Car Manufacturers Research Articles

PEDESTRIAN ALERT SYSTEM USING DEEP LEARNING

Pedestrian detection is an essential and significant task in any intelligent video surveillance system, as it provides the fundamental information for semantic understanding of the video footages. It has an obvious extension to automotive applications due to the potential for improving safety systems. Many car manufacturers (e.g., Volvo, Ford, GM, Nissan) offer this as an ADAS option in 2017. It is used in many cars and vehicles for automatic driver assistance systems. But when the ADAS system detects pedestrians but if fails to apply brakes on time accidents might happened. To overcome this situation our project provides an audio alert to the human passengers or driver in the vehicle so that they can apply manual brakes. In this project we will require Python libraries such as Pytorch and OpenCV. Pytorch is a widely used Machine Learning library. It is popular for the YOLO (You Only Look Once) algorithm which is built for Object Detection, we are using the YOLO algorithm and customize it to detect objects on a pedestrian dataset. Python has a library pyttsx3, that is capable to convert text-to-speech offline. Itextracts the label from the detected pedestrians in the video and converts the text label into speech. The algorithm detects the pedestrians when they are in a close approach to the vehicles and sends the identifies labels to the pyttsx3 speaker engine. An audio alert is generated by the engine and alerts the passengers or drivers. Keywords - YOLO, Pytorch, Pyttsx3, Object Detection, Python.

Special Issue on Advanced Metal Cutting Technologies

Cutting technologies are utilized in many industrial sectors, such as automobile, aircraft, and medical-device manufacturing as well as dies and molds. Thus, the requirements for higher geometric accuracy, better surface integrity, and longer component service lifetimes have substantially increased. In addition, maintaining high machining efficiency while simultaneously reducing power consumption and CO2 emissions during machining is important for sustainable development. This special issue features 11 papers on the most recent advances in cutting technologies for metals and composite materials. - Reverse finishing characteristics of drilling surfaces - Machining error simulation for end milling - Visualization of cutting phenomena using a single-crystal diamond tool - Milling of TiB2 particle-reinforced high-modulus steel - Electrodischarge-assisted turning of carbon fiber-reinforced polymers - Suppression of chatter vibration during double-insert turning - Prediction of surface roughness components during turning - Microtome blades for high-precision tissue sectioning - Boiling of coolant near the cutting edge in high-speed machining - Residual stress during drilling of aluminum alloy - Effect of strain hardening on burr control during drilling This issue provides an understanding of recent developments in cutting technologies, aiming to inspire further research in this field. We deeply appreciate the careful work of all the authors and thank the reviewers for their diligent efforts.

Application of Waste Tire in Construction: A Road towards Sustainability and Circular Economy

The global demand for rubber is on a steady rise, which is driven by the increasing production of automobiles and the growing need for industrial, medical, and household products. This surge in demand has led to a significant increase in rubber waste, posing a major global environmental challenge. End-of-life tire (ELT) is a primary source of rubber waste, having significant environmental hazards due to its massive stockpiles. While landfilling is a low-cost and easy-to-implement solution, it is now largely prohibited due to environmental concerns. Recently, ELT rubber waste has received considerable attention for its potential applications in civil engineering and construction. These applications not only enhance sustainability but also foster a circular economy between ELT rubber waste with the civil engineering and construction sectors. This review article presents a general overview of the recent research progress and challenges in the civil engineering applications of ELT rubber waste. It also discusses commercially available recycled rubber-based construction materials, their properties, testing standards, and certification. To the best of the authors’ knowledge, this is the first time such a discussion on commercial products has been presented, especially for civil engineering applications.

