Auto Parts Research Articles

The structure and dynamics of the auto parts industry: Product space and complexity perspectives

Economic structures are strong determinants of diversification, growth, innovation, inequality, and many other socio-economic outcomes; however, structural change's effect on specific industries remains unexplored. This study investigates Japan's automotive components industry, analyzing its productive structure (the auto parts product space) and structural change process. We develop exploratory and econometric analyses that unify the measures of product relatedness and complexity. The firm-level data analysis shows that specific structural properties in international and domestic economies also exist in the automobile industry. This fractal structure implies that common principles and regularities underlie the formation of productive structures, notwithstanding the economies’ size, maturity, and industrial scope differences. The exploratory and econometric analyses indicate that the events of a product's appearance are not random but are significantly contingent on the network topology of the product space. Furthermore, network topology significantly impacts the development of complex products with sophisticated capabilities.

Marketing strategy, competitive advantage and business success among SME auto parts: Basis for business agility framework

Marketing strategy, competitive advantage and business success among SME auto parts: Basis for business agility framework

An optimisation of the internal roller burnishing process for magnesium composites using Taguchi Multi objective optimization method

Machining Metal Matrix Composites with conventional metal removal causes particle debonding and crack propagation. This paper has given enhancing results for magnesium silicon carbide Metal Matrix Composite using an internal roller burnishing process. The optimal process parameters are obtained using a full factorial design and Taguchi Multi Response optimization. The optimized parameters include a spindle speed of 500 rpm, a feed rate of 0.5 mm/rev, and a stock allowance of 0.03 mm. The resulting surface characteristics comprise a surface roughness of 0.1555 µm, an out of roundness of 0.0595 mm, and a surface hardness of 66.9 HV. Scanning electron and atomic force microscope, images analyze the surface topology. Auto parts like transfer case and steering components can use burnished components.

Pesky Stock Keeping Unit (SKU) demand forecasting model for American Auto Parts Retailer

Pesky Stock Keeping Unit (SKU) demand forecasting model for American Auto Parts Retailer

The Use of New Technologies in the Auto Parts Industry.

The Use of New Technologies in the Auto Parts Industry.

A Study on the Relationship Between Quality Monitoring Technology Innovation in Auto Parts Enterprises and National Interest

This paper aims to explore the relationship between the innovation of quality monitoring technology in auto parts enterprises and national interests. By providing an overview of the development history, current main types, and characteristics of quality monitoring technology, as well as the driving forces and trends of technological innovation, it elaborates on the positive impact of quality monitoring technology innovation on auto parts enterprises, including improving product quality and reliability, enhancing production efficiency, reducing costs, and strengthening market competitiveness. At the same time, by analyzing typical enterprise cases, it specifically demonstrates how technological innovation promotes the realization of national interests, such as promoting industrial upgrading, ensuring economic security, and enhancing international competitiveness. Finally, the research concludes and puts forward suggestions and prospects for future development, emphasizing that the government, enterprises, and all sectors of society should work together to promote the innovation of quality monitoring technology in China’s auto parts enterprises to a new level.

Analysis of the Effectiveness and Efficiency of the Procurement Process in the Procurement Department at PT. Bakrie Auto Parts

Every company is inseparable from the procurement of goods or services. With the procurement of goods or services being one of the factors that support the operational activities of a company and to maintain the survival of the company, especially companies engaged in the manufacturing industry. One of them PT Bakrie Auto parts also procure goods run by the procurement department, in the process of procuring goods PT Bakrie Auto parts is utilizing technological advances by conducting electronic procurement which aims to increase the effectiveness and efficiency of procurement. The purpose of this research is to determine the effectiveness and efficiency of the procurement process at PT Bakrie Auto parts. The data collection method in this study is the interview method and direct observation, with the analysis method in the form of quantitative non statistical analysis, namely the method of analyzing data without using statistical analysis. The implementation of the procurement of goods carried out by PT Bakrie Auto parts has been running effectively with an assessment of four indicators, namely: indicators of increasing transparency and accountability, indicators of supporting the monitoring process, indicators of meeting the needs of real team information access, and indicators of achieving goals. In addition, the implementation of procurement carried out by PT Bakrie Auto parts has also been running efficiently based on the results of the assessment of the use of the expenditure budget.

