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The shift to electric mobility is driving disruptive transformations in the automotive sector worldwide. It poses significant but different opportunities and challenges to incumbents and latecomers at both the firm and country levels. China's green industrial policy has facilitated its rapid catching up and even leapfrogging in some domains of electromobility. This article asks whether the exploitation of this window of opportunity can be replicated in other latecomer countries. Accordingly, it provides a comparative analysis of the automotive green window of opportunity in Brazil, India, and South Africa, three emerging economies with long established but structurally different automotive industries. To do so, it examines domestic preconditions, policy and enterprise responses, and preliminary industrial development outcomes. Although all the three countries face constraints in replicating China's relative success, the article shows how green opportunities and threats are unequally divided between the three countries. [ABSTRACT FROM AUTHOR]

In response to the challenges posed by economic globalisation and increasing customer demands, enterprises are compelled to adapt and refine their production models and operational objectives, which motivates this paper to address the integrated production scheduling and vehicle routing problem in the distributed manufacturing environment (IPSVRP-DME). The objective is to simultaneously minimise both total energy consumption and total earliness/tardiness. Initially, a mixed integer programming model is proposed to address small-scale problems using Gurobi. Considering the NP-hardness of the problem, a novel Self-adapted Gaussian Mutation-based Arithmetic Optimiser Algorithm (SGMAOA) is developed to handle medium-scale and large-scale instances. To address the complexity of decision-making, an innovative two-level encoding method that encompasses four decision dimensions is introduced. Additionally, an incremental repair strategy is devised to rectify infeasible solutions caused by unreasonable delivery batching, while a time relaxation strategy is proposed to further enhance service levels without compromising energy consumption. Comparative experiments are conducted to demonstrate the effectiveness of SGMAOA, which is benchmarked against five prominent metaheuristics. In addition, a specific example is applied for the discussion of managerial applications and to illustrate the practicality of the proposed model and solution method. [ABSTRACT FROM AUTHOR]

The automotive industry introduces a sizable number of new automobile products annually. The naming of new products may have significant impact on their market performance. Diverging from prior research on the impact of product names, companies' innovative consciousness endows them with a certain level of proactive positioning, thereby implementing independent naming strategies after considering product factors and consumer preferences passively. This paper analyzes the drivers of the market performance of sequential products on the naming of new products in Chinese automotive industry. We collected market share data and names of various car series from January 2007 to September 2022. Then, we calculated semantic distances between names and performed empirical tests. Our findings show that firms demonstrate a risk preference pattern contrary to traditional prospect theory when using the previous car series' market share as a reference point. In the interplay between market orientation and risk preferences, the relationship between the market share of the last car series and the similarity in names between old and new car series follows an inverted U-shaped pattern. This study extends the discussion on risk preferences within the behavioral theory of the firm (BTOF) and proposes a decision mechanism for product naming that considers market and firm factors during the response phase of market orientation. [ABSTRACT FROM AUTHOR]

Buyer-supplier negotiations play a central role in supply chain networks regulating the conditions for the exchange of goods. This paper investigates the relationships between influencing factors and their impact on bargaining power. In a multiple case study, we triangulate secondary data from 12 German automotive suppliers. Following a structural equation modelling approach, bargaining power and the effects of those influencing variables are analysed. Four relationships can be found. (1) The availability of internal resources and the existence of strong buyer-supplier relationships have a positive effect on bargaining power. (2) A positive influence of buyer-supplier relationships on gaining access to internal resources can be identified. (3) External market conditions have a small negative effect on bargaining power. (4) No significant effect can be found looking at the impact of external market conditions on internal resources or buyer-supplier relationships. The findings support theory by showing that internal resources and strong buyer-supplier relationships positively influence bargaining power. Based on these results, managers are advised to prioritise strategic resource allocation, implement win-win strategies, and employ benchmarking techniques to enhance competitiveness and strengthen bargaining positions. [ABSTRACT FROM AUTHOR]