A non-uniform lattice design method for lightweight structures in 3D printing

Lightweight design is an essential topic in aerospace, automotive and other fields. In automobile manufacturing, the engine connecting rod is one of the main components; its lightweight design has a high reference value. And 3D printing provides a feasible solution for designing and manufacturing lightweight structures. Unlike the traditional geometrically homogeneous point design, this study offers a non-homogeneous point design method based on the spatial stress state of additively manufactured components. After numerical simulation of quasi-static stresses on a model of an engine connecting rod, finite element grid cells with different stress values are replaced by lattice cells with different specific stiffnesses at similar local stress levels. The overall specific stiffness of the structure is further improved by continuing the optimized design with the corresponding gradient-type reinforcement of the non-uniform lattice structure. The basic idea of this design is to perform non-uniform adaptive filling of solid parts under localized loading by employing different types of unit cells. Stereolithography 3D printing technology prepares the engine lattice structural parts for quasi-static compression comparison experiments and fracture analysis after failure. The conclusions show that the engine connecting rod members with non-homogeneous lattice have more excellent overall mechanical properties than homogeneous lattice members. This work demonstrates the feasibility of such design methods for 3D printing lightweight structures and optimization.

Influence of Hole Preparation Technique on Stretch Flangeability of Aluminium Alloys

Application of aluminium alloys has increased for light-weighting the sheet metal parts in manufacturing of automobiles. Formability is important in sheet metal forming of aluminium alloys. In the assessment of formability of sheet metals, stretch flangeability or edge formability is an important aspect in application such as flanges or plunged rims. The stretch flangeability refers to the ability to avoid cracking during hole expansion and it is evaluated by performing the hole expansion test. Besides material properties, hole making process also influences the stretch flangeability of aluminium alloys. In this work, the stretch flangeability of two Al-Mg alloys has been investigated through hole expansion tests by using three different hole making techniques namely punching, water jet cutting and laser cutting. The stretch flangeability of aluminium alloys has been compared with that of a high strength steel (Dual phase steel of grade DP600) which is more commonly used steel for stretch flanging applications.

A study on: Design and fabrication of E-glass fiber reinforced IPN composite chain plates for low duty chain drives

Chains are used in mechanical drives to carry away a large amount of load from one drive to another drive. Therefore the material of the chain should be able to withstand tensile loads and have high stiffness. Usually the chains are made up of iron. But the disadvantage is that iron consumes more weight and it is more expensive. In order overcome the difficulties, the chain plates are fabricated with the help of Interpenetrating Polymer Networks (IPNs) resins (with vinyl ester and polyurethane) and reinforced E-glass fiber composite material. The main aim of the project is to study and analyze the physical properties and structural properties of the plate material varying proportions of IPN resin such as 100% vinyl ester (VEU) with 0% polyurethane (PU), 90% VEU and 10% PU, 80% VEU and 20% PU, 70% VEU and 30% PU, 60% VEU and 40% PU. Finally a fatigue tests is conducted for different plates for different resin proportion and comparison is made between the characteristics of fabricated chain plate with that of iron material. Because of their dependability and durability, glass fibre reinforced composite link plates are used in material handling equipment, agricultural machinery, manufacturing conveyors, and automobile manufacture.

Product changes from various viewpoints along the product lifecycle – an empirical study

AbstractFrom an economic perspective, the appeal of a product diminishes over time. However, volatile markets and divergent technological advancements make it challenging to anticipate when and to what extent changes will be necessary. Therefore, it is important to be able to integrate changes after a product's launch. This paper provides an overview of different perspectives on the product lifecycle. In addition, the paper presents an empirical study on implementing changes at an automobile manufacturer.

Reducing uncertainty regarding customer expectations for a sustainable car interior design integrated in a data-informed design approach

AbstractSustainability is influencing the automotive industry. Car manufacturers are increasingly prioritizing sustainable materials. The production of these still pose environmental challenges. This paper addresses the trends related to sustainable car interiors. It emphasizes the importance of understanding how customers perceive these new materials. Seven in-depth interviews were conducted, followed by a survey with 106 participants to obtain generalized insights. The results will reduce the uncertainty regarding customer expectations for sustainable car interiors.

