Automobile Quality Research Articles

Enhancing ride comfort of semi-active suspension through collaboration control using dung beetle optimizer optimized Fuzzy PID controller

The enhancement of automobile quality is a significant area of modern research and development, with a focus on improving ride comfort and driving experience. This is achieved not only through structural improvements but also through the optimization of suspension control strategies. To enhance the ability of online real-time adjustment and overcome the limitations of fuzzy control, this study combines dung beetle optimizer (DBO), Fuzzy control, and Proportional-Integral-Derivative (PID) control to propose a reduced optimization complexity control method to improve MR damper control. The control parameters generated by fuzzy control are utilized as the initial values for DBO iteration to obtain the optimal solution, which is subsequently fed into the PID controller to regulate changes in the actuator’s magnetic field. Use MATLAB/Simulink to build a quarter semi-active suspension model with magnetorheological (MR) dampers for simulation analysis. Under sinusoidal and random disturbances, compared with the passive suspension, the vehicle acceleration of the Fuzzy-DBO-PID controller is reduced by 51%, 50.82%, 47.56% and 11.42%. Compared with Fuzzy-PID, the vehicle acceleration of Fuzzy-DBO-PID is reduced by 25.98%, 32.86%, 29.41%, and 7.19% on sinusoidal and random disturbances, which improves the ride comfort and verifies the effectiveness of the proposed control strategy.

Intelligent Vehicle Inspection Tool Design Based on Freeman Chain Code for Automatic Annotation of 3D Models

Autonomous vehicle are more and more widely used in daily life, and the requirements for their safety performance are higher and higher. As a tool for testing auto parts, intelligent inspection tools are crucial to the guarantee of automobile quality. However, traditional fixture design relies on manual drawing, which is inefficient and prone to errors. To solve this problem, this research uses Freeman chain code to determine the annotation object, uses case clustering method to annotate, and uses error back propagation algorithm to realize case knowledge classification learning, and designs intelligent vehicle inspection tool design technology based on Freeman chain code 3D automatic annotation method. The experimental results show that the geometric feature matching results are correct, and the difference in feature comparison results is significant, with a high accuracy rate. Meanwhile, the geometric similarity annotation method has a high accuracy rate, taking only 3 minutes to complete the annotation, which is 7 minutes longer than traditional manual annotation. The error backpropagation algorithm can accurately achieve feature classification, and the design time of size chain inspection tool deformation design is reduced by 214 minutes compared to manual reverse deformation design, significantly improving design efficiency. In summary, the proposed design method for automotive inspection tools can achieve automatic model annotation, improve design efficiency, and reduce design time.

Key Components of Brand Image Regarding Automobile Quality and Service

Key Components of Brand Image Regarding Automobile Quality and Service

Supply Base Geographical Complexity and Quality Risks: Evidence From the Chinese Automobile Industry

Supply base geographical complexity has important implications for supply chain risk and performance, but less is known about its relationship with product quality risks. Drawing on the transaction cost economics and social network theory, we argue that supply base geographical complexity increases monitoring and coordination challenges, thus leading to higher product quality risks. However, vertical integration and high network centrality can mitigate this impact by facilitating trust and information sharing. We test our hypotheses using Chinese automobile industry data collected from multiple sources and find that supply base geographical complexity is positively related to automobile quality risks, but this relationship is weakened by the network centrality asymmetry between a buyer and its suppliers. This study extends our understanding of the antecedents of product quality risks and the interaction of supply network structural characteristics.

Research on the Sound Quality Evaluation Method Based on Artificial Neural Network

For the improvement of the traditional evaluation effect of the automobile sound quality, an evaluation model of automobile sound quality is constructed based on BP neural network. The first is to introduce the basic principle of the BP neural network in detail. The second is to use the MGC parameters to establish the vehicle interior sound conversion model. The converted sound characteristic parameters are taken into the WORLD model to synthesize the new sound signals. Furthermore, the wavelet decomposition method is used to remove noise from the synthesized sound signals. Finally, a sound evaluation model based on BP neural network is established. The sound quality of automobiles can be better evaluated by carrying out the ABX test and MOS test in the field of sound conversion. For the newly synthesized sound signal and the target sound signal, it can be seen that the newly synthesized sound signal is more inclined to the target sound signal, and the sound quality is better. In addition, the sound quality is tested through loudness, roughness, sharpness, and level A in the field of sound quality evaluation. The final results show that the quality of newly synthesized sound is better, and the average errors of sound signals meet the sound standard. Therefore, the constructed sound conversion model and the sound evaluation model are feasible and effective.

