#Yanfeng

[beurich]

Europa-Debüt: Yanfeng präsentiert zukunftsweisendes Innenraumkonzept EVI für Elektrofahrzeuge

Die Vision: ein Fahrzeuginnenraum, der im Cockpitbereich dem Fahrer viel Bewegungsspielraum und Entspannung ermöglicht. Neuss (ots) – Yanfeng stellt erstmals sein „Electric Vehicle Interior“-Konzept (EVI) in Europa vor. Die Vision: ein Fahrzeuginnenraum, der dank der Designfreiheit einzigartige Innenraumerlebnisse bietet und im Cockpitbereich dem Fahrer viel Bewegungsspielraum und Entspannung…

[digitalcreationsllc]

Qilin Ransomware Claims Attack on Automotive Giant Yanfeng

The threat actors published multiple samples to prove their alleged access to Yanfeng systems and files, including financial documents, non-disclosure agreements, quotation files, technical data sheets, and internal reports.

[sanvees]

characters that made me feral in 2023 (in no particular order):

ohara yamato (kimi ni wa todokanai) | dongfang qingcang (love between fairy and devil) | yang yanfeng (love in translation) | kusakabe ritsu (the end of the world with you) | tantai jin (till the end of the moon) | seo jaewon (the eighth sense) | babe (pit babe) | pu yiyong (oh no here comes trouble) | chen yi (kiseki dear to me) | togawa (old fashion cupcake)

[zishuge]

please listen to this cover of <<I Know>> (aka THAT song) by ruan nanzhu's voice actor li yanfeng and cry with me 😭😭😭😭

source: xhs

[statmodeller]

"I am using excel in daily working but many things were unknown in excel which I have learnt in this session." - Pankaj Panchal   Completed 2-Day workshop on "MS Excel to Boost Productivity" at Yanfeng Seating (India) Pvt. Ltd. (Supplier of MG Motors)   We have covered, • Saving, Sharing, Protecting, Inspecting Workbook • Basic Formula & Functions • Cell Reference • Advanced Sorting & Filtering • Conditional Formatting • Data Validation • Advanced Formulas • Excel Charts & Excel Table • Dashboard Thank you Mr. Jay Gohil for giving this opportunity.   𝗪𝗮𝗻𝘁 𝘁𝗼 𝗱𝗼 𝗶𝘁 𝗳𝗼𝗿 𝘆𝗼𝘂𝗿 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻? 𝗽𝗹𝗲𝗮𝘀𝗲 𝗰𝗼𝗻𝘁𝗮𝗰𝘁 𝘂𝘀.   ‪📧 : contact@statmodeller.com ‬ ‪💬 : https://lnkd.in/dpTmMwzg 📞‬ : +91 98982 33268 ‪🌐 : www.statmodeller.com   ‪#statmodeller #datascience #operationalexcellence #training #consultancy #statistics #powerbi #datavisualization #dataanalytics #dashboard   #excel #microsoft #microsoftexcel #office #word #o #powerpoint #business #cursodeexcel #data #msexcel #powerbi #exceltips #datascience #microsoftoffice #dashboard #exceltraining #excelbasico #dataanalytics https://www.instagram.com/p/Cnvu-sNtcKX/?igshid=NGJjMDIxMWI=

[drmikewatts]

Complex & Intelligent Systems, Volume 10, Issue 5, October 2024

1) 3D facial animation driven by speech-video dual-modal signals

Author(s): Xuejie Ji, Zhouzhou Liao...Meng Mao

Pages: 5951 - 5964

2) An improved fruit fly optimization algorithm with Q-learning for solving distributed permutation flow shop scheduling problems

Author(s): Cai Zhao, Lianghong Wu...Hongqiang Zhang

Pages: 5965 - 5988

3) A strategic framework for optimal decisions in football 1-vs-1 shot-taking situations: an integrated approach of machine learning, theory-based modeling, and game theory

Author(s): Calvin Yeung, Keisuke Fujii

Pages: 5989 - 6008

4) Population state-driven surrogate-assisted differential evolution for expensive constrained optimization problems with mixed-integer variables

Author(s): Jiansheng Liu, Bin Yuan...Haobo Qiu

Pages: 6009 - 6030

5) An intelligent MRI assisted diagnosis and treatment system for osteosarcoma based on super-resolution

Author(s): Xu Zhong, Fangfang Gou, Jia Wu

Pages: 6031 - 6050

6) A dimension-aware gaining-sharing knowledge algorithm for distributed hybrid flowshop scheduling with resource-dependent processing time

Author(s): Rong-hao Li, Jun-qing Li...Li-jie Mei

Pages: 6051 - 6080

7) Crossover in mutation oriented norm evolution

Author(s): Bingyu Lv, Xianchang Wang, Rui Zhang

Pages: 6081 - 6102

8) Residual serialized cross grouping transformer for small scale sketch face recognition

Author(s): Kangning Du, Yinkai Wang...Yanan Guo

Pages: 6103 - 6116

9) A blockchain-based hybrid encryption technique with anti-quantum signature for securing electronic health records

Author(s): Shtwai Alsubai, Abdullah Alqahtani...Abdu Gumaei

Pages: 6117 - 6141

10) ACGND: towards lower complexity and fast solution for dynamic tensor inversion