Production systems have to be adapted continuously to changing circumstances. This means that the responsible production planner has to frequently make decisions about reconfiguring complex systems under uncertainty whose outcome greatly affects the company's business success. Discrete-event simulation is one powerful tool to support the necessary analysis and scenario evaluation, but still remains time-consuming and tricky to set up and to maintain. When implemented as a digital twin of the production system, the simulation model can maintain a high degree of accuracy over a long time period. An approach to realise this potential is presented and illustrated in this paper with a use case from the automotive industry. This paper contributes several new methods and findings to the development of digital twins of production systems: Firstly, it demonstrates how exceptional events in the validation of the digital twin can be handled. Secondly, it shows how structural changes in the system can be discovered using data on machine activity and process mining. Thirdly, the paper introduces a possibility on how to assess the accuracy of the digital twin. Furthermore, it demonstrates how to assess the robustness of the digital twin to estimation errors in machine processing times. [ABSTRACT FROM AUTHOR]

For automobile manufacturers, reducing vehicle interior noise is essential for increasing customer satisfaction and vehicle quality. Windshield wipers are one of the major components that generate such noises, and faulty wipers could negatively affect passengers' psychological and physiological perceptions while driving. Thus, identifying faulty wipers during the manufacturing process would improve the driving experience and vehicle and road safety as well as reduce driver distraction. However, the existing windshield wiper noise-detection process is entirely manual, relies upon human subjectivity, and is time-consuming. Accordingly, this paper develops a novel automated windshield wiper fault-detection system. First, a novel binarization approach is used to effectively binarize the transformed spectrograms of sound signals from windshield wiper operation to segment nAoisy regions. Then, a new matrix-factorisation approach called orthogonal binary singular value decomposition is proposed to decompose binarized mel spectrograms into uncorrelated binary eigenimages to extract meaningful features and identify faulty wipers. Then, the $ k $ k -nearest neighbour classifier is utilised to classify the extracted features into normal or faulty windshield wipers. Finally, to demonstrate the effectiveness of the proposed system, it was validated on real-life windshield wiper reversal and squeal noise datasets, where it outperformed existing methods and achieved accuracies of 95% and 94%, respectively. [ABSTRACT FROM AUTHOR]

Managing acquired subsidiaries can be daunting. Parent and affiliate executives strive to co-create value, but fixed mindsets around subsidiary autonomy can result in diverging interests and outcomes. Through a longitudinal study of Audi’s post-acquisition integration of supercar manufacturer Lamborghini, this article provides guidance on how to manage the level of acquired subsidiary autonomy as a strategic dial that can be dynamically adjusted over time for mutual benefit. This dynamic approach to autonomy rests on three specific managerial levers—appraisal respect, organizational identity, and resource orchestration. These can enable the renewal of competitive capabilities and sustain post-acquisition success. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) provides new opportunities to improve manufacturing lines' performance and in-plant logistic processes. The digital milk-run system represents the new frontier to optimize material handling strategies but is still not fully exploited to address material distribution depending on the time slots required by the manufacturing lines. Therefore, to fill this gap, this paper investigates the actual integration of the milk-run system with an IoT system. An analytical model for planning a dynamic routing strategy for tugger trains to deliver the materials to different workstations of a production line has been developed. The proposed model provides a materials distribution consistent with the time slot required by the manufacturing line, ensuring the minimisation of the total distance of the routes. An algorithm developed in Python is proposed to solve the NP-hard problem (nondeterministic polynomial time problem). The model has been applied to a real case of a worldwide automotive company to validate and prove its efficacy and efficiency. Indeed, compared to the current in-plant logistic strategy, (i) the inventory stock of each workstation was ensured, (ii) the average utilization rate of the tugger trains' fleet was improved, and (iii) the daily path was minimized. [ABSTRACT FROM AUTHOR]