Advanced Lightweight Structural Materials for Automobiles: Properties, Manipulation, and Perspective

The key drivers for automotive manufacturers to develop vehicles with decreased weight are the growing requirements for improved fuel efficiency. This endeavor not only tackles the issues related to fuel efficiency but also aligns with the objectives of enhanced recyclability and overall performance of the vehicle, encompassing factors like driving efficiency, braking characteristics, and collision safety. Herein, a successful strategy entails investigating and utilizing lightweight materials with superior performance as substitutes for conventional automotive materials such as cast iron and steel. This article provides a thorough analysis of the lightweight materials that are currently being researched and available for use in the production of next-generation cars. These materials include composites, light alloys, high-strength steel, and other innovative materials. The review covers all aspects of the life cycle of automotive materials, examining their mechanical and physical characteristics, production processes, characterization strategies, and their uses. Both the merits and limitations of these materials are analyzed, leading to a nuanced understanding of suitable scenarios for their application. In anticipation of future challenges, the study suggests that advancements in versatile materials or enhancements in manufacturing and treatment techniques hold promise for overcoming potential obstacles, ultimately facilitating the creation of more capable, safer, durable, and environmentally friendly vehicles.

Does the dual-credit policy promote the technological development of new energy vehicles? An industry chain reconstruction perspective

With the deep application of automation and digitalization technologies, the global automobile value chains are undergoing a new round of large-scale restructuring, and the traditional supply chain structure taken vehicle manufacturers as the core has been broken. The dual-credit policy (DCP), taking over the subsidies for new energy vehicles (NEVs), plays a vital role in reconstructing, transforming, and upgrading the automobile industry. The target group of DCP is passenger vehicle manufacturers, but it is unclear how its implementation will affect the NEV industry chain. To address this issue, this study examined the impact of the DCP on the innovation performance of automobile manufacturing enterprises using a DID (difference-in-difference) model based on the data of 693 listed advanced manufacturing enterprises in China A-shares from 2014 to 2021. The empirical results show that the DCP has significantly promoted the innovation performance of automobile manufacturing enterprises. In terms of supply chain role heterogeneity, the impact of the DCP on the innovation performance of parts manufacturers is more significant. Regarding enterprise ownership heterogeneity, the DCP has a greater impact on the innovation performance of SOEs(state-owned enterprises). In addition, regarding regional heterogeneity, enterprises in eastern and middle regions are significantly affected by the DCP to improve innovation performance.

Joint impact of service efficiency and salvage value on the manufacturer’s shared vehicle-type strategies

With the rapid development of the sharing economy, many traditional automobile manufacturers have been choosing to provide the car sharing service. Some manufacturers share GVs, while others introduce EVs in the sharing market. We develop a model that a monopoly manufacturer who simultaneously sells GVs and EVs and discuss which type of vehicles should the manufacturer launch in the sharing market considering the service efficiency and the salvage value. Our findings are that no matter which type of vehicles the manufacturer shares, EV sales remain the same, but GV sales are reduced. This means that the manufacturer’s EV-sharing strategy always promotes EVs’ adoption. It is found that when both the service efficiency ratio of EV to GV and the salvage value gap between them are low or high, the manufacturer launches EVs; otherwise, the manufacturer launches GVs. We also find that the equilibrium vehicle-type strategy can maximize the manufacturer’s profit while being the most environmentally friendly only if the valuation of shared product is high. Through numerical analysis, we know that, although the manufacturer’s GV-sharing strategy worsens the environment, it always improves the social welfare. Notably, the manufacturer’s EV-sharing strategy is not always beneficial for the environment, especially if the service efficiency ratio is relatively high. Similarly, the manufacturer’s EV sharing does not always improve the social welfare, especially if the service efficiency ratio is in the middle range. The findings not only contribute to guiding the manufacturer’s vehicle-type strategies for car sharing, but also providing potential policy implications for the government’s effort in promoting EVs’ adoption.