Author(s): Aiping Ye, Xiuchun Xiao...Cong Lin

Pages: 6143 - 6157

11) Prioritizing complex health levels beyond autism triage using fuzzy multi-criteria decision-making

Author(s): A. S. Albahri, Rula A. Hamid...A. H. Alamoodi

Pages: 6159 - 6188

12) A multi-scale spatial–temporal capsule network based on sequence encoding for bearing fault diagnosis

Author(s): Youming Wang, Lisha Chen

Pages: 6189 - 6212

13) Bayesian network structure learning with a new ensemble weights and edge constraints setting mechanism

Author(s): Kaiyue Liu, Yun Zhou, Hongbin Huang

Pages: 6213 - 6229

14) A GAN based PID controller for highly adaptive control of a pneumatic-artificial-muscle driven antagonistic joint

Author(s): Zhongchao Zhou, Yuxi Lu...Wenwei Yu

Pages: 6231 - 6248

15) Modelling attack and defense games in infrastructure networks with interval-valued intuitionistic fuzzy set payoffs

Author(s): Yibo Dong, Jin Liu...Weili Li

Pages: 6249 - 6265

16) An oversampling algorithm of multi-label data based on cluster-specific samples and fuzzy rough set theory

Author(s): Jinming Liu, Kai Huang...Jian Mao

Pages: 6267 - 6282

17) Intelligent optimization of steam gasification catalysts for palm oil waste using support vector machine and adaptive transition marine predator algorithm

Author(s): Xin Guo, Yassine Bouteraa...Diego Martín

Pages: 6283 - 6303

18) Chinese Named Entity Recognition method based on multi-feature fusion and biaffine

Author(s): Xiaohua Ke, Xiaobo Wu...Binglong Li

Pages: 6305 - 6318

19) Improving two-layer encoding of evolutionary algorithms for sparse large-scale multiobjective optimization problems

Author(s): Jing Jiang, Huoyuan Wang...Fei Han

Pages: 6319 - 6337

20) A hybrid model to improve IC-related metrics of semantic similarity between words

Author(s): Jia Xiao

Pages: 6339 - 6377

21) Long-term student performance prediction using learning ability self-adaptive algorithm

Author(s): Yi Ren, Xinjie Yu

Pages: 6379 - 6408

22) A novel fractional neural grey system model with discrete q-derivative

Author(s): Zhenguo Xu, Caixia Liu, Tingting Liang

Pages: 6409 - 6420

23) Research on charging strategy based on improved particle swarm optimization PID algorithm

Author(s): Xiuzhuo Wang, Yanfeng Tang...Chunsheng Xu

Pages: 6421 - 6433

24) Spatial-temporal memory enhanced multi-level attention network for origin-destination demand prediction

Author(s): Jiawei Lu, Lin Pan, Qianqian Ren

Pages: 6435 - 6448

25) An iterative two-phase optimization method for heterogeneous multi-drone routing problem considering differentiated demands

Author(s): Huan Liu, Guohua Wu...Wei Zhou

Pages: 6449 - 6466

26) Hybrid structure of maximal ideals in near rings

Author(s): B. Jebapresitha

Pages: 6467 - 6480

27) Joint data augmentations for automated graph contrastive learning and forecasting

Author(s): Jiaqi Liu, Yifu Chen...Yang Gao

Pages: 6481 - 6490

28) Grounding rod hanging and removing robot with hand-eye self-calibration capability in substation

Author(s): Yunhan Lin, Jiahui Wang...Huasong Min

Pages: 6491 - 6507

29) Two-stage many-objective evolutionary algorithm: enhanced dominance relations and control mechanisms for separated balance

Author(s): Wei Li, Qilin Niliang...Qiaoyong Jiang

Pages: 6509 - 6543

30) Enhancing learning on uncertain pixels in self-distillation for object segmentation

Author(s): Lei Chen, Tieyong Cao...Jibin Yang

Pages: 6545 - 6557

31) Aggregation operators of complex fuzzy Z-number sets and their applications in multi-criteria decision making

Author(s): Ali Köseoğlu, Fatma Altun, Rıdvan Şahin

Pages: 6559 - 6579

32) Pose estimation algorithm based on point pair features using PointNet + +

Author(s): Yifan Chen, Zhenjian Li...Mingyue Zhang

Pages: 6581 - 6595

33) An edge-assisted group authentication scheme for the narrowband internet of things

Author(s): Guosheng Zhao, Huan Chen, Jian Wang

Pages: 6597 - 6618

34) Transformer fusion-based scale-aware attention network for multispectral victim detection

Author(s): Yunfan Chen, Yuting Li...Xiangkui Wan

Pages: 6619 - 6632

35) Joint entity and relation extraction combined with multi-module feature information enhancement

Author(s): Yao Li, He Yan...Xu Wang

Pages: 6633 - 6645

36) MDSTF: a multi-dimensional spatio-temporal feature fusion trajectory prediction model for autonomous driving