This paper analyzes the hydrogen refueling process for heavy-duty vehicles according to the SAE J2601/2 protocol. Attention is paid to two key aspects of the protocol that affect the refueling process: treatment of the storage system from a thermodynamic and geometric point of view and the maximum deliverable flow rate of the station in the refueling process. The effect of the ratio of the inner diameter to the inner length of the total volume on the refueling process was then analyzed, and it was shown how far the new approach results deviate from the results obtained by applying the SAE protocol. A total supply of 28 kg was simulated but with three different configurations: 14∗2 kg tanks, 7∗4 kg tanks, and 4∗7 kg tanks. When analyzing the effect of varying the ratio of inner diameter to inner length, it was noted that in the most conservative case, there is an overestimation in terms of final temperature for the three configurations of about: 2.1 °C, 1.4 °C and 1.1 °C, respectively. This aspect has a significant impact on the refueling time, which could be reduced by about 9.9% in the first case and about 7.1% and 5.4% in the other two. In addition, refueling using the multi-tank approach was simulated for some case studies assimilated to heavy vehicles currently on the market in terms of the amount of hydrogen stored. These refuelings were carried out with stations capable of delivering a maximum flow rate of 120 g/s, 180 g/s, and 240 g/s. It is inferred that increasing the flow rate from 120 g/s to 180 g/s results in time savings for the three cases of: 35%, 34% and 37%. On the other hand, running up to 240 g/s results in time savings of: 54%, 52% and 55%. [Display omitted] • Conventional refueling processes have temperature margin to be exploited. • Hydrogen refueling with innovative multi-tank approach. • Impact of increasing the maximum flow rate up to 240 g/s. • Multi-approach tank allows a reduction of about 10% in the refueling time. • Flow rate increase to 240 g/s results in time savings of more than 50%. [ABSTRACT FROM AUTHOR]

The article from the Physics Teacher journal discusses the deployment of an airbag in a scene from the television series Reacher. It explores the physics behind airbag deployment, the history of airbags, and modern airbag technology. The article presents two methods for students to analyze the realism of the scene in question, using principles of impulse and Newton's second law. Ultimately, the article concludes that the events portrayed in the television series are impossible based on the calculated forces required for airbag deployment. [Extracted from the article]

Trichloroethylene (TCE) is a volatile, colorless liquid that is widely used as a chlorinated organic vehicle in industrial production and processing industries. Many workers exposed to trichloroethylene may develop trichloroethylene hypersensitivity syndrome (THS). However, the underlying mechanism of THS is still unclear, especially liver injury. The present study aimed to investigate whether Wnt5a/c-Jun N-terminal kinase (JNK) is involved in and regulates liver injury caused by TCE exposure and to provide new directions for the prevention and treatment in clinical settings of liver injury caused by TCE exposure. We used 6- to 8-week-old SPF-grade BALB/c female mice to establish a TCE sensitization model and explored the mechanism through inhibitor intervention. We found that the expression of Wnt5a/JNK was significantly elevated in the liver of TCE sensitization-positive mice. Inhibitors of Wnt Production 2 (IWP-2) are known antagonists of the Wnt pathway. TCE-sensitization mice treated with IWP-2 showed downregulated Wnt5a/JNK expression, reduced Kupffer cell activation, and decreased liver injury. At the same time, we found that phosphorylated JNK in TCE-sensitization mouse livers and extracted Kupffer cells showed a significant downward trend after inhibition of Wnt5a function. We also found that a specific JNK inhibitor, SP600125, decreased the secretion of cytokines and chemokines and decreased Kupffer cell activation. We demonstrated that Wnt5a/JNK was involved in the regulation of liver injury in TCE-sensitization mice and that it exacerbated liver injury by activating Kupffer cells and releasing chemokines. We therefore hypothesized that Kupffer cell activation was affected by JNK, which reduced chemokine and cytokine secretion and attenuated liver injury in TCE-sensitization mice. [ABSTRACT FROM AUTHOR]

In April 2024, workers at Volkswagen's huge plant in Chattanooga, Tennessee, voted overwhelmingly to join the United Auto Workers. The victory was highly-significant; the union had organized the first foreign-owned automaker in the South after decades of trying. A breakthrough in a sector responsible for half of North American auto production, this "seismic victory" was widely-reported. This article probes the reasons for the union's victory, advancing the concept of "long haul unionism" to understand it. While media accounts stressed short-term factors – including the UAW's recent revival and a wider post-pandemic labor upsurge – I argue that it also occurred because of the union's long haul strategy. The UAW had been trying to organize the plant since 2010, losing elections in 2014 and 2019. Undeterred, it stayed on the ground, gradually overcoming its "outsider" label. It also focused effectively on workers' demands for a stronger voice in the plant. The victory illustrated how southern organizing often required sustained effort over many years, something highlighted by previous union fights, including Operation Dixie in the 1940s and the J.P. Stevens campaign of the 1970s. As such, the win needs to be understood in the context of history – not just contemporary conditions. [ABSTRACT FROM AUTHOR]

