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Maintaining the newness of a vehicle is currently significant concern for users and vehicle companies. The gap difference between interior and exterior trims plays a crucial role in the overall appearance of vehicles. Over time, the gap and flush parameters of these trims may change due to the movement of components, putting forward higher requirements for the assembly accuracy and reliability design of automotive products. This article presents a study where a test car is subjected to endurance vibration on a wheel-coupled vibration bench. Through measuring the changes in gaps and flushes between the exterior trim parts at different endurance mileage intervals, the variation patterns are obtained. Using dimensional engineering technology, the effects of durable vibration on the gaps and flushes of the vehicle's exterior trim parts were determined. This study provides a foundation for the design of new interior and exterior decoration parts in automobiles. It also offers valuable insights for product design, development, and quality improvement. Problems can be predicted in advance in the early stage of design, and closely coordinate various aspects of production and manufacturing to obtain products with higher standards, requirements, and quality. [ABSTRACT FROM AUTHOR]

A molecular level understanding of the aqueous Mg corrosion mechanism will be essential in developing improved alloys for battery electrodes, automobile parts, and biomedical implants. The structure and reactivity of the hydroxylated surface is expected to be key to the overall mechanism because (i) it is predicted to be the metastable surface state (rather than the bare surface) under a range of conditions and (ii) it provides a reasonable model for the outer corrosion film/water interface. We investigate the structure, interactions, and reactivity at the hydroxylated Mg(0001)/water interface using a combination of static Density Functional Theory calculations and second-generation Car–Parrinello ab initio molecular dynamics. We carry out detailed structural analyses into, among other properties, near-surface water orientations, favored adsorption sites, and near-surface hydrogen bonding behavior. Despite the short timescale (tens of ps) of our molecular dynamics run, we observe a cathodic water splitting event; the rapid timescale for this reaction is explained in terms of near-surface water structuring lowering the reaction barrier. Furthermore, we observe oxidation of an Mg surface atom to effectively generate a univalent Mg species (Mg+). Results are discussed in the context of understanding the Mg corrosion mechanism: For example, our results provide an explanation for the catalytic nature of the Mg corrosion film toward water splitting and a feasible mechanism for the generation of the univalent Mg species often proposed as a key intermediate. [ABSTRACT FROM AUTHOR]

In this work, we aim to understand and predict the thermal properties of automotive lubricants using non-equilibrium molecular dynamics. After a previous study on model materials for the mechanical parts of a car engine, we now focus on the thermal conductivity κ of the poly- α -olefin base oil (PAO4) using the well-known sink and source method to study the response of the system to an imposed heat flux. We present a detailed methodology for the calculation of κ , taking into account specific constraints related to the system under study, such as large steady-state fluctuations and rapidly growing stationarization times. We provide thermal conductivity results using four different force fields, including OPLS-AA, PCFF and COMPASS, in a temperature range of 300 to 500 K, which corresponds to the typical operating range of a car engine. The results are compared to experimental measurements performed on the commercial compound using the laser flash method. Agreement at room temperature is shown to be excellent for our in-house force field. [ABSTRACT FROM AUTHOR]

Non-heat-treated Al–Mg-based die casting alloys have been developed for the structural parts of automobiles. In previous studies, alloy compositions with at least 1.0%Si have been proposed to reduce the hot tearing susceptibility (HTS). On the other hand, the increase in the Si content reduces the ductility. For some automotive body structures, Al–Mg alloy die castings with Si content exceeding 1.0% should not have the required ductility. This study aims to develop an Al–Mg alloy with both high ductility and low HTS by investigating the following three characteristics of an Al–4.5Mg–1.0Mn alloy with 0.2%Si added: (1) additional elements to reduce the HTS, (2) the associated mechanical properties (requirements for the automotive company: 0.2% proof stress ≥ 140 MPa and fracture elongation ≥ 15%), and (3) the mechanism of decreasing the HTS. It was revealed that the co-addition of 0.025%Sr, 0.08%Ti, and 0.016%B reduced the HTS when the hydrogen content of the melt was 0.5–1.0 mL/100 g Al. Furthermore, the 0.2% proof stress and fracture elongation of a lower link arm produced via HPDC with the above composition were found to achieve the requirements. It was also indicated that the mechanism of decrease in the HTS by the Sr addition should result from the decrease in the thermal tensile load due to the formation of hydrogen porosity at a lower solid fraction than that without Sr. It is suggested that when 0.025%Sr, 0.08%Ti, and 0.016%B are added to the Al–4.5Mg–1.0Mn–0.2Si alloy, non-heat-treated automotive structural parts with both high ductility and low HTS will be obtained by high-pressure die casting. [ABSTRACT FROM AUTHOR]

In order to detect and diagnose the operating status without disassembling automobile parts, engine speed and suspension status were tested and analyzed based on vibration detection technology. Based on a DSP processor and an acceleration sensor, the speed of a single cylinder engine was tested under steady-state and transient conditions, respectively. Using the cepstrum method, the vibration signals were collected at different speeds are processed, the fundamental frequency was extracted, and the engine speed information was obtained. According to the speed verification using the Otsu EWT method, the maximum relative error of engine speed was less than 1.5 %, and the error decreases as the speed increases. In order to ensure the reliability of suspension vibration signals, the overall structure and safety of the vibration characteristic detection scheme were designed. Due to the limited sampling frequency of suspension load status sensor data, the EMD method was adopted to process dynamic load signals, which had a good separation effect on suspension vibration signals. [ABSTRACT FROM AUTHOR]