Author(s): Xing Wang, Zixuan Wu...Lyuchao Liao

Pages: 6647 - 6665

37) Comprehensive comparisons of gradient-based multi-label adversarial attacks

Author(s): Zhijian Chen, Wenjian Luo...Xiangkai Yang

Pages: 6667 - 6692

38) Nested attention network based on category contexts learning for semantic segmentation

Author(s): Tianping Li, Meilin Liu, Dongmei Wei

Pages: 6693 - 6703

39) DFFNet: a lightweight approach for efficient feature-optimized fusion in steel strip surface defect detection

Author(s): Xianming Hu, Shouying Lin

Pages: 6705 - 6723

40) Scalable concept drift adaptation for stream data mining

Author(s): Lisha Hu, Wenxiu Li...Chunyu Hu

Pages: 6725 - 6743

41) Twin-tower transformer network for skeleton-based Parkinson’s disease early detection

Author(s): Lan Ma, Hua Huo...Ningya Xu

Pages: 6745 - 6765

42) Complete area-coverage path planner for surface cleaning in hospital settings using mobile dual-arm robot and GBNN with heuristics

Author(s): Ash Yaw Sang Wan, Lim Yi...Mohan Rajesh Elara

Pages: 6767 - 6785

43) Variational AdaBoost knowledge distillation for skin lesion classification in dermatology images

Author(s): Xiangchun Yu, Guoliang Xiong...Qing Xu

Pages: 6787 - 6804

44) An adaptive trimming approach to Bayesian additive regression trees

Author(s): Taoyun Cao, Jinran Wu, You-Gan Wang

Pages: 6805 - 6823

45) DIB-UAP: enhancing the transferability of universal adversarial perturbation via deep information bottleneck

Author(s): Yang Wang, Yunfei Zheng...Tieyong Cao

Pages: 6825 - 6837

46) Moboa: a proposal for multiple objective bean optimization algorithm

Author(s): Lele Xie, Xiaoli Lu...Shangshang Yang

Pages: 6839 - 6865

47) Multi-UAV pursuit-evasion gaming based on PSO-M3DDPG schemes

Author(s): Yaozhong Zhang, Meiyan Ding...Frank Jiang

Pages: 6867 - 6883

48) Enhancing robustness in asynchronous feature tracking for event cameras through fusing frame steams

Author(s): Haidong Xu, Shumei Yu...Lining Sun

Pages: 6885 - 6899

49) Recommending suitable hotels to travelers in the post-COVID-19 pandemic using a novel FAHP-fuzzy TOPSIS approach

Author(s): Tin-Chih Toly Chen, Hsin-Chieh Wu, Keng-Wei Hsu

Pages: 6901 - 6915

50) GraphMriNet: a few-shot brain tumor MRI image classification model based on Prewitt operator and graph isomorphic network

Author(s): Bin Liao, Hangxu Zuo...Yong Li

Pages: 6917 - 6930

51) Global semantics correlation transmitting and learning for sketch-based cross-domain visual retrieval

Author(s): Shichao Jiao, Xie Han...Ligang He

Pages: 6931 - 6952

52) An end-to-end hand action recognition framework based on cross-time mechanomyography signals

Author(s): Yue Zhang, Tengfei Li...Maoxun Sun

Pages: 6953 - 6964

53) Model inductive bias enhanced deep reinforcement learning for robot navigation in crowded environments

Author(s): Man Chen, Yongjie Huang...Zhisong Pan

Pages: 6965 - 6982

54) A novel BWM-entropy-COPRAS group decision framework with spherical fuzzy information for digital supply chain partner selection

Author(s): Kai Gao, Tingting Liu...Tapan Senapati

Pages: 6983 - 7008

55) A novel fuzzy finite-horizon economic lot and delivery scheduling model with sequence-dependent setups

Author(s): Esmat Sangari, Fariborz Jolai, Mohamad Sadegh Sangari

Pages: 7009 - 7031

56) Strategic analysis of intelligent connected vehicle industry competitiveness: a comprehensive evaluation system integrating rough set theory and projection pursuit

Author(s): Yi Wang, Fan Zhang...Kai Kang

Pages: 7033 - 7062

57) KnowledgeNavigator: leveraging large language models for enhanced reasoning over knowledge graph

Author(s): Tiezheng Guo, Qingwen Yang...Yingyou Wen

Pages: 7063 - 7076

58) Self-supervised multi-object tracking based on metric learning

Author(s): Xin Feng, Yan Liu...Zhi Liu

Pages: 7077 - 7088

59) Optimal time reuse strategy-based dynamic multi-AGV path planning method

Author(s): Ke Wang, Wei Liang...Qi Wang

Pages: 7089 - 7108

60) Reinforced robotic bean optimization algorithm for cooperative target search of unmanned aerial vehicle swarm

Author(s): Jun Li, Hongwei Cheng...Xiaoming Zhang

Pages: 7109 - 7126

61) Optimal saturated information load analysis for enhancing robustness in unmanned swarms system

Author(s): Jian Wu, Yichuan Jiang...Linfei Ding

Pages: 7127 - 7142

62) Multi-view subspace clustering based on multi-order neighbor diffusion

Author(s): Yin Long, Hongbin Xu...Xujian Zhao

Pages: 7143 - 7161

63) Improving the reliability of nanosatellite swarms by adopting blockchain technology