Enhancing the exploitation of natural resources for green energy: An application of LSTM-based meta-model for aluminum prices forecasting

Efficient resource allocation for electric car production can be achieved by anticipating aluminum future pricing. For the electric car sector to maintain a steady supply chain, efficient production, and long-term growth, accurate forecasts are essential for policymakers to plan resource policies. The accuracy of ensemble learning models in predicting Aluminum prices was analyzed using Gene Expression programming and long short-term memory (LSTM) method. The analysis was based on monthly frequency spot settlement price data of Aluminum, copper, silver, and crude oil prices, as well as currency inflation rates of USA, China, and Peru. The study period spanned from January 1, 1994 to December 31, 2022, and also included the gross domestic product (GDP) of USA, China, and other metal minerals. Initially, we assess the level of multicollinearity between each chosen input parameter and Aluminum price volatility using Variance inflation factor-based multicollinearity. The primary innovation of this study lies in the creation of a highly precise model that utilizes the LSTM algorithm to estimate monthly Aluminum prices. This model serves as a revolutionary forecasting method. An extensive evaluation of various ensemble learning models reveals that XGBoost is the optimal model for accurately forecasting monthly Aluminum prices. The LSTM-based recurrent neural network model exhibited the lowest error, with a Mean Relative Error (MRE) ranging from 0.001 to 0.008, RMSE ranging from 54.527 to 136.044, and R2 ranging from 0.95 to 0.983. The findings demonstrated that the LSTM-based super learner models had superior performance compared to the CatBoost, LightBoost, Random Forest, XGBoost, and AdaBoost models, as evidenced by higher values of the determination coefficient (R2), value account for (VAF), and other 10 error analysis evaluators. Therefore, the utilization of an LSTM-based super learner model can serve as a dependable approach for forecasting future monthly Aluminum prices. In addition, this study introduces a logical mathematical model utilizing gene expression programming (GEP) to anticipate future Aluminum prices, which can be utilized by other researchers. Thus, we conclude that both the GEP and ensemble learning models, particularly the LSTM-based Super learner model, are appropriate for precise metal price predictions, which can benefit policymakers and assist in resource policy planning.

Predicting Engine Emissions Using Eco-Friendly Fuels for Sustainable Transportation

In recent years, increasing concerns about vehicle emissions' environmental and public health impacts have led to the desire to use eco-friendly fuels as alternatives to traditional fossil fuels. Biofuels, hydrogen, and electric power offer lower greenhouse gas emissions and improved air quality, resulting in their development and adoption globally. Predicting vehicle emissions using these fuels is crucial for assessing their environmental benefits. This study proposes using artificial neural networks (ANN), a machine learning technique, to accurately predict vehicle emissions associated with eco-friendly fuels across different compositions and engine speeds. The ANN model has a strong correlation between predicted and observed emissions values, indicating the effectiveness of its model. The research underscores the importance of adopting innovative approaches to address environmental challenges and promote sustainable transportation solutions. This study contributes to reducing the adverse effects of vehicle emissions on air quality and public health by assisting policymakers, car manufacturers, and city planners in making effective decisions. It promotes environmental sustainability by providing valuable insights into vehicle emissions prediction and guiding the development of eco-friendly fuels for a more efficient transportation system.

Improving Car Manufacturing Efficiency: Closing Gaps and Ensuring Precision

Manufacturing of an automobile consists of production and assembly of various individual components related to both on the interior and exterior of a vehicle. All these components are spatially related to each other hence making it a very complex procedure. Sometimes a variance in this spatial relationship can have a direct effect on both the appearance as well as the performance of the vehicle. As industry produces several thousands of units a day, minor defects like gaps and flushness between parts are generally neglected as it is very costly and time consuming to rectify them. This paper demonstrates the variance in each of the unit that is produced by taking five samples of same car built by the same manufacturer. This spatial variance maybe avoided by employing procedures like PPAP and other tools.