Outsourcing in the automotive industry of the Kyrgyz Republic: Development prospects

The study was conducted to assess the prospects for the development of outsourcing in the automotive industry of the Kyrgyz Republic and its impact on productivity, economic efficiency, and innovation in the industry. The study used statistical analysis methods to process data on production and employment from official sources, a comparative analysis of successful examples of international cooperation, and methods for assessing risks associated with outsourcing. As a result of the study, it was established that outsourcing in the automotive industry of the Kyrgyz Republic helps to reduce operating costs and increase production efficiency. It was also determined that the transfer of non-core functions to external contractors allows companies to focus on key processes, which accelerates the introduction of innovations. It was also confirmed that outsourcing helps to attract international companies, stimulating economic growth, and creating new jobs. However, the risk of loss of control over the quality and timing of tasks, which requires the development of effective mechanisms for interaction with contractors to minimise possible negative consequences, is identified. The study showed that the successful implementation of outsourcing requires the active participation of government agencies to create a supportive regulatory framework and incentives to attract investment. The results demonstrated that outsourcing contributes to the development of related industries such as auto parts manufacturing and IT services, which in turn stimulates the growth of the local labour market. In the long term, the use of outsourcing can become a key factor in increasing the competitiveness of the country's automotive industry in the international arena. The study provided valuable data on the impact of outsourcing on the efficiency and innovative development of the automotive industry, which can serve as a basis for developing strategies to optimise production processes and improve economic performance in this industries

Why do multinational enterprises in the auto parts industry set up in Morocco?

Why do multinational enterprises in the auto parts industry set up in Morocco?

Research on the intelligent fatigue detection of metal components in vehicles

With the acceleration of transportation speed, heavy loading of trucks has higher requirements for the quality of wheel axles, and the detection of wheel axles on trucks has become a key focus in corrective maintenance. The automotive industry requires timely detection of vehicle components. Nondestructive testing (NDT) technology provides a method of detecting and analyzing physical quantities on the internal surface of an object without causing damage. It can determine the presence of defects or abnormal conditions. The application of nondestructive testing (NDT) is essential in the automotive industry to guarantee the safety and dependability of vehicles. This article provides an overview of the principles and applications of phased array ultrasound imaging and eddy current testing, focusing on intelligent monitoring solutions for axles. This article proposes an enhanced intelligent monitoring approach that utilizes existing detection methodologies to provide vehicle owners with real-time feedback regarding the fatigue strength of individual automotive parts. This approach aims to prompt the replacement of auto parts when the fatigue trend approaches predetermined warning thresholds.

Strategic packaging in the supply chain: Benefits and challenges

The packaging must have the goodness of being strategic, a fundamental characteristic to be related to the proper maintenance of the good or product. The objective of the research is to analyze the economic effects that low-quality packaging has on the auto parts industry of the automotive industry in Guanajuato, Mexico, compared to packaging that has a good design and is constantly improving. 190 auto parts companies participated, there was a margin of error of 1.59% with a confidence level of 95%. Information was collected on pieces discarded due to poor packaging quality over a two-year period, 2022 and 2023. For the analysis, the statistical model of moving averages and dispersion measures under the standard deviation was used. The results were significant identifying inefficient packaging in the raw material and its economic impact on the organization. As well as well-designed packaging or packaging that undergoes continuous improvement, it implied significant cost reductions for the company.

Supply chain integration, competitive strategies and firm performance

Purpose This study aims to examine the interaction between different types of supply chain integration (SCI) and competitive strategies on firm performance. Design/methodology/approach The research method is quantitative. The study develops a structured model and a set of hypotheses based on the related theories. Empirical data is collected in a cross-sectional manner using an online survey to test the model and its hypotheses. The survey comprised standard scales to measure study variables. The scales had high reliability and validity and were commonly used in the literature. The study was conducted on Iranian firms working in steel and auto parts industries. Based on official reports, a total of 305 active companies were found in these two industries. Due to the small population size, all companies in the two industries were contacted for participation. Overall, 84 firms completed the survey. To test the research hypotheses, the authors used hierarchical regression analyses using SPSS 27 software. Findings Results showed that internal integration improves financial performance when firms follow a cost leadership strategy. Differentiation strategy and process integration interact positively and improve operational performance. Type of industry had no significant effect. The results add to the SCI literature by showing that a match between competitive strategy and integration type can influence both operational and financial performance. In total, firms should focus on the appropriate dimension of SCI based on their competitive strategy to improve the performance of the firm. Originality/value The impact of competitive strategy as a moderator on the SCI-performance relationship has not been widely addressed in the literature. In one study, Huo et al. (2014) investigated this relationship using data from 604 manufacturing companies in China. The results provided support for financial performance but not for operational performance. However, the influence of competitive strategies on the SCI performance may vary in different countries and contexts with dissimilar environmental, social and cultural characteristics. As several supply chain scholars have argued, understanding contextual conditions that influence the effect of best practices such as SCI on performance are critical