Author(s): Hussein A. Ibrahim, Marwa A. Shouman...Ayman Ahmed

Pages: 7163 - 7182

64) Reparameterized underwater object detection network improved by cone-rod cell module and WIOU loss

Author(s): Xuantao Yang, Chengzhong Liu, Junying Han

Pages: 7183 - 7198

65) A granularity data method for power frequency electric and electromagnetic fields forecasting based on T–S fuzzy model

Author(s): Peng Nie, Qiang Yu...Xiguo Yuan

Pages: 7199 - 7211

66) A multi-period intuitionistic fuzzy consensus reaching model for group decision making problem in social network

Author(s): Wei Yang, Luxiang Zhang

Pages: 7213 - 7234

67) Automatic control of UAVs: new adaptive rules and type-3 fuzzy stabilizer

Author(s): Jinya Cai, Haiping Zhang...Chunwei Zhang

Pages: 7235 - 7248

68) Attention-based RNN with question-aware loss and multi-level copying mechanism for natural answer generation

Author(s): Fen Zhao, Huishuang Shao...Yan Yu

Pages: 7249 - 7264

69) Prototype as query for few shot semantic segmentation

Author(s): Leilei Cao, Yibo Guo...Qiangguo Jin

Pages: 7265 - 7278

70) Automated abnormalities detection in mammography using deep learning

Author(s): Ghada M. El-Banby, Nourhan S. Salem...Essam N. Abd El-Azziz

Pages: 7279 - 7295

71) A distributed adaptive policy gradient method based on momentum for multi-agent reinforcement learning

Author(s): Junru Shi, Xin Wang...Qingtao Wu

Pages: 7297 - 7310

72) Indirect adaptive observer control (I-AOC) design for truck–trailer model based on T–S fuzzy system with unknown nonlinear function

Author(s): Muhammad Shamrooz Aslam, Hazrat Bilal...Mohamed Hussien

Pages: 7311 - 7331

73) Unsupervised Graph Representation Learning with Inductive Shallow Node Embedding

Author(s): Richárd Kiss, Gábor Szűcs

Pages: 7333 - 7348

74) TRAA: a two-risk archive algorithm for expensive many-objective optimization

Author(s): Ji Lin, Quanliang Liu

Pages: 7349 - 7371

75) A novel bayesian network-based ensemble classifier chains for multi-label classification

Author(s): Zhenwu Wang, Shiqi Zhang...Benting Wan

Pages: 7373 - 7399

76) Transferable preference learning in multi-objective decision analysis and its application to hydrocracking

Author(s): Guo Yu, Xinzhe Wang...Quanling Zhang

Pages: 7401 - 7418

77) Correction to: MDSTF: a multi-dimensional spatio-temporal feature fusion trajectory prediction model for autonomous driving

Author(s): Xing Wang, Zixuan Wu...Lyuchao Liao

Pages: 7419 - 7420

[cmisayali]

Automotive Interior Component Market is Estimated to Witness High Growth Owing to Increase in Passenger Vehicle Production

The automotive interior component market comprises interior parts and accessories for seating, door panels, instrument panels, flooring solutions used to enhance comfort and safety in vehicles. These components are manufactured using high strength, durable and lightweight materials to meet rugged operational requirements. Growing consumer demand for premium interiors with enhanced aesthetic appeal and comfort features is driving automotive OEMs to adopt innovative interior designs and technologies.

The Global automotive interior component market is estimated to be valued at US$ 164.64 Bn in 2024 and is expected to exhibit a CAGR of 6.5% over the forecast period 2024 To 2031. Key Takeaways Key players operating in the automotive interior component market are Johnson Control, Toyota Boshoku Corporation, Lear Corporation, Toyoda Gosei Co., Ltd., Faurecia SA, Continental AG, Magna International, Delphi, Adient plc., Robert Bosch GmbH, Yanfeng (China), Lear Corporation, Antolin, Polydesign Systems, and Machino Plastics Limited. These players are focusing on new product development, partnerships, and expansions to gain higher share in the market. There is a high opportunity for manufacturers of eco-friendly and lightweight materials as automakers are under pressure to reduce vehicle weight and carbon footprint. 3D printing technology and development of smart surfaces with integrated electronics also present significant growth opportunities. The Global Automotive Interior Market Demand is witnessing increasing globalization with major players expanding their presence in Asia Pacific and Middle East & Africa. Regional customers demand localized manufacturing, which is enabling supply-chain optimization and competitive pricing. China, India and Mexico are emerging as top automobile manufacturing hubs attracting investments by global automotive interior parts suppliers. Market Drivers The global automotive interior component market is witnessing high growth owing to increase in passenger vehicle production over the years. As per projections, global passenger vehicle sales are expected to surpass 100 million units by 2026. This rising vehicle demand across developed and developing nations is driving need for interior parts and accessories among OEMs. Innovation in autonomous, connected and electric vehicles is also presenting opportunities for design and technology advancements in automotive interior components market.

PEST Analysis

Political: The automotive industry is subject to stringent government regulations regarding vehicle safety and emissions standards. New rules imposed by regulatory bodies can impact design and production of interior components.