The Value of a Technical Service Bulletin Index for the Consumer

Automobile Technical Service Bulletin Index represents additional information pertaining on the quality of a vehicle. Currently, there is no way for the consumer to evaluate this large amount of information when buying a new car. A Technical Service Bulletin Index is developed as an aid to the consumer to better understand the quality issues related to thirty different car models. When compared to two major existing surveys, the J.D. Power Initial Quality Study and the J.D. Power Vehicle Dependability Study, the Technical Service Bulletin Index proved that it provides new, useful information about automobile quality for consumers to use when making the decision of their next automobile purchase.

The Research of the Automobile Industry in Wuhan on the Context of New Technology, New Energy and Intelligentization

Nowadays, China’s automobile manufacturing industry has developed rapidly and the overall quality has been steadily improved. After several years of rapid development, with the continuous progress of technology, new energy and intelligent technology began to popularize. However, the production and sales of self-owned brand passenger cars have shrunk greatly due to the decline of overall sales of passenger cars. As the headquarters of Dongfeng Motor Group, Wuhan has certain cluster advantages in R&D of self-owned brand vehicles, but it has been in a loss state in recent years, and there is an obvious gap between Wuhan and the first-line self-owned brands. Therefore, it is worth discussing how to seize the development opportunity, promote the quality of its brand and become a first-line brand. This paper analyses the development status, challenges, and bottlenecks of Wuhan self-owned automobile brand quality improvement under the development background of new technology, new energy and intelligent, and puts forward the strategy of Wuhan self-owned automobile brand quality improvement. This paper suggests that we should strictly implement the automobile quality regulations, establish the quality assurance and traceability system of self-owned brands, increase the support of new energy sources for self-owned brands and the development of intelligent car service, and build a quality basic technology sharing platform, so as to achieve the purpose of improving the quality of Wuhan’s self-owned automobile brands.

Deep CNN transferred from VAE and GAN for classifying irritating noise in automobile

Noise from automobiles, such as buzzing, squeaking, and rattling (BSR) noises, is a key factor in automobile quality assessment. It is necessary to classify these noises for appropriate handling and prevention. Although many researchers have conducted studies to classify noise, they suffer from several problems: difficulty in extracting appropriate features, insufficient data to train a classifier, and weak robustness to surrounding noise. This paper proposes a method called latent semantic controlling generative adversarial networks (LSC-GAN) to solve these problems. To capture the features of data, a variational autoencoder (VAE), an autoencoder with approximate inference in a latent Gaussian model, learns the data representation by projecting them into the latent space according to their features and reconstructing the projected data. Because the generator and the discriminator of the LSC-GAN are trained simultaneously, the capacity to extract the characteristics of the data is improved and a knowledge space of classifiable data is also expanded with insufficient data. While data are generated by the generator, the encoder projects them back to the latent space according to their characteristics to advance the ability to extract features. Finally, the encoder is trained to the classifier, which is trained to classify BSR noises. The proposed classifier outperforms other models and achieves an accuracy of 96.68%. We confirm using a confusion matrix that the proposed model classifies the types of insufficient class better than other models. Our proposed model classifies data with accuracy of 94.68%, even if the data contains surrounding noise, which means it is more robust to BSR with surrounding noise than other models.

Quality Estimation Method of Heavy Vehicle Based on Speed Change

The heavy-duty vehicle has a wide range of mass changes from no-load to full-load, which affects the shift control of the heavy-duty vehicle transmission. Therefore, the quality of heavy vehicles needs to be identified. The traditional taxiing method needs to know the road rolling resistance coefficient and air resistance coefficient. Acceleration sensor-based automobile quality identification methods require additional sensors on the car, which increases the cost of the car. In this study, based on the principle of function conversion and vehicle longitudinal dynamics, a method for estimating the mass of a heavy vehicle based on changes in vehicle speed is proposed, in the case of unknown vehicle characteristic parameters. In this study, after calculating the air resistance coefficient of the vehicle by the coasting method when the vehicle is under no load, the rolling resistance coefficient of the vehicle is decoupled based on the functional principle and the least square method during the flat road taxiing phase of the heavy vehicle. Based on this, the vehicle longitudinal dynamics model is established, and the mass of the heavy vehicle is estimated by fitting the vehicle speed with the Newton’s global algorithm. The research results show that the algorithm of this research can calculate the rolling resistance coefficient of the vehicle in real-time during the taxiing phase of the vehicle, with a calculation accuracy of more than 97%, and the online real-time estimation of the vehicle quality, with an accuracy of more than 95%. The algorithm of this study provides a new solution for online estimation of heavy vehicle driving quality, and can be used for automatic shift control of heavy vehicles.