Image defect detection of casting parts is a key part of the production process in the machinery manufacturing industry. The traditional methods are ineffective because traditional computer image processing methods require a large number of manual features to be set artificially, and the detection time is too long. In order to save human resources and improve the efficiency of image defect detection, this paper proposes a deep learning-based defect detection method for automobile parts. This paper selects EfficientNetB0 as the backbone framework of the target detection network, which significantly reduces the memory usage of the model and shortens the model inference time, while improving the model detection accuracy. Facing the problem of small samples of defect image dataset, we analyze the image characteristics of the dataset and introduce shape transformation and scale scaling as the basic online data enhancement method according to the industrial field image projection law. Then, it is expected to combine the traditional image processing algorithms according to the characteristics of casting parts with different depth distribution and multiple morphological changes, and develop a special image defect data enhancement method. This further improves the performance of the model and increases the detection accuracy of the algorithm by 22.3% without increasing the data. [ABSTRACT FROM AUTHOR]

A356 alloy based composites are extensively used in different component industries like components of automobile parts owing to pronounced strength to weight ratio. In the current paper, A356/Si3N4 nanocomposites are fabricated by means of stir casting by varying Si3N4 reinforcement nanoparticles. Silicon Nitride (Si3N4) nanoparticle is intermixed to Al powder mechanically to develop their wettability among the particles of A356/Si3N4 nanocomposites. The Si3N4 nanoparticle is integrated by altering weight percentage. The electomechanical stirring process to produce the vortex is taken up to spread Si3N4 nanoparticles in the liquefied matrix dispensed into a permanent mould. Morphological investigation of the composite specimen is accomplished by TEM. Based on the study, it can be acquired that the strengthening by Si3N4 nanoparticles promotes the strength and hardness of the fabricated nanocomposites. The maximum tensile strength is depicted to be 319 MPa for A356/5%Si3N4 nanocomposites whereas hardness is increased from 43 HBN to 86 HBN. The physical properties such as density and porosity are also increased due to the presence of Si3N4 nanoparticles. The maximum porosity of 1.12% was predicted at 5 wt. % of Si3N4. The TEM examination discloses the presence of Si3N4 nanoparticles in the fabricated composites. Additionally, the current research guidance has ability to afford a monitor to the industrialized preparation of A356/Si3N4 nanocomposites. [ABSTRACT FROM AUTHOR]

Brake pads are vital parts of automobiles, where tribological properties are prime concern. Usually, asbestos brake pads were used, which were replaced by copper-based in later years. As brake lining materials have evolved, synthetic friction composites were explored as alternatives. Recent works suggest that, natural composites are promising friction material. However, poor thermal conductivity and frictional stability have limited their applications. Surface treatment of fibers and addition of secondary fillers have improved their possibilities. Thus, hybridization of reinforcements has expanded their range of applications. The present article attempts to review various aspects of brake pads and their testing with attention on natural composites. Their properties were studied to conform their ability to meet desired requirements. The article reviews the studies conducted in recent years on various materials properties related to brake pads. The future potential of natural components in the development of friction composite materials for automotive applications is highlighted. [ABSTRACT FROM AUTHOR]

This methodological paper proposes two codifiability indicators to examine trade and manufacturing statistics and the spatial distribution of value-added manufacturing activities. Codifiability is defined as the level of documentation about the manufacturing processes of a product required to allow tasks to be replicated by other suppliers. First, the codifiability indicators allow researchers to examine products that are grouped under the same sub-product class in conventional statistics, but the manufacture of such products could involve vastly different technologies and thus the level of value-added. A proprietary database was used to delineate the supply networks of automakers in passenger vehicles and their major tier-I suppliers between 2000 and 2015. Second, codifiability allowed the researchers to unpack the spatial distribution of value-addedness of each supplier in the production network, as illustrated by the top two parts suppliers to the automotive industry, Bosch and Denso. The importance of codified standardized commodity parts with lower value-added in the continental European home market illustrates the importance of geographical proximity for Bosch, while the dominance of non-standardized service parts with lower level of codification and higher value-added in its exports to North America is also consistent with the ‘follow the customers’ process in the overseas market reported in the automotive industry. The relative importance of service parts with lower level of codifiability in Denso’s home market illustrates the division of labour with other cross-holding suppliers (especially Aisin and JTEKT) and thus the effects of the interlocking cross-holding of Japanese automobile and parts suppliers, which reconfirms the importance of cultural proximity in Asia’s (Japanese) supply networks. [ABSTRACT FROM AUTHOR]

Due to global warming, environmental issues are one of the most interesting issues in the world. Especially for automobiles that emit pollutants, the issue of lightweight design is one of the important research areas. Thus, this study deals with the lightweight design of a camber link, an automotive suspension component, through finite element analysis. With reference to the camber link made of steel (SM45C) material that has been proven by commercialization, we will replace it with A356 aluminum alloy material to reduce the weight. Here, the design was changed through finite element analysis to reinforce the reduction of rigidity due to material substitution. In particular, we propose a method of designing a camber link considering the safety factor by analyzing the change of stress applied to the suspension. The weight reduction of about 14 % was achieved through static analysis using the weight factor. Using the dynamic optimization method through static analysis using the weight factor and stress ratio, it can be seen that the application is convenient and easy for the lightweight and optimal design of automobile parts. [ABSTRACT FROM AUTHOR]