Economic: Rising disposable incomes and growing automobile sales are fueling demand for upgraded interiors with advanced features. However, economic slowdowns may negatively impact consumer spending on non-essential automotive upgrades.

Social: Growing consumer inclination toward luxury, comfort and infotainment is driving innovation in areas like seats, audio-visual displays and panoramic sunroofs. Technology-savvy customers expect digitally enabled dashboards and connectivity options in vehicles.

Technological: Developments in materials, digitization and connectivity are reshaping automotive cabins. Lightweight composites, smart textiles and customizable digital dashboards are being integrated. Integrated voice assistance, mobile app controls and advanced driver-assistance features are becoming standard. Geographical Regions of Concentration

In terms of value, The Automotive Interior Component Market Regional is concentrated in Asia Pacific and Europe. Asia Pacific currently holds the largest share, supported by the strong presence of automotive manufacturing hubs and rising vehicle production in China, India, Japan, South Korea and other developing nations. Majority of global automobile manufacturers have established supplier networks and manufacturing facilities in the region to cater to increasing domestic demand. Fastest Growing Region North America region is poised to witness the fastest growth in the automotive interior component market over the forecast period. This can be attributed to recovery of the automobile sector from recession, rising vehicle parc and preference for technologically advanced features among consumers. Automakers are focusing on implementing connectivity, customized infotainment and digital dashboards to enhance driver experience in this region.

Get More Insights on Automotive Interior Component Market

For Enhanced Understanding, Dive into the Report in the Language that Connects with You.

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About Author:

Ravina Pandya, Content Writer, has a strong foothold in the market research industry. She specializes in writing well-researched articles from different industries, including food and beverages, information and technology, healthcare, chemical and materials, etc. (https://www.linkedin.com/in/ravina-pandya-1a3984191)

[businessindustry]

Automotive Fascia Market: Impact Growth, Forecast, Research 2024-2032

The Reports and Insights, a leading market research company, has recently releases report titled “Automotive Fascia Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2023-2031.” The study provides a detailed analysis of the industry, including the global Automotive Fascia Market share, size, trends, and growth forecasts. The report also includes competitor and regional analysis and highlights the latest advancements in the market.

Report Highlights:

How big is the Automotive Fascia Market?

The global automotive fascia market size was US$ 22.3 Billion in 2022. The global automotive fascia market is expected to register a revenue CAGR of 6.5% during the forecast period and reach a market size of US$ 39.3 Bn in 2031.

What are Automotive Fascia?

An automotive fascia is the front or rear section of a vehicle designed to enhance its appearance and aerodynamics. It usually incorporates parts like the bumper, grille, headlights, and trim pieces into a cohesive and attractive surface. Constructed from materials such as plastic, metal, or composites, the fascia also serves practical functions, including absorbing impact in minor collisions and housing sensors and other essential technological features found in modern vehicles.

Request for a sample copy with detail analysis: https://www.reportsandinsights.com/sample-request/2047

What are the growth prospects and trends in the Automotive Fascia industry?

The automotive fascia market growth is driven by various factors and trends. The automotive fascia market is a dynamic and expanding sector, fueled by advancements in vehicle design, increased demand for visually appealing and aerodynamically efficient vehicles, and the integration of cutting-edge technologies. Market growth is driven by factors such as rising vehicle production, consumer preferences for lightweight and durable materials, and stringent safety regulations. Innovations in materials, like high-performance plastics and composites, are improving the functionality and design potential of automotive fascias. Key industry players are focusing on research and development to provide customized and advanced fascia solutions, meeting the evolving demands of the automotive industry. Hence, all these factors contribute to automotive fascia market growth.

What is included in market segmentation?

The report has segmented the market into the following categories:

By Product Type:

Standard Fascia

Illuminated Fascia

Sports Fascia

Luxury Fascia

Others

Material Type:

Plastic

Metal

Composites

Others

Technology:

Passive Safety Systems

Active Safety Systems

Advanced Driver Assistance Systems (ADAS)

Connectivity and Integrated Electronics

Others

Vehicle Type:

Passenger Cars

Light Commercial Vehicles (LCVs)

Heavy Commercial Vehicles (HCVs)

Electric Vehicles (EVs)

Others

Sales Channel:

Original Equipment Manufacturers (OEMs)

Aftermarket

Segmentation By Region:

North America:

United States

Canada

Europe:

Germany

The U.K.

France

Spain

Italy

Russia

Poland

BENELUX

NORDIC

Rest of Europe

Asia Pacific:

China

Japan

India

South Korea

ASEAN

Australia & New Zealand

Rest of Asia Pacific

Latin America:

Brazil

Mexico

Argentina

Middle East & Africa:

Saudi Arabia

South Africa

United Arab Emirates

Israel

Who are the key players operating in the industry?

The report covers the major market players including:

Magna International Inc.

Samvardhana Motherson Group

Faurecia

Plastic Omnium

Flex-N-Gate Corporation

Montaplast GmbH

Compagnie Plastic Omnium

Hanwha Advanced Materials Corporation

Yanfeng Global Automotive Interiors

SRG Global

Toyoda Gosei Co., Ltd.