Informal Quality Data Analysis via Sentimental analysis and Word2vec method

Purpose: This study analyzes automobile quality review data to develop alternative analytical method of informal data. Existing methods to analyze informal data are based mainly on the frequency of informal data, however, this research tries to use correlation information of each informal data. Method: After sentimental analysis to acquire the user information for automobile products, three classification methods, that is, naive Bayes, random forest, and support vector machine, were employed to accurately classify the informal user opinions with respect to automobile qualities. Additionally, Word2vec was applied to discover correlated information about informal data. Result: As applicative results of three classification methods, random forest method shows most effective results compared to the other classification methods. Word2vec method manages to discover closest relevant data with automobile components. Conclusion: The proposed method shows its effectiveness in terms of accuracy and sensitivity on the analysis of informal quality data, however, only two sentiments (positive or negative) can be categorized due to human errors. Further studies are required to derive more sentiments to accurately classify informal quality data. Word2vec method also shows comparative results to discover the relevance of components precisely.

Correlation analysis between subjective and objective evaluation data of automobile horn sound quality

Correlation analysis of subjective and objective evaluation for automobile sound quality is an important topic in automobile technology fields. Considering the theoretical characteristics of grey system method and neural network theory, grey relational analysis was applied to analyse the contributions of the variables of objective evaluation to subjective evaluation using the existing subjective and objective evaluation data of automobile horn sound quality. Then the main objective variables affecting the subjective feeling were determined, which include sound pressure level, A-weighted sound pressure level and sharpness. Back-propagation neural network model was designed and established as a quantitative expression between subjective and objective evaluation data. The simulation results of neural network model accorded with the original value of the subjective evaluation data very well, which illustrated the reliability of this method.

Evolution of product quality in European, Japanese and US automotive firms: An exploratory longitudinal analysis

For years we have been hearing that US automobile manufacturers have been losing market share to their Japanese rivals who are reputed to make better quality vehicles. Most such reports are based on the initial quality surveys on new automobiles. In this paper we address two exploratory questions: (1) how does the quality of an automobile change with its age, and, (2) can firm level variables help explain differences quality. To answer these questions, we collected Consumer Reports’ reliability ratings on approximately 300 automobile models made by European, Japanese and US automotive firms during the 1998–2007; and approximately 240 models made by these firms over period of 2008–2015. For both periods we found that not only do automobiles made by Japanese firms have higher initial quality, but, as automobiles get older the difference in the product quality between Japanese versus European and US firms increases. We also found that the more generalist a European or US automobile firm, i.e., the wider is the firm׳s product offering in the marketplace, the lower its overall automobile quality during the 1998–2007 period. Conversely, Japanese generalist firms were found to have higher quality than specialist firms over the same period. The result is partly explained by the fact that Japanese firms have taken a different path to broadening their product variety – they have ensured a high level of quality of their initial offerings before entering newer market segments. The rate of reliability decline was found to be slower for all firms, and the differences in reliability across the 3 groups of firms were much less pronounced during the 2008–2015 period. This improvement may be as result of restructuring done by US automobile firms.