Fabrication of Intelligent Braking System

Abstract: The braking system was designed and applied on a car to make the driving process safety using embedded system design. Most of the accident occurs due to the delay of the driver to hit the brake, so in this project work braking system is developed such that when it is active it can apply brake depending upon the object sensed by the Proximity sensor and speed of vehicle. Currently, vehicles are often equipped with active safety systems to reduce the risk of accidents, many of which occur in the urban environments. The most popular include Antilock Braking Systems (ABS), Traction Control and Stability Control. All these systems employ different types of sensors to constantly monitor the conditions of the vehicle, and respond in an emergency situation. An intelligent mechatronic system includes an Proximity wave emitter provided on the front portion of a car producing and emitting Proximity waves frontward in a predetermined distance. An Proximity receiver is also placed on the front portion of the car operatively receiving a reflective Proximity wave signal. The reflected wave (detected pulse) gives the distance between the obstacle and the vehicle and RPM counter gives speed of vehicle. The microcontroller is used to control the braking of the vehicle based on the detection pulse information to push the brake pedal and apply brake to the car stupendously for safety purpose.

An Analytical Study of Customer Satisfaction to Maruti Suzuki

It is a true fact that if you are satisfied you recommended to others. Word of mouth and customer satisfaction play a very important role in determining market perception about an automobile. It is the market perception that determines the success of a company and so it is very important for the car manufacturers to measure the “willingness of existing users of a product to recommend it to others”. The same is a lot of interest to customers as well for it helps them make the purchase decision. A car is one of the most significant purchases that an Indian household makes and this project addresses the most important question that perplexes car manufacturers; “What makes the perfect car that influence willful purchase?” The project highlights the factors that influence the buying decision of a Consumer. The factor under consideration would be: Price Income of the consumer Features in the car Safety standard Warranty scheme Finance facility Post sale service Customer Relationship Management

Investigation of the Penetration Performance of the Radial Forging Process for Wrought Aluminium Alloy.

With the wide application potential of wrought aluminium alloy in aerospace, automobile and electronic products, high-quality aluminium bars prepared by the radial forging (RF) process have received extensive attention. Penetration performance refers to the depth of radial plastic deformation of forgings, which is the key factor in determining the quality of forging. In this work, the penetration performance of the radial forging process for 6063 wrought aluminium bars is investigated by simulation using FORGE software. The minimum reduction amount of the hammer is calculated based on the forging penetration theory of forging. The influence of process parameters including forging ratio (FR) and billet temperature on the effective stress and hammer load in the RF process are investigated. The RF-deformed billet is then produced with the optimal process parameters obtained from the simulation results. The average grain size of aluminium alloy semi-solid spherical material is used to evaluate the forging penetration. Simulation results showed that the effective strain at the edge and the centre of the RF-deformed billet gradually increases, but the increasing speed of the effective strain at the edge becomes low. The hammer load first decreases quickly and then gradually maintains stability by increasing the FR. It is found that low billet temperature and high FR should be selected as appropriate process parameters under the allowable tonnage range of RF equipment. Under an isothermal temperature of 630 °C and a sustaining time of 10 min, the difference in the average grain dimension between the edge and the centre positions of the starting extruded blank is 186.43 μm, while the difference in the average grain dimension between the edge and the centre positions of the RF-deformed blank is 15.09 μm. The improvement ratio of penetration performance for the RF-deformed blank is obtained as 91.19%.

Dependence of mechanical properties on the phase composition of intercritically annealed medium-Mn steel as the main competitor of high-strength DP steels

