Auto Parts Research Articles

Research on the demand prediction of parts inventory for auto customer service

In order to optimize the inventory of auto aftermarket parts, the second weighted moving average method is used to forecast the demand of auto aftermarket parts. Compared with the traditional weighted moving average method, the results show that the improved method is better than the traditional method.

Effect of vulcanization time on crosslink density and aging performance of natural rubber composites

Abstract Natural rubber composites are widely used in the automotive industry because of their improved viscoelastic characteristics that are mostly governed by crosslink density. However, rubber parts suffer deterioration of performance over long service lives. Therefore, optimization of crosslink density and prediction of changes in physico-mechanical properties over time at elevated temperatures is extremely important for the production of safe auto parts. In this work, the effect of vulcanization time on crosslink density and thus the performance and lifetime of natural rubberbased auto parts was investigated. The natural rubber mixture prepared in this context was vulcanized for 3, 5, 10 and 15 minutes at a constant temperature of 160 °C. The crosslink density of each vulcanizite was determined by equilibrium swelling tests and the Flory-Rehner equation. The maximum crosslink density (10.75 × 10-5 mol × cm-3) and the minimum permanent compression set values (10 % at 70 °C and 25 % at 100 °C) were recorded for the sample vulcanized for 10 minutes (v10). Aging behavior of the samples were investigated by stress relaxation tests performed at 85 °C, 100 °C and 120 °C. The service lives of the vulcanizites at different temperatures were predicted by linear Arrhenius fits of degradation times. The sample vulcanized for 10 minutes (v10) was shown to exhibit a service life of 2282 hours at 70 °C in air and the optimum physico-mechanical performance under real operating conditions. The performance and lifetime prediction procedure used in this work could be employed in an early design of rubber components for specific applications.

Accurate Traceability of Key Auto Parts in China Automobile Factory

Based on barcode specification and quality error prevention, the manufacturing plant controls traceability information of logistics distribution, automobile assembly and quality inspection, and realizes accurate traceability of key parts of the vehicle. This thesis discusses how to realize the KPC of key parts and the quality traceability of production and assembly process when quality defects occur in a company.

Research on Computer Vibration Test System of Rotating Machinery Based on Wavelet Transform in Auto Parts Inspection

With the development of the automobile industry, the quality of automobile parts has attracted more and more attention. In the process of automobile driving, automobile parts are affected by temperature change, vibration, impact, friction and so on, which will lead to the performance damage of automobile parts. Vibration testing technology is an experimental method which combines theoretical analysis with practical testing. Vibration testing system is mainly used to inspect the quality of automotive parts, and to provide basis for parts optimization. Wavelet change is a new transform analysis method. This paper mainly introduces the theory of vibration. Then, this paper analyses the composition of vibration testing system in automotive parts testing. Finally, computer technology is used to analyze the application of the rotating machinery vibration test system based on wavelet change in vehicle vibration test.

An investigation into the method of energy monitoring and reduction for machining systems

Improving the energy efficiency of machining systems (MSs) is an urgent and challenging issue in sustainable manufacturing. Considering the dynamics and uncertainty of MSs, a five-dimension model is developed to monitor and reduce the energy consumption (EC) of MSs. In this model, the automatic acquisition of EC data from physical MSs is driven by Radio Frequency IDentification (RFID) read events. The EC service model provides monitoring and scheduling services for reducing the EC of physical MSs by connecting with virtual MSs in real time. The procedures of the EC reduction method for the MSs are presented. A case study of MSs for auto parts was conducted to illustrate the proposed method. The results showed that the time and EC of MSs were reduced by 148 s and 49.67 KJ, respectively.