View Full Report: https://www.reportsandinsights.com/report/Automotive Fascia-market

If you require any specific information that is not covered currently within the scope of the report, we will provide the same as a part of the customization.

About Us:

Reports and Insights consistently mееt international benchmarks in the market research industry and maintain a kееn focus on providing only the highest quality of reports and analysis outlooks across markets, industries, domains, sectors, and verticals. We have bееn catering to varying market nееds and do not compromise on quality and research efforts in our objective to deliver only the very best to our clients globally.

Our offerings include comprehensive market intelligence in the form of research reports, production cost reports, feasibility studies, and consulting services. Our team, which includes experienced researchers and analysts from various industries, is dedicated to providing high-quality data and insights to our clientele, ranging from small and medium businesses to Fortune 1000 corporations.

Contact Us:

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[langyanqi]

Jia Yanfeng wrote on Weibo: Recently, a Zhejiang fan asked me in a private message whether the Zhejiang club will become the Zhejiang Hangzhou team in the future. I understand the Zhejiang fans on the

[sassyharmonywombat]

asientos de carro, previsión del tamaño del mercado mundial, clasificación y cuota de mercado de las 16 principales empresas

Según el nuevo informe de investigación de mercado “Informe del Mercado Global del asientos de carro 2024-2030”, publicado por QYResearch, se prevé que el tamaño del mercado mundial del asientos de carro alcance 84.42 mil millones de USD en 2030, con una tasa de crecimiento anual constante del 2.0% durante el período de previsión.

Figure 1. Tamaño del mercado de asientos de carro global (US$ Millión), 2019-2030

Figure 2. Clasificación y cuota de mercado de las 16 principales entidades globales de asientos de carro (la clasificación se basa en los ingresos de 2023, actualizados continuamente)

Según QYResearch, los principales fabricantes mundiales de asientos de carro incluyen Lear Corporation, Adient, Faurecia, Toyota Boshuku, Magna, Yanfeng, Hyundai Transys, TS TECH, NHK Springs, Tachi-S, etc. En 2023, las diez principales entidades mundiales tenían una cuota de aproximadamente 82.0% en términos de ingresos.

Sobre QYResearch

QYResearch se fundó en California (EE.UU.) en 2007 y es una empresa líder mundial en consultoría e investigación de mercados. Con más de 17 años de experiencia y un equipo de investigación profesional en varias ciudades del mundo, QY Research se centra en la consultoría de gestión, los servicios de bases de datos y seminarios, la consultoría de OPI, la investigación de la cadena industrial y la investigación personalizada para ayudar a nuestros clientes a proporcionar un modelo de ingresos no lineal y hacer que tengan éxito. Gozamos de reconocimiento mundial por nuestra amplia cartera de servicios, nuestra buena ciudadanía corporativa y nuestro firme compromiso con la sostenibilidad. Hasta ahora, hemos colaborado con más de 60.000 clientes en los cinco continentes. Trabajemos estrechamente con usted y construyamos un futuro audaz y mejor.

QYResearch es una empresa de consultoría a gran escala de renombre mundial. La industria cubre varios segmentos de mercado de la cadena de la industria de alta tecnología, que abarca la cadena de la industria de semiconductores (equipos y piezas de semiconductores, materiales semiconductores, circuitos integrados, fundición, embalaje y pruebas, dispositivos discretos, sensores, dispositivos optoelectrónicos), cadena de la industria fotovoltaica (equipos, células, módulos, soportes de materiales auxiliares, inversores, terminales de centrales eléctricas), nueva cadena de la industria del automóvil de energía (baterías y materiales, piezas de automóviles, baterías, motores, control electrónico, semiconductores de automoción, etc.. ), cadena de la industria de la comunicación (equipos de sistemas de comunicación, equipos terminales, componentes electrónicos, front-end de RF, módulos ópticos, 4G/5G/6G, banda ancha, IoT, economía digital, IA), cadena de la industria de materiales avanzados (materiales metálicos, materiales poliméricos, materiales cerámicos, nanomateriales, etc.), cadena de la industria de fabricación de maquinaria (máquinas herramienta CNC, maquinaria de construcción, maquinaria eléctrica, automatización 3C, robots industriales, láser, control industrial, drones), alimentación, bebidas y productos farmacéuticos, equipos médicos, agricultura, etc.

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Stellantis sues another supplier it says withheld parts to extract price increase