Rubber tires, as an important part of automobiles, are produced by molding operation under molten temperature and high pressure. However, mold fouling during the vulcanization process is a rock-ribbed problem that not only leads to the loss in productivity and degradation of product quality but also results in severe accidents and enormous economic losses. In this work, a promising Co-Mo/CeO2 composite coating was electroplated and investigated to solve the mold fouling problem. The effect of CeO2 content on the surface morphology, microstructure, hardness, tribological and electrochemical behavior is systematically studied. With an addition of 10 g/L CeO2, the Co-Mo/CeO2 composite coating not only possesses the highest microhardness, the best wear and corrosion resistance but also features hydrophobicity and remarkable mold antifouling performance. This study offers a new strategy for producing composite coatings with excellent performance to reduce mold fouling in practical tire industry applications. Co-Mo/CeO2 composite coatings with excellent corrosion and wear resistance as well as low surface energy were simply electrodeposited and applicated for antifouling in tire mold for the first time. [ABSTRACT FROM AUTHOR]

Various petroleum-based polymers are being widely used in the automobile and aviation industries. However, the scarcity of petroleum-based polymers, their lack of biodegradability, and stringent environmental regulations lead researchers to look for green biopolymers/biocomposites as an alternative to petroleum-based polymers. Biopolymers have potential applications in various exterior and interior parts of an automobile, including steering, doors, wheels, electrical components, engine parts, exhaust systems, and so on. Almost all automakers are currently focusing on developing novel biopolymers, and they have successfully used bio-based materials in their newer version of automobiles, eventually replacing petroleum-based polymers. However, biopolymer uses in the aviation industry are not yet widespread because of stricter property requirements. Some advanced biopolymers are applied in interior aircraft panels, waste and drainage systems, engine components, cockpits, portholes, windshields, aircraft tires and inner tubes, exterior lighting, and helicopter windscreens. These materials are expected to substitute traditional plastics with the help of modifying agents, cutting-edge manufacturing technology, and a reliable supply chain of biopolymers. This review discusses the current practices, recent advances, and prospects of biopolymers in automotive and aviation engineering applications. [ABSTRACT FROM AUTHOR]

The goal of this paper is to establish a feasible three-species equilibrium model to analyze the symbiotic relationship of an automobile manufacturing community. In order to extend the Lotka–Volterra model to empirical analysis, this paper proposes an enterprise community symbiosis model based on a three-dimensional Lotka–Volterra model, as the classical two-dimensional Lotka–Volterra model has limited application scenarios. This paper takes the innovation assets of three communities of the Chinese automobile manufacturing industry as samples. The industrial community related to automobile manufacturing consists of the automobile manufacturing population, automobile parts population, and enterprise service industry population. The symbiosis system is empirically analyzed from two aspects: the balanced development of the three populations and the competitive evolution of the three populations. The stability of the model is tested by the data from information technology and the intelligent manufacturing community. In the process of dynamic simulation, the symbiotic relationship between automobile manufacturing-related populations shows a significant "skew symbiotic relationship." This paper reconstructs the "whole population symbiosis" optimization model as skew distribution is difficult to apply to support collaborative development. The symbiosis optimization under the equilibrium state of the three populations shows that the growth of the three automobile manufacturing industry populations has the possibility of equilibrium and reciprocity. The empirical analysis fully demonstrates the feasibility of this research paradigm. The evolution analysis of the symbiotic system shows that cooperative behavior is better than competitive strategy. The research paradigm proposed in this paper can better analyze the symbiosis mechanism of the enterprise community. [ABSTRACT FROM AUTHOR]

The main parts of automobiles are the piston rod of the shock absorber and the steering rack of the steering gear, and their quality control is critical in the product process. In the process line, these products are normally inspected through visual inspection, sampling, and simple tensile tests; however, if there is a problem or abnormality, it is difficult to identify the type and location of the defect. Usually, these defects are likely to cause surface cracks during processing, which in turn accelerate the deterioration of the shock absorber and steering, causing serious problems in automobiles. As a result, the purpose of this study was to present, among non-destructive methods, a shock response test method and an analysis method that can efficiently and accurately determine the defects of the piston rod and steering rack. A test method and excitation frequency range that can measure major changes according to the location and degree of defects were proposed. A defect discrimination model was constructed using machine and deep learning through feature derivation in the time and frequency domains for the collected data. The analysis revealed that it was possible to effectively distinguish the characteristics according to the location as well as the presence or absence of defects in the frequency domain rather than the time domain. The results indicate that it will be possible to quickly and accurately check the presence or absence of defects in the shock absorber and steering in the automobile manufacturing process line in the future. It is expected that this will play an important role as a key factor in building a smart factory. [ABSTRACT FROM AUTHOR]

Carbon/glass fiber-reinforced polymer hybrid composite (HFRP) has the advantages of a light weight and high strength. For the lightweight design of automobile parts, composite parts made of HFRP and polymer materials are increasingly in demand. The method of the injection molding is usually adopted to fabricate composite part with HFRP and polymer materials. The connecting strength between the two materials has an important influence on the service life of the composite part. In this paper, HFRP and polyamide-6 (PA6) were used to fabricate a composite part by the injection molding method. In order to improve the connecting strength between HFRP and PA6, a kind of micro-grooves was fabricated on the HFRP surface. The micro-grooves on the surface of the HFRP provided sufficient adhesion and infiltrating space of molten PA6 material into the mold. In addition, the glass fiber in HFRP can also be used as nucleating agent to facilitate the rapid crystallization of PA6. The micro-grooves on the surface of HFRP were embedded into PA6 like nails, which could improve the connecting strength at the interface effectively. The paper investigated the effects of mold temperature, injection pressure, holding pressure and holding time on the injection quality and connecting strength of composite parts in detail. With a mold temperature of 240 °C, an injection pressure of 8 MPa, a holding pressure of 8 MPa and a holding time of 3 s, the maximum tensile strength of 10.68 MPa was obtained for the composite part. At the effect of micro-grooves, the tensile strength of the composite part could be increased by 126.27%. [ABSTRACT FROM AUTHOR]