Depending on the alloy composition, intercritical annealing may provide different phases in the microstructure. For low-alloyed dual-phase (DP) steels it is usually ferrite and martensite, while for medium-Mn steels retained austenite is also formed. In a present study, a wide intercritical temperature range was applied to a 5% Mn steel to investigate possible microstructure combinations: ranging from fully ferritic, through ferritic-austenitic, multiphase, to fully martensitic, which were next investigated in terms of mechanical properties to clarify the behavior of this type of material. The obtained results together with technological issues and economic indicators were next compared to mechanical properties of typical DP steels in order to assess the possibility of replacing this material in car production. The mechanical properties were evaluated using static tensile and hardness tests. The phase composition was determined qualitatively and quantitatively using dilatometry, X-ray diffraction measurements, and electron backscatter diffraction analysis. The results suggest that both initial austenite and martensite fractions have a decisive influence on the yielding and elongation of steel; however, the tensile strength depends mainly on the sum of martensite initially present in the microstructure and the strain-induced martensite formed from the plastically deformed austenite regardless of the initial retained austenite—martensite ratio. The results indicate superior total elongation of medium-Mn steels reaching 30% compared to DP steels with a similar strength level in the range between 900 and 1400 MPa. However, medium-Mn steels could be a significant competitor to dual phase steels only if some technological problems like discontinuous yielding and serrations are significantly reduced.

Analysis of the local integration rate relevance as a performance indicator for the Moroccan automotive industry

Purpose The purpose of this paper is to define the local integration rate and how it is calculated to assess its relevance as a national performance indicator for the Moroccan automotive industry. Design/methodology/approach The research methodology first followed a systematic review approach through the analysis of published research articles and academic works. This study then followed a qualitative approach based on semi-structured interviews with various actors in the Moroccan automotive industry. Finally, the findings of this work were reinforced by a case study to analyze the supply chain of a locally produced vehicle. Findings The results indicate that the local integration rate as calculated today overestimates the performance of the automotive industry and does not systematically guarantee a significant creation of value added. Research limitations/implications Due to the confidentiality of the data in terms of turnover, payroll and purchase prices as well as the large number of suppliers in the different supply chains of the car manufacturer, the case study focused on only one of the six existing ecosystems. Originality/value On the basis of research work on the Moroccan automotive industry as well as interviews with various actors, the local integration rate is unanimously considered as a viable performance indicator. This study has not only led us to the method of calculating this rate by the Ministry of Industry but also demonstrated its limitations while proposing a new method of calculation to increase the value added.

Formation of New Technology in Automated Highway System in Peripheral Highway

There will be a dramatic shift in the transportation sector with the advent of autonomous highway systems, which might boost safety, efficiency, and sustainability. Modernizing India's transportation system may be as simple as installing state-of-the-art equipment along the Western Peripheral Highway. This abstract explores the potential impacts of autonomous highway systems on the Western Peripheral Highway, a vital piece of infrastructure. The development of autonomous highway systems is facilitated by a number of critical technologies, including artificial intelligence, sensor fusion, communication networks, and autonomous vehicles. These innovations enable cars to navigate themselves, exchange data with each other and roadside infrastructure, and make split-second decisions, all with the goal of enhancing traffic flow and roadway safety. By using high-definition mapping and precise localization systems, vehicle positioning and navigation are assured to be accurate, even in complex urban environments. The installation of Formation of new technology in Automated highway system in peripheral highway along the Western Peripheral Highway in India is widely anticipated as a potential solution to the country's dire transportation issues. Formation of new technology in Automated highway system in peripheral highway offer a realistic solution to increase mobility, decrease emissions, and alleviate congestion, all of which are contributing factors to the growing demand for efficient logistics networks brought about by rapid urbanization. Smart grid technology and renewable energy sources, when integrated into highway infrastructure, can make the transportation sector more resilient and eco-friendly. To make Formation of new technology in Automated highway system in peripheral highway a reality, many things and challenges must be taken into account. Make sure the communication protocols and car manufacturers are compatible for a smooth integration and operation. Urgent action is needed to address privacy and cybersecurity concerns in order to ensure the security of data and autonomous driving systems. The development of autonomous highway systems along India's Western Peripheral Highway finally presents a chance to drastically change transportation and urban mobility. It is possible for India to use cutting-edge technology and promote cooperation between the government, businesses, and universities to build highways that are safer, more efficient, and less harmful to the environment in the future. With sufficient investment, innovative thinking, and meticulous planning, Formation of new technology in Automated highway system in peripheral highway have the potential to transform urban landscapes and improve the quality of life for countless Americans.