Stellantis NV has filed another lawsuit against a parts supplier over a pricing dispute, this time targeting the manufacturer of fuel tanks for the Chrysler Pacifica minivan. The automaker sued Quebec-based Spectra Premium Mobility Solutions Ltd. earlier this month after the supplier threatened to stop shipping fuel tanks for the plug-in hybrid minivan, which would shut down production at Windsor Assembly Plant, according to the lawsuit filed in Oakland County Circuit Court. Stellantis said its supplier demanded a 12.5% price increase retroactive to Jan. 1 or it would withhold parts. The automaker was set to run out of fuel tanks late last week, which would bring the line to a halt. An Oakland County judge denied the automaker’s request for a temporary restraining order that would have forced the supplier to keep shipping parts at contract price. It is unclear to what extent, if any, production has been impacted at the plant, which produces 350 minivans per week and is aiming to scale up to 750 per week in the second half of the year, per the lawsuit. Stellantis declined to comment. The automaker has warned of devastating consequences, including sweeping layoffs and large financial damages, resulting from production shutdowns related to supplier disputes. However, the automaker has averted long-term production disruptions by either winning injunctive relief from the court or paying suppliers under protest. The lawsuit against Spectra marks the fourth known legal fight Stellantis has initiated against its suppliers this year. Pricing disputes are common in the automotive industry, but it is rare for a customer to sue its supplier. Long-simmering tensions between Stellantis and parts makers have come to a head in recent months amid the automaker’s relentless cost-cutting pursuit and unapologetic targeting of its supply base to drive down costs. Domestic rivals Ford Motor Co. and General Motors Co. are in the same fight to retain market share and electrify their portfolios as Tesla Inc. and foreign automakers pose greater threats. As in previously filed lawsuits, Stellantis argued that a production shutdown would have dire consequences not only on the automaker, but the supply chain dependent on the Pacifica. “The economic consequences of a cascading automotive industry disruption of this magnitude is massive and immeasurable,” the lawsuit said. But Judge Victoria Valentine denied the restraining order against Spectra, departing from her previous rulings on the other two supplier lawsuits that have crossed her docket. In the case against Yanfeng, which involved millions of dollars allegedly lost in a cyberattack, Valentine granted injunctive relief to Stellantis. Same went for Kamax when Valentine’s order forced it to keep parts flowing to the automaker. In the Spectra order entered July 5, Valentine did not provide a reason for denying the request this time. The decision is a blow for Stellantis as the automaker turns to the court to protect it from supplier demands for better pricing. The company has argued that its suppliers are bound by contract terms even if the economics have become unfavorable. Lawyers representing the suppliers have argued that the supply agreements are not enforceable requirement contracts. In a case against MacLean-Fogg, Oakland County Judge Michael Warren also denied a preliminary injunction against the supplier. To keep production going, Stellantis is paying the company under protest while the case works its way through the court. After the judge indicated that Stellantis was likely to win the case on merits, however, MacLean-Fogg’s attorneys moved the case to federal court. Patrick Green, attorney at Dickinson Wright representing Stellantis, did not return a request for comment on the most recent lawsuit. Matthew Letzmann, attorney at Brooks, Wilkins, Sharkey & Turco PLLC representing Spectra, declined to comment. Stellantis said in the lawsuit that in 2022 it agreed to pay 100% of Spectra’s raw material costs per agreed index and that the supplier…

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Cisal, rinnovo Rsu Yanfeng, lista in campo – Dentro Salerno | www.dentrosalerno.it

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Automotive Trim Market To Witness the Highest Growth Globally in Coming Years

The report begins with an overview of the Automotive Trim Market and presents throughout its development. It provides a comprehensive analysis of all regional and key player segments providing closer insights into current market conditions and future market opportunities, along with drivers, trend segments, consumer behavior, price factors, and market performance and estimates. Forecast market information, SWOT analysis, Automotive Trim Market scenario, and feasibility study are the important aspects analyzed in this report.

The Automotive Trim Market is experiencing robust growth driven by the expanding globally. The Automotive Trim Market is poised for substantial growth as manufacturers across various industries embrace automation to enhance productivity, quality, and agility in their production processes. Automotive Trim Market leverage robotics, machine vision, and advanced control technologies to streamline assembly tasks, reduce labor costs, and minimize errors. With increasing demand for customized products, shorter product lifecycles, and labor shortages, there is a growing need for flexible and scalable automation solutions. As technology advances and automation becomes more accessible, the adoption of automated assembly systems is expected to accelerate, driving market growth and innovation in manufacturing.

The market will rise rapidly, and the aftermarket segment will grow with it in the coming years due to the increasing age of vehicles on the road and the demand for required aftermarket trims.

Get Sample PDF Report: https://www.fortunebusinessinsights.com/enquiry/request-sample-pdf/108005

Key Strategies

Key strategies in the Automotive Trim Market revolve around optimizing production efficiency, quality, and flexibility. Integration of advanced robotics and machine vision technologies streamlines assembly processes, reducing cycle times and error rates. Customization options cater to diverse product requirements and manufacturing environments, ensuring solution scalability and adaptability. Collaboration with industry partners and automation experts fosters innovation and addresses evolving customer needs and market trends. Moreover, investment in employee training and skill development facilitates seamless integration and operation of Automotive Trim Market. By prioritizing these strategies, manufacturers can enhance competitiveness, accelerate time-to-market, and drive sustainable growth in the Automotive Trim Market.

Major Automotive Trim Market Manufacturers covered in the market report include:

Magna International (Canada), Grupo Antolin (Spain), Faurecia (France), Toyoda Gosei Co. Ltd (Japan), Yanfeng Automotive Interiors (China), BASF SE (Germany), IAC Group (Luxembourg), Continental AG (Germany), Adient plc (U.S.), Cooper Standard (U.S.), Tata Autocomp System (India).

The market is also influenced by trends such as lightweight trims and sustainable materials without impacting the environment. Automotive trims play a major role in enhancing appearance, and the market is expected to have an high growth as major manufacturers shift towards high customization of their production.