Analysis of the Impact and Global SCM Diversification on the Automotive Industry caused by COVID19

코로나19는 사람뿐만 아니라 각국의 경제와 기업의 경영활동에도 영향을 미쳤다. 이는 국내외 자동차산업에도 예외 없이 큰 타격을 주었다. 본 연구는 코로나19가 자동차 산업의 글로벌 공급사슬에 끼친 영향에 대해 분석하고 현재 취할 수 있는 대응방안과 향후 어떤 방향으로 공급사슬이 변화해 나가야할지를 분석하고자 한다. 이를 위해 제 2장에서는 자동차 산업의 현황을 제시하였으며 제 3장에서는 코로나19가 자동차산업에 끼친 영향을 사례중심으로 분석하였다. 제4장에서는 현상황에서 취할 수 있는 물류적 대응방안을 제시하며 코로나시대 또는 그 이후의 자동차 산업 글로벌 공급망 운영방안에 대한 시사점을 제시하였다. 이를 위해 공급망과 공급루트 다변화의 중요성을 언급 하였으며 그 예시로 TSR·TCR의 전략적 활용방안, 새로운 복합운송루트의 효용성 그리고 유가폭락과 물동량 저하로 시작한 아프리카 대륙을 경유하는 해상운송 루트의 사용사례를 분석 하였다. 이러한 사례분석은 공급망 다변화의 중요성을 역설할 뿐만 아니라 향후 코로나19의 지속에 따른 급변하는 상황에 대한 신속한 물류대응과 글로벌 조달 리스크 분산의 필요성에 실무적, 이론적, 전략적 시사점을 줄 수 있을 것이다.Purpose : This study analyzes the impact of COVID 19 on the global supply chain of the automotive industry and suggest current impact and development directions of the supply chain. Research design, data, methodology : In this paper, the effects of alternative transportation means and logistics routes was analysed by using Inventory Theoretic Model. First, assuming import from Europe, optimal procurement methods were derived using TSR and TCR. Second, the logistics efficiency is verified by adding a newly emerged multimodal transportation route to the Korea-US auto parts logistics transport case. Results : It was proved that diverse SCM channel and logistics route able to effectively operate global logistics. Conclusions : This case analysis not only emphasize the importance of supply chain diversification, but also give practical, theoretical, and strategic implications for the necessity of rapid logistics response to changing circumstance and global procurement risk distribution in the future.

The Strategy and Path of Finite Element Analysis in the Design of Auto Parts

<p align="justify">Under the background of helping to realize “made in China 2025”, it is the most challenging task to standardize the implementation of General Principles of Structural Finite Element Analysis for Mechanical Products (GB/T33582-2017). The current changes and progress of the automobile industry are promoting the development of innovation. Infrastructure design, reducing design risks and eliminating artificial subjective factors can shorten the design cycle of the goals to be achieved.</p>

A fuzzy cognitive map based on Nash bargaining game for supplier selection problem: a case study on auto parts industry

Supplier Selection (SS) is a critical issue due to intense competition in the current market and the need to provide customer necessities with acceptable quality. On the other hand, SS depends on various criteria that make it a Multi-Criteria Decision-Making problem. Hence, a novel framework has been proposed in the current study to evaluate and rank suppliers. The proposed framework by aggregating the Process Control Score (PCS) and Process Evaluation Score (PES) evaluate and rank suppliers. For calculating PCS, a new structure and logic of the Fuzzy Cognitive Map based on the Nash Bargaining Game (BG-FCM) has been proposed to solve FCM’s shortcoming in distinguishing between the important concepts in the real world. Moreover, for generating solutions with high separability and helping decision-makers to have a precise analysis of the system, a modified learning algorithm based on the Particle Swarm Optimization (PSO) and S-shaped transfer function (PSO-STF) has been utilized for training BG-FCM. For calculating PES, experimental mathematical equations in the inspected case have been utilized for important criteria of quality, delivery time, and price of the shipment. The proposed framework has been applied in an auto parts industry for validation. The results show that BG-FCM can successfully highlight the most important concepts and assign their original value. Also, PSO-STF in the comparison between other conventional FCMs’ learning algorithms has better performance in generating solutions with high separability. It can be concluded that BN-FCM with more progressive intelligence can analyze the complex systems and help decision-makers to have a vivid insight into the system.

