespective of melting mode. Similar to single track the average grain size of bulk samples increased with increase in VED. The bulk samples were subjected to three different heat treatments (Homogenisation, Solution treatment and Direct Double Aging) to study their effect on the microstructures and mechanical properties. Homogenisation resulted in near identical equiaxed microstructure irrespective of processing parameters. The highest hardness of about 470 HV was observed for the direct double aged samples.