Trends Analysis

The Automotive Trim Market is experiencing rapid expansion fueled by the manufacturing industry's pursuit of efficiency and productivity gains. Key trends include the adoption of collaborative robotics and advanced automation technologies to streamline assembly processes and reduce labor costs. With the rise of Industry 4.0 initiatives, manufacturers are investing in flexible and scalable Automotive Trim Market capable of handling diverse product portfolios. Moreover, advancements in machine vision and AI-driven quality control are enhancing production throughput and ensuring product consistency. The emphasis on sustainability and lean manufacturing principles is driving innovation in energy-efficient and eco-friendly Automotive Trim Market Solutions.

Regions Included in this Automotive Trim Market Report are as follows:

North America [U.S., Canada, Mexico]

Europe [Germany, UK, France, Italy, Rest of Europe]

Asia-Pacific [China, India, Japan, South Korea, Southeast Asia, Australia, Rest of Asia Pacific]

South America [Brazil, Argentina, Rest of Latin America]

Middle East & Africa [GCC, North Africa, South Africa, Rest of the Middle East and Africa]

Significant Features that are under offering and key highlights of the reports:

- Detailed overview of the Automotive Trim Market.

- Changing the Automotive Trim Market dynamics of the industry.

- In-depth market segmentation by Type, Application, etc.

- Historical, current, and projected Automotive Trim Market size in terms of volume and value.

- Recent industry trends and developments.

- Competitive landscape of the Automotive Trim Market.

- Strategies of key players and product offerings.

- Potential and niche segments/regions exhibiting promising growth.

Frequently Asked Questions (FAQs):

► What is the current market scenario?

► What was the historical demand scenario, and forecast outlook from 2024 to 2030?

► What are the key market dynamics influencing growth in the Global Automotive Trim Market?

► Who are the prominent players in the Global Automotive Trim Market?

► What is the consumer perspective in the Global Automotive Trim Market?

► What are the key demand-side and supply-side trends in the Global Automotive Trim Market?

► What are the largest and the fastest-growing geographies?

► Which segment dominated and which segment is expected to grow fastest?

► What was the COVID-19 impact on the Global Automotive Trim Market?

Table Of Contents:

1 Market Overview

1.1 Automotive Trim Market Introduction

1.2 Market Analysis by Type

1.3 Market Analysis by Applications

1.4 Market Analysis by Regions

1.4.1 North America (United States, Canada and Mexico)

1.4.1.1 United States Market States and Outlook 

1.4.1.2 Canada Market States and Outlook 

1.4.1.3 Mexico Market States and Outlook 

1.4.2 Europe (Germany, France, UK, Russia and Italy)

1.4.2.1 Germany Market States and Outlook

1.4.2.2 France Market States and Outlook 

1.4.2.3 UK Market States and Outlook

1.4.2.4 Russia Market States and Outlook 

1.4.2.5 Italy Market States and Outlook 

1.4.3 Asia-Pacific (China, Japan, Korea, India and Southeast Asia)

1.4.3.1 China Market States and Outlook

1.4.3.2 Japan Market States and Outlook 

1.4.3.3 Korea Market States and Outlook 

1.4.3.4 India Market States and Outlook 

1.4.3.5 Southeast Asia Market States and Outlook 

1.4.4 South America, Middle East and Africa

1.4.4.1 Brazil Market States and Outlook

1.4.4.2 Egypt Market States and Outlook 

1.4.4.3 Saudi Arabia Market States and Outlook 

1.4.4.4 South Africa Market States and Outlook 

1.5 Market Dynamics

1.5.1 Market Opportunities

1.5.2 Market Risk

1.5.3 Market Driving Force

2 Manufacturers Profiles

Continued…

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Yanfeng Envisions The Minimalist EV Cockpit Of The Future - CarScoops

https://news.google.com/rss/articles/CBMiXGh0dHBzOi8vd3d3LmNhcnNjb29wcy5jb20vMjAyNC8wMS95YW5mZW5nLWVudmlzaW9ucy10aGUtbWluaW1hbGlzdC1ldi1jb2NrcGl0LW9mLXRoZS1mdXR1cmUv0gFgaHR0cHM6Ly93d3cuY2Fyc2Nvb3BzLmNvbS8yMDI0LzAxL3lhbmZlbmctZW52aXNpb25zLXRoZS1taW5pbWFsaXN0LWV2LWNvY2twaXQtb2YtdGhlLWZ1dHVyZS9hbXAv?oc=5&utm_source=dlvr.it&utm_medium=tumblr

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Yanfeng und TactoTek kooperieren, um zukünftige Anwendungen im Fahrzeuginnenraum zu verbessern

Yanfeng und TactoTek werden gemeinsam hochintegrierte Mensch-Maschine-Schnittstellen-Lösungen (HMI) für zukünftige Smart-Cabin-Anwendungen entwickeln. Yanfeng, ein weltweit führender Automobilzulieferer, und TactoTek, ein Pionier und Marktführer im Bereich intelligenter Oberflächentechnologien, werden gemeinsam hochintegrierte Mensch-Maschine-Schnittstellen-Lösungen (HMI) für zukünftige…