The influence of leadership styles on new product development performance: the moderating effect of product innovativeness

PurposeThis article aims to examine the impact of leadership styles on new product development (NPD) and how product innovativeness of NPD projects moderates this impact. The results reveal the implications of different product innovativeness for leaders of NPD projects in achieving successful outcomes.Design/methodology/approachData were collected through a questionnaire survey of NPD team members who were involved in NPD. Participants were employees from different departments, including research and development (R&D), quality control (QC), production and marketing. These individuals worked in innovative manufacturing industries such as automotive and auto parts and electronics.FindingsResults show that transformational leadership has a significantly positive effect on new product success and NPD speed, whereas transactional leadership has a significantly negative effect on both outcomes. Furthermore, the positive impact of transformational leadership on new product success for high innovativeness is stronger than for low innovativeness. In addition, the negative impact of transactional leadership on both new product success and speed for high innovativeness is stronger than for low innovativeness.Research limitations/implicationsFirst, the sample size was fairly small because of limited access to middle-level management and low willingness to share information involving the firms' production. Second, since both transformational and transactional leaderships are multidimensional, each dimension may affect performance in different ways. Third, the respondents were mainly from a single department which could omit varying perspectives.Practical implicationsThe research findings provide recommendations on how different leadership styles support team members to effectively perform NPD tasks in either high or low innovativeness.Originality/valueThis study extends the theory of leadership by providing a holistic understanding of how leadership styles affect NPD performance. It also extends the understanding of how the impact of two different leadership styles on NPD performance is moderated by product innovativeness.

PREDICTING CUSTOMER LOYALTY LEVELS OF PROFESSIONAL CUSTOMERS: THE CASE OF BALKANS

The paper presents the results of customer satisfaction survey in the auto spare parts industry through the presented analyses conducted in period from 2015 to 2018 on a sample of 3269 professional customers of a company that operates in the region of Balkans: Bosnia and Herzegovina (BIH), Republic North Macedonia (RNM) and Serbia (SRB). The Categorical Regression Analysis (CATREG) was used as a method of predicting the level of customer loyalty by combining variables from the survey-questionnaire with regard to the relationship between the sales staff and the characteristics of the products themselves. The study identifies that for BIH the range of goods, delivery and the price and quality ratio have the greatest impact on customer loyalty, for RNM the assortment of goods, delivery and manner of resolving complaints, while in Serbia the delivery of goods and the resolution of complaints, have the greatest importance in anticipating the level of loyalty of customers.

A Framework for Designing the Customer-Order Decoupling Point to Facilitate Mass Customization

Abstract In the age of Industry 4.0, manufacturing enterprises are under pressure to improve mass customization to satisfy evolving demands in different markets. One challenge is to fulfill orders swiftly at an acceptable cost, while maintaining service quality. To do this, the customer-order decoupling point (CODP), where value-adding activities take place, should be designed and adapted to changing market demands. We propose a formulation-exploration framework to make decisions on customer-order decoupling point positioning and improve the supply chain to support mass customization. A test problem of auto parts manufacturing is used to illustrate the efficacy of our framework. The formulation-exploration framework can be used to design a supply chain to facilitate the mass customization of products, especially when information is incomplete and inaccurate (including uncertainties), and goals conflict with each other. In this paper, we focus on the method embodied in the framework rather than the results per se.

A Study on Potential Strip Shape Control of High‐Strength Steel during Hot Pinch Rolling Process

Hot‐rolled high‐strength steel (HSS) strips always present side‐camber after they are cut into subsections along the rolling direction. To deal with the potential strip shape defect of hot‐rolled HSS, the nonlinear finite element (FE) software is applied to establish a 3D model of pinch roll and strips to simulate the pinch rolling process before the hot rolling coiler. The effects of temperature distribution, roll wear, friction coefficient, initial strip flatness defects, and tension on the strip longitudinal extension distribution are studied along the width direction. The results indicate that the pinch roll wear presents a great influence on both the tendency and quantitative value of the strip longitudinal extension distribution. The maximum unevenness value is 178%, and the maximum differences of longitudinal strain between the center and edge of the strips reach to 51.43%. A newly pinch roll contour is proposed to improve the potential strip shape defects. After the industrial application, the average pinch roll wear thickness decreases from 180 to 120 μm. The hot rolled strips are cut into substrips and the maximum side‐camber value decreases from 12 to 3 mm, which meets the requirement from the auto part manufacturers.