With the rapid development of the automotive manufacturing industry, enhancing production efficiency and flexibility in stamping workshops has become crucial for maintaining competitiveness. This paper presents an intelligent scheduling method based on an enhanced genetic algorithm to address the scheduling challenges in automotive stamping workshops. By incorporating the magic square selection method for initializing the population and an improved roulette wheel selection operation, this approach significantly enhances the search efficiency and solution quality of the genetic algorithm. During the algorithm's implementation, innovative crossover methods and decoding mechanisms were designed to better accommodate the production characteristics and constraint conditions of stamping workshops. The proposed method was validated using production data from an automotive factory. The scheduling results demonstrate that the enhanced genetic algorithm effectively addresses over 95% of the scheduling issues encountered in intelligent scheduling of automotive stamping workshops. The algorithm markedly improves workshop production efficiency, reduces production cycles, and enhances the stability and feasibility of production plans. This study provides a robust technical solution for intelligent production management in automotive stamping workshops, offering substantial theoretical significance and practical application value. [ABSTRACT FROM AUTHOR]

The non-fusion weld-brazing method has gained attention in automotive manufacturing, particularly for joining zinc-coated steels, due to its reduced heat input and resulting decrease in welding defects such as cracking and warping. However, despite extensive research, a significant gap persists in understanding how various characteristics of weld-brazed joints impact their mechanical properties. This study aims to investigate the key factors influencing the mechanical properties and failure behavior of weld-brazed zinc-aluminum-magnesium (ZnAlMg) coated interstitial free (IF) steel. Two weld-brazing procedures, differing in heat input, were employed to develop brazed joints with varying bead geometries, microstructures, and interfacial layer thicknesses. Results indicate that while the sample with higher heat input exhibited a larger bead size, higher precipitate density, and thicker interfacial layer, its peak load during shear-tensile testing was identical to that of the other specimen. However, the joint with lower heat input showed greater extension during mechanical testing. This study showed that bead characteristics alone proved insufficient for predicting the mechanical behavior of welded-brazed joints. Experimental and numerical strain distribution analysis revealed that weld-brazed joint characteristics directly influence the distribution of applied loading across different regions of the joint. The specimen with a larger bead size and higher precipitate density exhibited lower degrees of rotation during loading, leading to higher localized strain at the base metal, necking, and failure. These findings clarify the uncertainty surrounding the correlation between weld-brazed characteristics and mechanical properties. By identifying a significant factor influencing joint mechanical properties, this study advances the application of weld-brazing technology in joining zinc-coated steels within the automotive industry. [ABSTRACT FROM AUTHOR]

As hydrogen vehicles gain popularity, car manufacturers are introducing numerous models, presenting customers with the challenge of choosing the most suitable option. To address this, Multi-Criteria Decision Analysis methods are often used to evaluate and select the best alternative. This study applies the Characteristic Objects Method (COMET) to address the practical problem of selecting the most appropriate hydrogen car for decision-makers. Using data provided by manufacturers, we evaluate ten hydrogen vehicles and create six decision models based on the preferences of three decision-makers, utilizing both the recently proposed Triad Support and Expected Solution Point-COMET algorithms. The models provide insights into how customer preferences can be extracted and represented in decision models. Moreover, we analyze local weights derived from the models to understand customer expectations for hydrogen cars better. The results of our study highlight the effectiveness of the COMET approach in capturing and comparing decision-maker preferences, offering a valuable methodology framework for future applications in similar multi-criteria decision-making problems. [ABSTRACT FROM AUTHOR]