This research is concerned to propose a computer vision algorithm to track manual assembly task. Manual assembly in case of electronics parts are used largely in automotive industry. The phases tracking of assembly could also be used for learning purposes such in case showed in this research, checking the assembly of an electronic educational board. The algorithms used for detection of different components are CNN (Convolutional Neuronal Network) as well as blob detection. [ABSTRACT FROM AUTHOR]

Electrochemical Machining (ECM) is an important advanced machining process useful to obtain good quality finish with a stress-free and crack free machined surface. Machining performance of the process is independent of the hardness of the material. Objective of this study is to assess the effect of process parameters of the ECM on material removal rate (MRR) and surface roughness (SR) during machining of EN-31 alloy steel. The EN-31 alloy steel is widely used in the manufacturing industry for making plastic molding dies, gears, automobile parts, etc. The machining experiments have been conducted according to the design of experiments based on Central Composite Face Centered Design (CCFCD) with three independent input parameters – voltage, electrolyte concentration and electrolyte flow rate, and two response parameters – material removal rate (MRR) and surface roughness (SR). Response Surface Methodology (RSM) has been used to develop the empirical relationship between the response parameters and the input process parameters. Optimization has been carried out to maximize the MRR and minimize the SR using desirability function. [ABSTRACT FROM AUTHOR]

Small and medium-sized enterprises (SMEs) in today's world have numerous issues in ensuring the availability and safety of critical machines and their components in the working environment. As a result, SMEs considered planning and scheduling maintenance tasks to be a significant threat. The goal of this research is to identify the critical subsystem of the automobile spare parts production plant in the southern region of Tamil Nadu, India, and then to prioritize the maintenance activity and set up an architecture for autonomous preventive maintenance (PM) in SMEs that includes an optimal decision support system. The transition state diagram of the individual and simultaneous production system has been developed with the application of the Markov decision model approach. It was used to analyze the present variables of the production systems and forecast the optimal maintenance parameters such as the failure rate and the repair rate, through the production system's availability analysis. This availability analysis reveals that system B (Piercing) is classified as the most critical because of the abrupt availability variation compared to all other production systems, concerning the corresponding maintenance parameters such as a failure rate of 0.0371, a repair rate of 0.7094, and the availability of the piercing system of 0.5056. Finally, the use of an autonomous PM management system and the most effective maintenance workforce has enhanced productivity and customer satisfaction in SMEs. The predictive maintenance management system has been further investigated to determine the real-time remaining useful life (RUL) of critical systems in the automobile spare parts manufacturing plant in the southern region of Tamil Nadu, India. [ABSTRACT FROM AUTHOR]

With the development of autonomous vehicles, activities in the indoor spaces of autonomous vehicles are diversifying. Therefore, as the operating range of the interior parts increases, the occupant becomes sensitive to the operating noise of autonomous vehicles. Therefore, to reduce operating noise, it is necessary to analyze the causal relationship between the mechanical/electrical noise characteristics of the motor and sound quality. In this paper, we propose a methodology to analyze the relationship between the noise frequency components and the sound quality of small motors used in automobile interior parts. Two types of motors were selected for this study, and noise measurements and analyses were performed by applying the design proposed in this study. Subjective sound quality evaluations were conducted using the 12 pairs of adjectives extracted from the survey. The results suggest that subjective sound quality evaluation scores should be converted to Z-scores to ensure the reliability of the statistical analysis. In addition, we present a critical sound quality value that can be used as a criterion for determining whether the sound quality is positive (good quality) or negative (bad quality). Sound quality regression models explain the causal relationship between rotational frequency components of the motor and subjective sound quality characteristics. Thus, a method for analyzing the effect of the rotational frequency component of the motor on the sound quality is presented, which suggests that it can be used as basic research data to improve the noise performance of the motor. [ABSTRACT FROM AUTHOR]

Progress in today's modern industry requires a lot of knowledge, one of which is scheduling. Flow-shop scheduling is one of the most widely used optimization problems. In this research, considering the importance of simultaneously order in different stages of production in the automotive industry, and also in order to make the problem more practical, we have investigated the problem of scheduling the flow-shop, taking into account the lead time and the costs of each order. Due to the fact that in most research studies, the lead time and costs of an order have been ignored because they made it difficult to find the initial solution to the problem. In this research, using the firefly meta-heuristic method, a suitable solution is provided to overcome this problem. Therefore, considered objective function is to minimize the total completion time. Absolute relative error (ARE) has been used to validate the model in a deterministic and meta-heuristic mode. According to the ARE result, the difference in the results between the two algorithms is negligible. Then, the sequence results are determined according to the desired algorithm for 5 tasks considered for automobile parts. The results show that the completion time of job 1 is 1397.85; job 2 is 771.44; job 3 is 608.65; job 4 is 1163.87; and job 5 is 479.45. [ABSTRACT FROM AUTHOR]