Application of the OEE tool in an auto parts industry’s production line

The aim of this paper is to work on lean manufacturing's theory of tools in practice in a multinational auto parts industry responsible for the exhaust industry, located in state of São Paulo, Brazil. When use tools like OEE, TPM and Kaizen, it is possible to analyze the conditions of the equipment in the current scenario in production, proposing improvements such as professional maintenance planning, generating Kaizens, facilitating periodic activities (inspection, cleaning, lubrication and others) and training the employees to perform the autonomous maintenance, reducing the paras and faults of the equipment. was possible to optimize the OEE indicators: availability, performance and quality, resulting in a significantly better overall efficiency index.

ON THE QUESTION OF DETERMINING THE COST OF PAINTWORK OF WHEELED VEHICLES WITH ELEMENTS OF AIRBRUSHING

This article outlines problematic issues in determining the cost of paintwork of wheeled vehicles with elements of airbrushing. Options of applying patterns on the auto parts of the body depending on their complexity and the possibility of reapplication are considered. Ways of calculating the number of man-hours on airbrushing work are taken out, namely tabular data on already existing methodological recommendations as well as alternative, more accurate ways of calculating standard time are suggested, which at most reflect real costs, both for the time spent on airbrushing drawing, and on the amount of materials accordingly.

Raman spectroscopy for the identification of differences in the composition of automobile lubricant oils related to SAE specifications and additives

This study employed Raman spectroscopy for the identification of spectral differences in automotive lubricant oils with different SAE specifications. Samples of 18 lubricant oils were obtained from a local auto parts store. Spectra were obtained with a dispersive Raman spectrometer (830 nm) and separated according to the type of base oil in the samples: mineral, semi-synthetic and synthetic. Also, samples were separated according to the SAE specifications regarding the viscosity grade in low and high temperatures. Principal component analysis (PCA) showed that the lubricants with mineral base oils presented peaks referred to aromatic hydrocarbons and additives containing aromatics, sulfites/dissulphites and sulfonates, while semi-synthetic and synthetic base oils presented peaks referred to alkanes. Other peaks referred to alkanes and olefins were also seen in synthetic base oils. The discriminant analysis based on quadratic distance applied to the PCA variables was able to discriminate the lubricant samples according to the type of base oil with 89.7% accuracy and discriminate the SAE viscosity grade for low and high temperatures with 95.8% and 90.0% accuracy, respectively. The use of Raman spectroscopy makes possible nondestructive evaluation of lubricant oils, which may replace expensive and complex traditional tests and methods of quality control.

Research on Correspondence between ELV Exemption and Auto Parts Products

Restricting the use of hazardous substances in automobiles has become an inevitable trend for the green development of automotive products. In China, the technical requirements for hazardous substances in automobiles stem from GB/T30512 “Requirements for Prohibited Substances in Automobiles”, and the standard is currently undergoing strong revisions. One of the core contents of the standard is the exemption list, which stipulates the compliance content and distribution of hazardous substances in automobile products. This article analyzes the scope of auto parts and materials covered by each exemption list for the exemption list, constructs the corresponding relationship between the exemption list and auto parts in principle, and provides guarantee for the implementation of subsequent standards.