This research uses grounded theory to present a digital marketing model based on dynamic capabilities in the automotive industry. This qualitative research is based on grounded theory. Semistructured interviews were used to collect information, and the Strauss and Corbin method and the paradigm model were used to analyze data. The data are collected based on purposive sampling through semi-structured interviews with 15 experts and managers from the automotive industry. The sample is large enough to provide the required information and theoretical adequacy. The data obtained from interviews were analyzed through the process of open, axial, and selective coding. Accordingly, a digital marketing model based on dynamic capabilities in the automotive industry concerning the grounded theory was presented. The proposed model is both descriptive and prescriptive. Thus, we have selected well-known and qualified experts from the field of digital marketing and the automotive industry to provide a better model. However, the proposed model has implications for marketing managers to improve dynamic capabilities in the automotive industry. [ABSTRACT FROM AUTHOR]

Hybrid transmissions have attracted great attention in the automotive industry due to their energy-saving, low-emission properties, and have become a focus of research and development. This paper presents a new method to design the configuration of two mode power split hybrid transmission using the combination of the simple planetary gear trains (PGT). For this purpose, the hybrid transmission structure is divided into two substructures, which achieve different operation modes respectively. Then the output of one substructure is reconnected with the components of another substructure to obtain the complete hybrid transmission configuration. In addition, by adding additional shifting elements, the hybrid configurations can also realize the fixed gear mode as a traditional automatic transmission. As a result, 38 hybrid transmissions are obtained, and the kinematic analysis of a new configuration is performed for the subsequent optimization. Furthermore, using this decomposition and recombination method, the hybrid transmissions with multiple PGTs and different operation modes can be synthesized by changing the predefined modes. [ABSTRACT FROM AUTHOR]

Although ISO 14001 offers benefits such as improved environmental performance and a business advantage, to date, the financial benefits associated with ISO 14001 in South Africa have not been quantified. Thus, this study sought to assess the financial benefits accruing to selected manufacturing enterprises, accredited as ISO 14001 compliant, located in three South African provinces. Data was collected through an e-survey and interviews with key decision-makers in the selected organisations. The results show that the benefits of ISO14001 certification include improved environmental awareness among employees; enhanced responsibility for employees’ environmental concerns, better data management; reduced operational and production costs; and new income streams linked to re-use and recycling initiatives. But savings are seemingly sector-specific, with auto manufacturers making the greatest return on investment. Overall, the long-term financial benefits justify the relatively high cost; time-intensive obligations and extensive human resource requirements of ISO14001 certification for most, but not all, the companies under study. [ABSTRACT FROM AUTHOR]

UV-A exposure is a major risk factor for melanoma, nonmelanoma skin cancer, photoaging, and exacerbation of photodermatoses. Since people spend considerable time in cars daily, inadequate UV-A attenuation by car windows can significantly contribute to the onset or exacerbation of these skin diseases. Given recent market trends in the automobile industry and known impact of car windows on cumulative lifelong UV damage to the skin, there is a need to comparatively evaluate UV transmission across windows in electric vehicles (EV), hybrid vehicles (HV), and gas vehicles (GV) as well as variability based on year of manufacture and mileage to inform car manufacturers and consumers of the potential for UV exposure to the skin based on vehicle. To compare UV-A and UV-B transmission through EV, HV, and GV windows to evaluate differences in UV protection offered by various vehicle types. Comparative observational study that took place between June 10, 2024 and August 2, 2024. Outdoor setting with natural light exposure at car dealerships in Philadelphia, PA and New York, NY. 34 vehicles—15 gas vehicles (GV), 9 hybrid vehicles (HV), 10 electric vehicles (EV)—ranging from 2015 to 2025. Window status, with UV transmission measurements recorded with windows open and closed. UV-A and UV-B transmission through car windows was measured using UV transmission meters. The percent reduction in transmission was calculated. The front windshield and driver side window have statistically significant differences in UV-A attenuation across all vehicles with an average of 99.25% and 88.78% (p < 0.001), respectively. GV, HV, and EV all demonstrated significant differences in UV-A attenuation in most other vehicle windows compared to the front windshield. For GV, the front windshield, rear side windows (p =.176, p =.578) and back windshield (p =.457) blocked more UV-A than the front side windows. EV offered greater UV-A attenuation at the front and back windshield (p =.09) but not for any side windows, and HVs showed consistent differences in UV-A protection between the front windshield and all other windows. Domestic GV, trucks and luxury vehicles had no significant differences in UV-A attenuation across windows indicating reduced UV-A exposure for driver and passengers, whereas non-luxury vehicles had a notable difference in UV-A protection between the front windshield and all other windows. Regression analysis found mileage, not year of manufacture, to be a significant predictor of driver's side UV-A attenuation, with more UV-A attenuation as vehicle mileage increases. Most vehicles evaluated offer effective UV-A and UV-B protection from the front windshield but lack sufficient UV-A protection for drivers nor consistently to other passengers with notable exceptions seen with domestic GV, trucks, and luxury vehicles. Mileage and not year of manufacture also contributed to additional UV-A attenuation. This underscores the importance of patient education on this known source for cumulative lifetime UV exposure and need for continued sun safety measures even while driving given potential UV-A impact on the skin. [ABSTRACT FROM AUTHOR]