The Dreaming-Sharing-Excitement Model of K-Management and K-Entrepreneurship

1960년대 세계에서 가장 가난한 국가의 하나였던 한국이 가장 빠르게 경제적으로 성장한 국가로 세계의 주목을 받고 있다. 지난 60년간 경제성장의 주역이었던 한국 기업들의 경영성과를 어떻게 설명할 것인가? 이것이 본 연구의 배경이다. 한국 기업들은 흔히 스피드경영, 신바람경영, 파괴적 혁신, 창조경영 등을 K-경영의 특징으로 한다. 그러나 이들은 조직구성원들의 행동의 표면적 양상일 뿐이다. 그러면 이러한 양상을 만들어내는 원인변수와 메커니즘들은 무엇일까? 본 연구는 사회심리학적 접근을 통해 한국조직원의 행동을 끌어내는 ‘꿈’과 ‘흥’을 중심으로 K-경영모델을 설계, 제시하고, 이 모델에 근거하여 현대자동차의 글로벌 성장 과정 사례를 분석해 보고자 한다. K-경영모델은 위기 속에서 꿈을 가지고 미래를 향해 지속적으로 도전해가는 정신인 K-Entrepreneurship을 바탕으로 하고 있다. 본 연구의 사례 대상 기업인 현대자동차는 1998년 IMF금융위기이후 경영위기의 상황 속에서 1999년 미국에서의 10-10선언(10만마일 10년 보증 프로그램)을 통해 조직의 역량을 결집한 결과, 2004년 넘어설 수 없는 경쟁자처럼 보였던 도요타의 품질을 극복하고 GT5(Global Top 5)의 목표를 향해 도전하는 과정을 보여주고 있다. 2004년 저가차량만으로 인식되었던 현대자동차의 소나타가 경쟁차종인 캠리, 어코드를 밀어내고 JD 파워의 세그먼트 품질(IQS) 1위를 차지했을 당시 Automotive News(April 28, 2004)는 사람이 개를 물다(Man bites dog)라는 표현으로 현대차의 빠른 품질개선에 대한 놀라움을 표했다. 이후에도 디자인혁명, 전장화 등을 통해 현대자동차는 현재의 상태에 안주하려는 현재의 저주현상을 극복하고 창조성, 시장성, 생산성의 3대 지속성장 요인을 높여가고 있다. 본 연구는 ‘꿈-흥’(DSE)모델을 바탕으로 현대자동차의 창조성, 시장성, 생산성의 변화과정을 종단적으로 보여주면서 기업진화의 과정을 설명하고 있다.BR 이러한 접근은 1980년대 일본기업의 경쟁우위를 공동체주의를 중심으로 분석하는 윌리엄 오우치(William Ouchi)의 Z이론(Theory Z)이나, 카이젠 중심의 도요타 방식 등 일본식경영(Japanese Management) 연구와 비교될 수 있다.

Review of J. D. Power Quality Measurement of U. S. and Japanese Automotive Industry

J. D. Power and Associates (JDP) conducts customer surveys and reports information on automobile quality, reliability, safety, satisfaction and buyer behavior. The Initial Quality Study (IQS) by JDP provides feedback on the quality of new vehicles during the first 90 days of ownership. This paper evaluates the quality measurements of IQS and its economic impact on the sales performance of major U.S. automakers (GM, Ford, and Chrysler) and Japanese automakers (Toyota, Honda, and Nissan) between 2001 and 2010. The following research questions are addressed: (1) Does IQS have significant impact on the customers’ purchasing behavior during the period of study? (2) Who benefits more from IQS, U.S. or Japanese automakers? (3) How can the quality information of IQS be measured and evaluated? In order to address the first two questions, the event study methodology is used to analyze the impact the IQS surveys on U.S. market sales. IQS resulted in the positive response to the market (or increasing market share) for Japanese automakers with the opposite result for U.S. auto manufacturers. To address the third question, two quality measures (IQS score and event type, i.e., positive or negative event) are defined and analyzed. The analysis shows that there is a positive relationship between IQS score and market share response. Similarly, positive news had a significant effect on the market response of IQS reports, while the effect of negative news was not significant.

The Value of Automobile Surveys in Reducing the Buyer’s Risk

Consumers use quality surveys to reduce risk in purchasing a car. The J. D. Power's initial quality survey of automobile buyers reports the number of problems found in the first 90 days of ownership. It is important that this information be clear and concise for the public to understand. In 2006, the surveys were changed to combine two measures of quality, number of defects and design problems, into a single number. In prior years, only the number of defects was used. The survey design change combined with issues related to the methodology in aggregating values leads to confusion and inconsistencies over time as the difference between cars becomes insignificant. The conclusion recommends changes to correct these problems. INTRODUCTION Quality survey companies follow the basic information system's process of collecting the data from the assessment documents, creating a database of the information, analyzing the data, and disseminating the probability of a defect or the number of problems per product (O'Brien & Marakas, 2009). This paper examines the information process of a survey company and identifies specific problems that may lead to incorrect conclusions. These issues result from the design of survey, computational errors, and lack of continuity in the values over time. The example used in this analysis is taken from the automobile industry. Each year, numerous automobile quality surveys are reported by several information services. Driven by the results of these studies, car manufactures have substantially improved vehicle quality. The results from the J. D. Power's Initial Quality Surveys (Tews & Perryman, 2008) provide consumers with information on the awards for best car in a segment. These awards are used extensively in advertising and influence purchasing decisions. Before purchasing a car, consumers review the available literature on the quality of a product to minimize their risk of purchasing a defective car. Collecting all this information reduces the risk of making a decision with partial or imperfect information (Heiser & Render, 2008). The analysis of the survey process focuses on correctly calculating values and the consistency in the final results. First, the J.D. Power's methodology that is used to aggregate the results of individual models into nameplates, manufacturers and country is examined. Next, with the number of problems becoming statistically insignificant, a qualitative measure is added to the number of defects, a quantitative measure, resulting in a confusing and inconsistent set of values for the new surveys. Throughout the paper, suggestions for improvement are made. The conclusion recommends changes in the survey, a new methodology for aggregating data, and separate surveys for qualitative and quantitative measures to improve the information content