Effect of vulcanization time on crosslink density and aging performance of natural rubber composites

Abstract Natural rubber composites are widely used in the automotive industry because of their improved viscoelastic characteristics that are mostly governed by crosslink density. However, rubber parts suffer deterioration of performance over long service lives. Therefore, optimization of crosslink density and prediction of changes in physico-mechanical properties over time at elevated temperatures is extremely important for the production of safe auto parts. In this work, the effect of vulcanization time on crosslink density and thus the performance and lifetime of natural rubberbased auto parts was investigated. The natural rubber mixture prepared in this context was vulcanized for 3, 5, 10 and 15 minutes at a constant temperature of 160 °C. The crosslink density of each vulcanizite was determined by equilibrium swelling tests and the Flory-Rehner equation. The maximum crosslink density (10.75 × 10-5 mol × cm-3) and the minimum permanent compression set values (10 % at 70 °C and 25 % at 100 °C) were recorded for the sample vulcanized for 10 minutes (v10). Aging behavior of the samples were investigated by stress relaxation tests performed at 85 °C, 100 °C and 120 °C. The service lives of the vulcanizites at different temperatures were predicted by linear Arrhenius fits of degradation times. The sample vulcanized for 10 minutes (v10) was shown to exhibit a service life of 2282 hours at 70 °C in air and the optimum physico-mechanical performance under real operating conditions. The performance and lifetime prediction procedure used in this work could be employed in an early design of rubber components for specific applications.

Hazard quotient, microbial diversity, and plant composition of spent crude oil-polluted soil

BackgroundThe present work assesses the concentration of some heavy metal, plant species composition, and microbial diversity of spent crude oil-polluted soil from electric generator plant house, auto mechanic workshop, bakery, and auto spare part shops in four local governments areas (Egor, Ikpoba-Okha, Oredo, and Ovia North) in Edo State, Southern Nigeria.ResultsHazard quotient (HQ) of heavy metals varied in all the spent crude oil-polluted soil evaluated in the study. The HQ of heavy metals from auto mechanic workshop had the highest values for Cr (2.19), Mn (0.0965), Zn (4.1108), Fe (9.32015), and Cd (0.0155). The most frequent bacterial and fungal species found in all 16 sites were Bacillus subtilis (93.75%) and Aspergillus niger (100.0%) respectively. Auto spare part shops in Oredo had a bacterial count of 1.0 × 105 CFU/g while the bacteria count around power generator plants in Egor had a bacteria count of 1.71 × 105 CFU/g. Some of the plant species identified around all the sites include Acanthospermum hispidum, Alternanthera repens, Axonopus compressus, Cyperus esculentus, Eleusine indica, Paspalum scrobiculatum, and Tridax procumbens.ConclusionSpent crude oil pollution of the soil led to high amounts of heavy metal in the soil. However, the presence of higher plants and variable diversity and richness of microorganisms found in the soil are likely contributing to the remediation of the polluted soil.

Manufacture material characteristic analysis of original and alternative auto parts. Case Study: Brake Disc

Manufacture material characteristic analysis of original and alternative auto parts. Case Study: Brake Disc

REDUCTION OF IN- HOUSE REJECTION BY SIX SIGMA IN AUTO- ANCILLARY INDUSTRIES

Purpose- This paper is about the application of Six Sigma methodology in an auto ancillary industry. This paper demonstrates the application of DMAIC methodology to reduce the in- house rejections of the production process. Design/Methodology/approach- The complete manufacturing process auto ancillary parts was studied and decided to apply the DMAIC (Define-Measure-Analyze-Improve-Control) approach of Six Sigma methodology. The process was defined by SIPOC diagram, Pareto analysis is used to measure the defects, potential causes of the defects were found by cause and effect diagram, the process need to be improved by the control measures suggested for implementation to reduce the rejections. Thus, the in-house rejection will be reduced by increasing the productivity and thus by increase in sigma level. Findings- The process aims for the in-house rejection rate of 700 ppm. The actual rejection rate is above 2000 ppm which is 4.5 Sigma level. The six sigma methodology is applied and the major defects and the potential causes for the defect were found. The optimal solutions for were provided for improvement in process and for reduction of in- house rejections. Practical Implications- This six sigma methodology can be successfully implemented to improve the quality, productivity and profitability by reducing the defects in the process. Originality/Value- The auto ancillary manufacturing industry in India has the great potential for growth. This application of Six Sigma methodology in the production process improves the quality, productivity and profitability in small and medium scale industries.