Advanced high-strength steel is widely used in automobile production and manufacturing, for its advantages of light weight, high strength, and good formability. Compared with common steel plate, higher forming forces are required during the stamping forming process of advanced high-strength steel plate due to its continuous strength improvement. The higher forming forces directly result in a sharp increase in the reactive force on the stamping die, which easily cause inevitable fatigue deformation and damage fracture. In view of the above problems, the stamping forming process of an advanced high-strength steel anti-collision beam part and the loading bearing condition of the stamping die were explored. On basis of the theory of topology optimization, the structure of the stamping die was optimized to obtain the qualified stamping parts and the lesser quality punch. A method based on the node contact force conversion was proposed, and the reactive force on the stamping die during the forming process was obtained to function as the load boundary condition of topology optimization. Geometric reconstruction of the stamping die was implemented referring to the topology optimization results. The final result reveals that the lightweight punch and the qualified stamping part without fatigue deformation can be efficiently achieved through topology optimization. [ABSTRACT FROM AUTHOR]

A great loss of transportation capacity has been caused in auto parts supply logistics due to the independent transportation from auto parts suppliers (APSs) to the automobile production line (APL). It is believed that establishing distribution centers (DCs) for centralized collection and unified distribution is one effective way to address this problem. This paper proposes a unified framework simultaneously considering the location-inventory-routing problem (LIRP) in auto parts supply logistics. Integrating the idea of sustainable development, a multi-objective MIP model is developed to determine the location and inventory capacity of DCs and routing decisions to minimize the total system cost and carbon emissions while concerning multi-period production demand. In addition, a robust optimization model is developed further in the context of uncertain demand. Numerical experiments and sensitivity analyses are conducted to verify the effectiveness of our proposed deterministic and robust models. The results show that synergistically optimizing the location and capacity of DCs and routing decisions are beneficial in reducing total system cost and carbon emissions. The analysis can provide guidelines to decision-makers for the effective management of auto parts supply logistics. [ABSTRACT FROM AUTHOR]

When developing an entire vehicle system, testing the structure of the vehicle or each component as a module or individually is necessary to determine the reliability and ensure the endurance of the entire vehicle. Various tests have been conducted to check the durability of the parts. However, the most important part is the verification of the fatigue limit of the load vibration from the road surface when the vehicle is being driven. Verification can be achieved by experimenting while driving on a real road with a prototype vehicle best suited to the actual conditions. However, issues such as problems in time, space, and environmental constraints, inconsistency in driving characteristics of the test driver, and continuous monitoring exist. For testing the load vibration of the road surface in automobile parts in the laboratory, hydraulic servo actuators are used because they provide vibrational loads in multiple directions by configuring them in multiple axes rather than a single axis. In this article, a multiple-input multiple-output model predictive control–proportional–integral–derivative hybrid controller is proposed as the method for optimal control of a multi-axis hydraulic servo actuator used in a random road signal reproduction experiment. Its performance is compared with the simple proportional–integral–derivative controller. A method for obtaining an efficient black box multiple-input multiple-output system model using LabVIEW in a laboratory in the field is also introduced, and the effectiveness of the model predictive control–proportional–integral–derivative hybrid controller is shown by reproducing the actual road load. [ABSTRACT FROM AUTHOR]

Cold forging dies are manufactured through the shrink fit process to withstand high pressure loads, but fatigue failure eventually occurs due to repeated compressive stresses. The life cycle until fatigue failure was defined as the limit life, and attempts were made to predict the die life based on finite element method. However, accurate prediction was impossible owing to uncontrollable environmental variables. Consequently, it is impossible to clearly determine the die replacement cycle, resulting in negative consequences such as poor quality, production delay, and cost increase. Various environmental factors affecting the prediction of die life cycle result in the increase or decrease of the forming load, which is an important variable that determines the die life cycle. In this study, a system for monitoring load data generated from forging facilities was developed based on a piezo sensor. In addition, the die life cycle was more accurately predicted by using the forming load data measured in real time, and a die life management system that can determine the die replacement cycle was applied to the automobile steering parts production line. [ABSTRACT FROM AUTHOR]

In Nigeria, packaging of fresh fruits and vegetables especially tomatoes is mostly done using traditional woven baskets from palm fronds. There is a belief that the introduction of reusable plastic crates (RPC) may take away the source of livelihood of basket makers and sellers who are majorly domiciled in the southeastern zone of Nigeria. The study assessed the potential socio-economic impact of replacing baskets with plastic crates for fresh tomato transportation on the livelihoods of basket makers in southeast Nigeria. Primary data were collected using structured questionnaires. Overall, 430 basket makers were drawn from 16 basket production villages in Anambra, Imo, Ebonyi and Enugu states of the southeast. The primary source of income for the majority of the respondents (90.6%) was basket making, with other sources of income being mostly trading (21.3%) and farming (18.6%). About 28.9% of the respondents' income was between N11,000 and N20,000, while 34.7% were earning less thanN10,00 and 36.4% earning above N20,000. As many as 76.7% were willing to diversify into other businesses, particularly trading (37.3%), provision selling (16%) and skilled work (10.6%). The major challenges identified in diversifying were shortage of capital (96.3%) and a lack of prerequisite skills (3.7%). These challenges could be resolved by government intervention (47.8%), provision of financial aid, (39.2%); new jobs (2.2%) and loans (3.2%). Alternative income-generating activities include opening a provision store, food selling, rearing of animals/animal husbandry, trading in automobile spare parts, fruit selling, meat selling, bakery and confectionary. The perceived impacts of replacing baskets with RPCs were joblessness, increased poverty, crime and prostitution, rural urban drift and a dwindling economy. It is thus recommended that plastic crate introduction should be gradual and systematic and basket makers should be properly sensitized and informed. Government and nongovernmental organizations should assist basket makers in mitigating the potential impact of replacing baskets with RPCs. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of the present work is to develop the combination of the radial point interpolation method (RPIM) with a bi-directional evolutionary structural optimization (BESO) algorithm and extend it to the analysis of benchmark examples and automotive industry applications. Design/methodology/approach: A BESO algorithm capable of detecting variations in the stress level of the structure, and thus respond to those changes by reinforcing the solid material, is developed. A meshless method, the RPIM, is used to iteratively obtain the stress field. The obtained optimal topologies are then recreated and numerically analyzed to validate its proficiency. Findings: The proposed algorithm is capable to achieve accurate benchmark material distributions. Implementation of the BESO algorithm combined with the RPIM allows developing innovative lightweight automotive structures with increased performance. Research limitations/implications: Computational cost of the topology optimization analysis is constrained by the nodal density discretizing the problem domain. Topology optimization solutions are usually complex, whereby they must be fabricated by additive manufacturing techniques and experimentally validated. Practical implications: In automotive industry, fuel consumption, carbon emissions and vehicle performance is influenced by structure weight. Therefore, implementation of accurate topology optimization algorithms to design lightweight (cost-efficient) components will be an asset in industry. Originality/value: Meshless methods applications in topology optimization are not as widespread as the finite element method (FEM). Therefore, this work enhances the state-of-the-art of meshless methods and demonstrates the suitability of the RPIM to solve topology optimization problems. Innovative lightweight automotive structures are developed using the proposed methodology. [ABSTRACT FROM AUTHOR]