Optimization of the VARTM Process for Prototyping a Bumper Using Hybrid Composite Materials

To provide an alternative for manufacturing auto parts using composite materials, the Vacuum Assisted Resin Transfer Molding (VARTM) process was utilized to prototype the bumper for the Chevrolet Aveo vehicle. This technique emerges as an alternative for composite material manufacturing, allowing for rapid and high-quality production of advanced composites. In this study, a hybrid composite material reinforced with fiberglass, cabuya fiber, IN2 epoxy resin, an infusion mesh, peel ply, and a vacuum bag was employed. To optimize the VARTM process in bumper prototyping, several simulations of resin flow were conducted with different locations of resin injection and vacuum entry points. Autodesk Moldflow Insight software facilitated the modification and addition of resin injection points to observe the flow evolution, thus determining the filling time for each proposed design. Six different designs were applied for the bumper mold filling. The proposed linear flow design reduced the total filling time of the bumper mold by 81.56% compared to the other five designs analyzed. The result of the numerical simulation was validated through the experimental process, where a high degree of concordance in the mold filling time was achieved between both methods.

Optimizing coolant oil wastewater treatment via modified air-Fenton process with bimetallic particles from auto parts manufacturing waste

This study evaluated the efficiency of aluminium (Al)/iron (Fe) bimetallic particles, produced from waste by-products of auto parts manufacturing—namely, aluminum dross (AD) and shot blast (SB)—in removing chemical oxygen demand (COD) and total organic carbon (TOC) from coolant oil wastewater originating from an auto parts manufacturer. Two different molar ratios of ADSB bimetallic particles, namely, 1:1 (ADSB1) and 2:1 (ADSB2), were investigated for their characteristics and applied in the modified air-Fenton (MAF) process which enhances the traditional Fenton method by utilizing ADSB bimetallic particles instead of Fe0 and Al0, and by incorporating aeration to stimulate the reaction. The wastewater contained an initial COD ranging from 60,000 to 120,000 mg L–1 (at 3–5 % v/v) and a TOC ranging from 10,000 to 40,000 mg L−1. The experimental design included varying reaction times, pH values, quantities of bimetallic particles, airflow rates, and wastewater concentrations were performed using the Minitab-19 software package. X-ray fluorescence (XRF) analysis revealed that the bimetallic particles have SiO2 content ranging from 39.69 % to 56.03 %, Fe2O3 ranging from 20.52 % to 30.90 % and Al2O3 ranging from 16.51 % to 16.66 %, with surface areas varying between 5 and 6 m2 g−1. As a result of XRF analysis, SiO2 can be contaminated by the sand molds used in the manufacturing process of products. Notably, ADSB1 exhibited impressive removal efficiencies of 98.70 % and 98.50 % for COD and TOC, respectively, at 0.6 g, pH 3, airflow rate of 1.5 L min–1, and reaction time of 105 min. Conversely, ADSB2 achieved removal efficiencies of 96.30 % and 98.43 % for COD and TOC, respectively, at 0.2 g, pH 9, airflow rate of 2.0 L min–1, and reaction time of 180 min. Pareto charts and 3D surface plots derived from the data showed the number of bimetallic particles as the most influential factor, followed by the initial pH. The MAF process significantly extends the pH range under diverse conditions by incorporating ADSB particles and reduces the reliance on traditional chemicals like hydrogen peroxide. This research presents a promising advancement in wastewater treatment technology.