A Case Study of Applying SOM in Market Segmentation of Automobile Insurance Customers

Over the last decade, it has been observed that automobile insurer organizations are being tasked with a new challenge characterized by increased competition, increased requirements of automobile insurance quality and an increasing emphasis on time-to-market. Furthermore, knowledge regarding what customers think, what they want, and how to serve them is quite useful for insurance organization wishing to generate suitable strategies in competitive markets.

다구치 방법과 근사최적설계를 이용한 자동차 연료탱크의 연료 넘침 방지 시스템 설계

자동차 연료탱크는 크게 본체와 본체에 조립되는 부품들로 구성되어 있다. 본체에는 차량 주행시에 연료탱크에서 발생되는 증발가스를 배출하고, 연료가 외부로 유출되는 것을 방지하기 위한 여러 밸브들이 조립되어 있다. 하지만 이러한 밸브들은 연료 넘침에 주된 원인으로 알려져 있음에도 불구하고 현재 증발가스의 배출과 기구적인 위치만 고려하여 설계되고 있다. 따라서 본 연구에서는 밸브들의 기존기능을 유지하면서 연료 넘침을 최소화 시키기 위해 근사최적설계를 적용하였고, 다구치방법을 통해 실제 실험에서 근사최적설계의 유용성을 보였다. 결과적으로 최적화된 밸브 위치를 통해 개발기간과 비용을 절감하였고, 연료 넘침 최소화를 통해 자동차의 신뢰성을 향상시켰다.

Shared Roadway Implementation Guidance

Shared roadways have automobiles and bicycles operating in the same traveled way, which may negatively affect traffic operations; there is limited guidance on appropriate shared roadway implementation. To provide guidance on shared roadway implementation, this paper uses microsimulation models and a sensitivity analysis to evaluate automobile quality of service on shared roadways. After the sensitivity analysis, automobile quality of service is compared to bicycle quality of service on shared roadways. Using the results of the sensitivity analysis and comparison, guidance is provided on the implementation of shared roadways. This study finds that outside lane width and bicycle volume affect automobile quality of service on shared roadways. Additionally, higher values for unsignalized access points per kilometer (per mile), heavy vehicle percent, and signalized intersection crossing distance result in bicycle quality of service being less than automobile quality of service. Using this study’s findings, shared roadway implementation guidance is provided for four-lane divided urban street segments. Future research should develop shared roadway implementation guidance using microsimulation models calibrated to observed data.

The Application of 7 Diamond Process in the Automobile Quality Control

With the rapid development of domestic automobile industry, product quality issues are also increasingly prominent. 7 Diamond Process is one of analysis method and tool used for the automotive industry to solve quality problems and difficult problems, it is a standard seven-step method used to promote problem-solving. Moreover this paper introduces the concept and content of 7 Diamond Process, by giving a practical example, the detailed steps of 7 Diamond Process applied in automobile quality problem analysis are described. It will become an effective tool to improve the quality level of automotive products.

자동차 인테리어 모듈의 BSR 소음과 음질 특성 연구

Among the various elements affecting a customer's evaluation of automobile quality, buzz, squeak and rattle(BSR) have been considered to be major factors. In most vehicle manufacturers, the BSR problems are solved by find-fix method with the vehicle road test, mainly due to various excitation sources, complex generation mechanism and subjective response. To systematically tackle the BSR problems in early stage of the vehicle development cycle, these difficulties should be resolved. The aim of the present paper is to characterize the sound quality property of BSR noise that can be used to assess the subjective responses to BSR. The four sound metrics from Zwicker's sound quality parameter are computed for the signals recorded for eight BSR noise source regions localized by using the acoustic-field visualized results. Then, the jury test of BSR noise are performed. On the basis of the computed sound metrics and jury test result is evaluated to represent the harshness of BSR noise. It is expected that the developed BSR measuring system and sound quality properties can be used to reduce the automotive interior BSR noise in terms of subjective levels as well as objective levels.