During the development of an automobile part obtained by stamping process, time and money are required aiming process planning and setup of a new tooling. One of the difficulties in stamping is to know if the chosen material will have sufficient formability to reach the final form required by the project. Because of this difficulty, it is very interesting to propose a method that can accurately simulate the forming process. The failure criteria can be mathematical or empirical models capable of determining the onset of necking for each stress/strain states. It is interesting to find a failure criterion that can be easily determined and provides a good ability to detect the failure accurately. In this study, six different failure criteria were studied. Five of them are classified as ductile damage models and they depend on the stress triaxiality and plastic strain. The last criterion depends only on the deformations in the main directions and it is called the forming limit curve (FLC). Computational models through finite element analysis (FEA) were used. The formability was evaluated by monitoring the displacement of the punch until the failure of the material. Lou and Huh criterion and Johson-Cook criterion have been able to provide approximation errors in the range of 0.7–5% which makes them interesting for practical implementation in the industry. [ABSTRACT FROM AUTHOR]

Continuous process improvement is critical for organisations to stay in business. An automotive component manufacturer faced productivity challenges after the launch of a new hybrid C-SUV automobile in South Africa. This paper aims to improve the seat cover sewing process line through a line balancing technique. The use of process standard times to balance the production process initially led to bottlenecks, and the cycle time was above the takt time of the assembly line. Through the use of work-study analysis and time studies, the bottleneck processes were identified. Elements were then categorized, and kaizen implementation occurred at the processes. The processes were then rebalanced to meet the calculated cycle time. A root cause analysis was also conducted to investigate the sources of muda and the factors affecting the rate of working. The assembly line was then rebalanced, and the balance delay decreased by 33%. [ABSTRACT FROM AUTHOR]

The main motive of this paper is to prepare a newer composite material using non-conventional reinforcement (industrial waste) for various industrial applications. The aluminium alloy (Al-4032) matrix based composites (AMCs) have been fabricated through bottom pouring stir casting method. The granite powder (GP, ceramic particles) obtained from waste (normally available from construction site) has been used as reinforcement, at 0, 3, 6, 9 % by weight. The particle size of the reinforcement has been up to 54μm. The morphological (microstructure, SEM, XRD) and mechanical (tensile strength, micro-hardness, impact strength) characterization of the AMCs have been carried out. The morphological study reveals that the reinforcement particles (GP) are almost uniformly distributed throughout the matrix phase. The mechanical properties of the AMCs have been observed to be better than the unreinforced alloy. It is expected that the fabricated Al-4032-GP composites will be useful for the automobile parts like piston, disc brakes, high speed machinery and high-speed rotating parts etc. [ABSTRACT FROM AUTHOR]

Aluminum alloy is widely used in automobile parts because of its light weight and good process performance. In view of the complex structure of aluminum alloy automobile rear upper control arms, multiple forming processes and the difficulty in quality control, in this paper, we propose a rolling-forging composite process to produce a rear upper control arm. Based on the reasonable volume distribution of the blank by cross-wedge rolling, multi-step forging was carried out. Finite element simulation of thermomechanically coupled multi-step forming was carried out using DEFORM software. Based on a comparison of the traditional process and the proposed rolling-forging composite forming process, we concluded that the rolling-forging composite process can greatly reduce the material cost and the forming force, resulting in superior product performance. The coarse-grain structure of products at different process temperatures was analyzed by a crystal-phase experiment. The results show that the process temperature of the multi-step process, as well as the heat treatment temperature and time have an important influence on the coarse-grain structure of the product. The optimal preheating temperatures for preforging and final forging dies were determined to be 335 °C and 350 °C, respectively; a preheating temperature of 530 °C and a solution time of 45 min resulted in the least coarse-grain surface structure. The research results provide a theoretical basis for improving the multi-step forming quality of automobile rear upper control arms. [ABSTRACT FROM AUTHOR]