Revolutionizing Land-Based Vehicle Parts Management: Basis for a Unified Digital Platform for Auto Parts Information Systems

The study provides the basis for a much-needed digital platform one that is consumer-friendly by examining current practices, pain points, and stakeholder requirements. This marketplace aims to aggregate the information of all of the autoparts dealers, suppliers, distributors, and manufacturers centrally for collaboration. Our goal is to reduce TCO and time associated with data access/wait times for real-time insights around inventory management, supply chain visibility, and actionable insights. This study is designed to save the face of the land and rarity-based car parts management at the end, foster efficiency in the automotive industry while taking on sustainability. To be a highly effective, secure and scalable "Autohub System" the design is implemented using several strategies and tactics in database domain.In order to reduce redundancy, this entails using a Relational Database Management System (RDBMS) such as MySQL and implementing strategies such table definition, relationship building, and normalization. Indexing helps enhance efficiency while looking for information and to model the autoparts ecosystem we use Entity-Relationship Diagrams (ERD). For stronger security against attacks and availability of data some methods used are concurrency control, adequate back-up and recovery procedures, and encryption of data. Performance tuning and considering scalability are other topics as they focus on the efficiency of work and further increase in the company’s possibilities, whereas data auditing gives them accountability. Altogether these strategies can accurately set the database to cater for the goals that the autoparts management system has to accomplish. It’s the exact same concept with the Autohub System which revolutionizes the conventional autoparts management sector by producing IoT and predictive maintenance, making operations smoother while eliminating waste. It is beneficial for many businesses as they experience reduced costs, less downtime, and an overall increase in productivity. This is true because the indicated system enhances earth-friendly causes since the automotive industry it fosters is more competitive because of worldwide cooperation. The newly introduced system, the Autohub System, has posed a major change in the ways businesses within the autoparts management industry operate today. This is achieved through offering real-time information, supplier control and a clear and user-friendly front-end in order to ensure that it facilitates the tends, procurement and cooperation. Through sustained supplier dynamics, buy order optimization, and analytical proficiency, decision making becomes enhanced tremendously. The long-term feasibility is guaranteed by the very fact of the opportunity to expand on it and adapt to new needs. This technology takes autoparts management to a new level because it has an overall positive impact on the functions of decreasing downtime, improving supplier interaction, and improving the supply chain. Summing up, The Model T exemplifies the milestone in progress toward sustainability and efficiency that shapes the future of the automobile industry.

Sustainable supply chain decision-making in the automotive industry: A data-driven approach

The auto parts manufacturing sector faces multifaceted challenges ranging from production planning to sustainability imperatives, necessitating innovative solutions. This study presents an integrated data-driven approach tailored to address these challenges. Leveraging advanced AI techniques, including Convolutional and Recurrent Neural Networks optimized with the Moth-flame Optimization Algorithm (MFO), we accurately predict demand quantities for automotive components. Through empirical validation with Iranian auto parts manufacturers, our model achieves an impressive accuracy rate of over 90 %. Subsequently, Data Envelopment Analysis (DEA) evaluates suppliers not only based on demand quantities but also on their social, economic, and environmental impacts, with a resulting average efficiency score of 0.75. The Best-Worst Method (BWM) further refines supplier selection, leading to the identification of top-performing suppliers with an average score of 0.8. This comprehensive approach enables auto parts manufacturers to optimize production planning processes while aligning with sustainable development goals. The successful application of our model underscores the transformative potential of integrating business analytics and AI in the automotive industry towards sustainability.

Disposal of spent oil into soils around auto parts markets impacts heavy metal concentrations and poses a potential ecological risk

Nigeria is facing the problem of soil degradation as a result of continuous deposition of spent oil in the soil. The physiochemical properties, including heavy metals concentrations, of spent oil contaminated soils and adjacent control soils were investigated at 0–15 and 15–30 cm depths at Ladipo and Berger auto-mobile Markets in Lagos, southwest Nigeria. The soils were collected in triplicate and analyzed in a 2 (location) * 2 (study site) * 2 (soil depth) factorial experiment. The results showed a uniform soil texture in both study sites and at both soil depths, with loamy sand at Ladipo and sandy loam at Berger. Bulk density was significantly decreased, while the total porosity (46.44%), organic C (21.79 g kg− 1), available P (16.48 mg kg− 1), Na+ (0.72 cmolc kg− 1) and K+ (0.81 cmolc kg− 1) increased in the contaminated site compared to the control site. Soil pH was higher at Ladipo (8.4) than at Berger (7.4). However, the soil pH and available P concentration decreased in the contaminated soil compared to the control at both locations, resulting in a decrease in available P concentration of more than 300% and 100% at Ladipo and Berger, respectively. At the Ladipo location, the concentration of Ca2+ was higher in the control than in the contaminated counterpart, while the opposite was true at the Berger location. The concentrations of the heavy metals Pb and Zn in the contaminated soils were low, while the Cu concentration was high. Although the concentrations of these heavy metals were below the standards for potential environmental risks, the high Cu concentration at both locations poses a potential ecological risk and may affect soil and human health as Cu accumulates in critical levels in the soil due to the continued irresponsible disposal of spent oil on the ground.