The adhesion between metals and polymers plays a pivotal role in numerous industrial applications, especially within the automotive and aerospace sectors, where there is a growing demand for materials that are both lightweight and durable. This study introduces an innovative technique to improve the adhesion between a metal and a polymer in hybrid structures through the synergistic use of anodization and plasma treatment. By forming a nanoporous oxide layer on aluminum surfaces, anodization enhances the interface for polymer binding. Plasma treatment further augments the surface properties by increasing the concentration of functional groups, thus allowing better polymer infiltration during the 3D printing process. Comprehensive analyses, including X-ray photoelectron spectroscopy, energy dispersive X-ray spectroscopy, and contact angle measurements confirm the substantial enhancement in the bonding strength achieved through this method. Additionally, cross-sectional analysis via focused ion-beam etching provides a detailed view of polymer integration into the treated layers. The findings suggest significant potential for these surface modification strategies to advance the development of lightweight, robust composites suitable for use in sectors such as automotive, aerospace, and consumer electronics. [ABSTRACT FROM AUTHOR]

Maraging steel is a high-performance material valued for its exceptional properties, making it ideal for demanding applications such as aerospace, tooling, and automotive industries, where high strength, toughness, and precision are required. These steels can be prepared by powder metallurgy techniques, which offer new processing possibilities. This paper introduces novel thermal powder pre-treatment and its impact on the final mechanical properties. Solid solution pre-treatment results in a modest improvement in strength (from 972 MPa to 1000 MPa), while the use of pre-aged powder achieves the highest strength (1316 MPa) and lowest ductility (2.6%). A self-composite material is created by mixing pre-treated powders with the same chemical composition but different properties. Such material was characterized by intermediate strength (1174 MPa) and ductility (3.1%). Although challenges such a porosity and oxidation were present, this approach allows for tuning of mechanical properties by mixing pre-treated powders, offering significant potential for advanced engineering applications. [ABSTRACT FROM AUTHOR]

Over several decades, manufacturing enterprises have embraced Lean manufacturing (LM) to enhance the management of operations and optimize their production processes. In more recent times, the advent of transformative technologies facilitating network connectivity and process digitalization has underscored the imperative to adopt Industry 4.0 (I4.0), leading to smart manufacturing. Consequently, the simultaneous incorporation of these paradigms necessitates comprehending their interplay, elucidating the interconnections and collective impact on performance through the modeling of influence. Manufacturing enterprises often find themselves at a crossroads when aspiring to integrate both LM and I4.0. This article seeks to reinforce the integration of LM and I4.0 by presenting an accurately identified array of combinations through a comprehensive links cartography. The integration model, automatized by the proposed LeaTechRP algorithm, considers the company's desired objectives and offers diverse pathways to achieve them. The overarching goal is to furnish a decision-aided approach that explores a cohesive implementation path assessing the usefulness of LM tools and the relevancy of I4.0 technologies. Finally, the method application is showcased within the realm of the automotive industry. This demonstration serves to underscore the practical insight, extending its relevance from a strategic perspective to the operational level within the production workshops. [ABSTRACT FROM AUTHOR]