Aspect ratio is a critical parameter of bamboo fiber (BF), and is not well defined for the bending properties of BF composite for automobile inner parts. In this study, six different types of BF were extracted and tensile tested that 20–130 mm in length and 483–713 in aspect ratio, then mixed with polypropylene (PP) fiber which has been added 5%wt maleic anhydride grafted polypropylene by non-fabric and heat pressing technology. The results present that the bending performance of BF composite is the best when the BF aspect ratio is 600–700; and the modified Halpin–Tsai equation with anisotropic material factor can approximate fitting out the relationship between BF aspect ratio and bending modulus of BF/PP composite. Polyvinyl alcohol can effectively enhance the three dimensional (3D) cross structure of non-fabric mats showed by optical microscopy images, so as improve the bending modulus of 12%. [ABSTRACT FROM AUTHOR]

With the consistent advancement and technical improvisation in the automobile industry, the researchers are working on the material optimization techniques to select and utilize the materials effective in power transmission. It is well know that power transmission systems in the mechanical industries and, namely, in automotive machinaries, require a durable material with proper properties to ensure the optimum operational conditions during power transmission. The material utilized in the driving shaft must have a proper endurance and considerable yielding limit that means they have that ability to sustain the fatigue in the power transmission elements. The method of study is that engine shafts are a major part of the automobiles and the production of these shafts is an important requirement for the resistance against bending and torsion. The torsion and bending resisting moments are important before selecting the material. As a result, selecting the optimal material and surface treatment procedure to offer the highest performance for the shaft is crucial. Wear resistance and corrosion resistance are the two most important factors to consider when selecting a material for a surface. This paper is able to show the effect of materials of the crankshaft on those two elements. The research discusses the shafts of three different types of materials: homogeneous, composite, and functionally graded materials (FGM). For the optimum performance of the vehicle engine shaft, FGM is the ideal material to consider. It has been shown that the performance of crankshaft was improved in case of FGM. Based on the results of the modal and harmonic analysis, it is concluded that FGM crankshaft would offer the best durability and show optimum performance when compared with the other two material crankshafts investigated in this study. [ABSTRACT FROM AUTHOR]

A dual-mass flywheel is an important part of an automobile transmission system whose function is to ensure the smooth transmission of engine power to a gearbox. Vehicle vibration and noise are major indicators of vehicle comfort, while dual-mass flywheel technology can preferably solve the comfort problem. Based on the created torsional vibration model, this paper describes the testing of the torsional characteristics under various conditions with an LMS AMESim simulation. The results show that the noise in the cab is fundamentally below 60 dB. The computational formula for the angular stiffness of an arc coil spring is derived, and then the spring angular stiffness is optimized with arithmetic averaging, which reveals an adjusted angular stiffness of 12.8 Nm/°. Additionally, the requirement for the angular acceleration of the WOT input shaft (i.e., being less than 500 rad/s2) is satisfied for various gears. The test results show that the double-mass flywheel can attain a vibration isolation efficiency of around 85%, which more effectively reduces the transmission vibration and noise and improves the vehicle comfort. [ABSTRACT FROM AUTHOR]

[Display omitted] • Circular economy practices are identified for circular supply chain implementation. • Sustainable development goals are derived due to circular economy practices adoption. • An empirical case example of Indian automobile part manufacturing organization is considered. • The proposed framework is analyzed through hybrid PF-AHP and PF-CODAS approach. • Sensitivity analysis is conducted to check the effectiveness of proposed framework. Recently, the novel concept of the circular supply chain (CSC) has gained substantial attention amongst researchers across the globe. It is due to the issues of unsustainability in supply chain operation of manufacturing industry. CSC amalgamates the circular economy (CE) into the supply chain of manufacturing organizations. Business organizations can achieve several sustainable development goals by adopting CSC as an innovative strategy. However, limited attention has been given to its implementation in emerging economies. Thus, this research aim is to identify and analyze the essential CE practices that help to accomplish the several sustainable development goals (SDGs) of CSC management. This research presents an integrated framework of Pythagorean fuzzy analytic hierarchy process (PF-AHP) and Pythagorean fuzzy combinative distance-based assessment (PF-CODAS) techniques. PF-AHP is employed to determine the relative importance of CE practices, whereas PF-CODAS method ranks the SDGs derived due to the adoption of CE practices. The effectiveness of the proposed framework is validated with the help of an Indian manufacturing organization. The finding of this research reveals that practices based on 'government', 'management', and 'economy' initiatives play a significant role and contribute 50 % of its influence on the effective CSC adoption, whereas, 'mitigate waste and enhance environmental sustainability', is identified as the most critical SDG realized due to adoption of CE practices. Sensitivity analysis is conducted to check the robustness of proposed methods. This research provides the systematic, accurate, and valuable decision support tools to practitioners to execute the CE practices efficiently for achieving the various sustainability goals. [ABSTRACT FROM AUTHOR]

This paper focuses on providing economical methods for manufacturing of hot die steel inserts, for various optimized solutions developed the constraint of the existing manufacturing setup is also considered. The techniques are implemented on a pressure die casting moving die insert component. The present optimized solution is derived for manufacturing rope length minimization of the die casting inserts (moving and fixed die) to get optimized solutions at every stage. The implementation of combined electrode, combined assembly machining and the cluster plate machining techniques are the key development done in the research. Combined electrodes, assembly machining along with cluster machining of the electrodes reduce the total physical operational time of the die which will ultimately leads to saving the overall manufacturing cost and increase the profit The proposed solution opens up new avenues for similar automobile components by setting benchmark to decrease the rope length associated to manufacturing and increase the profit. [ABSTRACT FROM AUTHOR]