Automotive Parts Defect Detection Based on YOLOv7

Various complex defects can occur on the surfaces of small automobile parts during manufacturing. Compared with other datasets, the auto parts defect dataset used in this paper has low detection accuracy due to various defects with large size differences, and traditional target detection algorithms have been proven to be ineffective, which often leads to missing detection or wrong identification. To address these issues, this paper introduces a defect detection algorithm based on YOLOv7. To enhance the detection of small objects and streamline the model, we incorporate the ECA attention mechanism into the network structure’s backbone. Considering the small sizes of defect targets on automotive parts and the complexity of their backgrounds, we redesign the neck portion of the model. This redesign includes the integration of the BiFPN feature fusion module to enhance feature fusion, with the aim of minimizing missed detections and false alarms. Additionally, we employ the Alpha-IoU loss function in the prediction phase to enhance the model’s accuracy, which is crucial for reducing false detection. The IoU loss function also boosts the model’s efficiency at converging. The evaluation of this model utilized the Northeastern University steel dataset and a proprietary dataset and demonstrated that the average accuracy (mAP) of the MBEA-YOLOv7 detection network was 76.2% and 94.1%, respectively. These figures represent improvements of 5.7% and 4.7% over the original YOLOv7 network. Moreover, the detection speed for individual images ranges between 1–2 ms. This enhancement in detection accuracy for small targets does not compromise detection speed, fulfilling the requirements for real-time, dynamic inspection of defects.

Investigation on effect of high-efficiency solid solution and hot stamping process on microstructure evolution and mechanical properties of high-strength aluminum alloy

Aluminum alloy has become an important lightweight material in the automotive industry due to its excellent performance. The development of hot stamping technology has effectively promoted the application of high-strength aluminum alloys in auto parts. However, aluminum alloy hot stamping requires a long time for solid solution and aging heat treatment, which hinders its mass production application in the existing mature hot stamping production line. Therefore, this paper studies the effect of a high-efficiency solid solution and hot stamping process on the microstructure and mechanical property strengthening mechanism of high-strength aluminum alloy. The contact heating and hot stamping experiment device was designed. It was found that the temperature rise rate of the sheet during the contact heating process could reach 44.51 °C/s. The experiment results show that contact heating treatment with a solution temperature of 480 °C and a solution time of 20s can achieve the high-efficient solution treatment of the sheet metal. The high-temperature deformation behavior of 7075-T6 at different temperatures (300-450 °C) and different strain rates (0.01∼1/s) under the condition of high-efficiency solid solution rapid heating was studied.

Research on Defect Detection Method of Painting Parts Based on Machine Vision

The technology is used to study and analyze the appearance defect characteristics of sprayed auto parts. The corresponding recognition method is developed by using MATLAB and Halcon software. Firstly, the causes of background noise and uneven brightness are described from the hardware and theory, and the specific treatment methods are given from the two perspectives of eliminating background noise and balancing illumination. A variety of frequency domain low-pass filters are constructed to eliminate background noise. The image preprocessing algorithm based on homomorphic filter is studied to achieve the expected preprocessing effect. The image segmentation method of local features is adopted, and the binary processing is carried out. Corresponding recognition algorithms are designed for different defect features. The on-line monitoring system of spraying quality is established and field test is carried out to verify the effectiveness of the system and realize the rapid and accurate identification of spraying quality. The single recognition time is 320 milliseconds, and the recognition accuracy is 97%. Compared with manual identification, it is improved by about 40% and meets the needs of industry applications