At present, in China's automobile manufacturing industry, the main problem is the manufacturing of parts and on-board equipment. Most domestic industries still adopt the step-by-step production of parts, and each manufacturer customizes the required parts according to the scale and production needs of its own enterprise. This situation is easy to cause unstable quality of parts and serious unqualified quality inspection problems. Based on the above situation, we study the high-quality development, parts quality optimization, and remanufacturing of auto parts manufacturing industry with the support of machine learning model. Firstly, based on the analysis of auto parts procurement and production mode, this paper briefly describes the basic problems in the manufacturing process of auto parts in China. Machine learning technology is used to count the changes of quality data in manufacturing, and the quality standard is reflected in the learning model. The machine learning algorithm is used to diagnose and analyze the faults of auto parts and equipment, so as to turn high-quality production to high-quality production. The projection feature extraction algorithm is used to quantitatively analyze the low quality state of automobile parts. Finally, 3D printing technology is used to solve the quality manufacturing problem of parts with high-precision requirements, and the later materials are processed again to achieve the purpose of remanufacturing planning. The results show that the transformation of auto parts manufacturing to high quality can improve the economic development of the auto industry and meet the needs of modern society. The data analysis of parts controlled by machine learning model can help the precision manufacturing of automobile parts. [ABSTRACT FROM AUTHOR]

Low-carbon process planning is the basis for the implementation of low-carbon manufacturing technology. And it is of profound significance to improve process executability, reduce environmental pollution, decrease manufacturing cost, and improve product quality. In this paper, based on the perceptual data of parts machining process, considering the diversity of process planning schemes and factors affecting the green manufacturing, a multi-level evaluation criteria system is established from the aspects of processing time, manufacturing cost and processing quality, resource utilization, and environmental protection. An integrated evaluation method of low-carbon process planning schemes based on digital twins is constructed. Each index value is normalized by the polarized data processing method, its membership is determined by the fuzzy statistical method, and the combination weight of each index is determined by the hierarchical entropy weight method to realize the organic combination of theoretical analysis, practical experience, evaluation index, and process factors. The comprehensive evaluation of multi-process planning schemes is realized according to the improved fuzzy operation rules, and the best process planning solution is finally determined. Finally, taking the low-carbon process planning of an automobile part as an example, the feasibility and effectiveness of this method are verified by the evaluation of three alternative process planning schemes. The results show that the method adopted in this paper is more in line with the actual production and can provide enterprises with the optimal processing scheme with economic and environmental benefits, which may be helpful for more data-driven manufacturing process optimization in the future. [ABSTRACT FROM AUTHOR]

Aiming at the selection of modern auto parts design schemes, an evaluation method of automobile parts design scheme for intelligent manufacturing is proposed. Considered the environment-friendly factors and traditional manufacturing factors, the evaluation index system of automobile parts design scheme was established, which taken technology, environment, economy and quality reliability as the first level evaluation index, and 12 second level indexes under the first level index. The game theory method was used to comprehensively consider the proportion of subjective and objective weights to determine the composite weight of each index. Aimed at the certainty and uncertainty of the evaluation index, the set pair analysis relative closeness method was used to calculate the composite weight and established the model. Three sets of automobile panel design schemes of a company were selected, and the mathematical model was used to calculate them. With the help of C language program, the advantages and disadvantages of the three design schemes were evaluated, and the optimal scheme was obtained. The calculation example proves that the method is true and effective, conforms to the background of modern intelligent manufacturing, and the calculation is simple, and has good feasibility and practicability. [ABSTRACT FROM AUTHOR]

7000 series high strength aluminum alloys are increasingly used in manufacturing automobile body parts to meet the more stringent demands for automobile lightweight. Hot stamping of 7000 series high strength aluminum alloys is a complex thermal-mechanical coupling process and precise simulation is needed to predict material fracture. To obtain damage model of 7075 aluminum alloy in hot stamping, five different stress triaxiality specimens were designed. The fracture strain, critical strain and average stress triaxiality of different specimens were obtained by the hybrid finite element simulation and experiment (FE-EXP) method. GISSMO model of 7075 aluminum alloy at 400 °C was established. Compared with the experimental results of U-shaped part hot stamping under different lubrication conditions, the calibrated GISSMO model was demonstrated to predict the damage behavior of 7075 aluminum alloy during high temperature deformation accurately. [ABSTRACT FROM AUTHOR]

The application of flame retardants in automobiles is extensive, and the existing flame retardants will cause some pollution to the environment. Therefore, environmentally friendly flame retardants need wide exploration. Natural fibers have been used in various fields for their environmentally friendly features. Thus, in this paper, hemp fiber (HF) was modified with phytic acid and then combined with melamine cyanurate to improve the fire safety of unsaturated polyester resins (UPRs). The fire behavior and thermal stability of UPR composites were evaluated using the limiting oxygen index (LOI), cone calorimeter test, and thermo-gravimetric analysis (TGA). With 3 wt. % modified HF (HF-P) incorporation, the LOI value of UPR/HF-P-3 composites increased from 18.9% of pure UPR to 22.1%, and the average heat release rate (AHRR) and total heat release were reduced to 401.9 kW/m2 and 150.6 MJ/m2, respectively. TGA revealed that UPR/HF-P-3 composites led to the increased amount of residual char and better thermal stability compared to UPR/HF composites. In addition, HF-P endowed a better enhancement on the flexural strength of UPR composites. [ABSTRACT FROM AUTHOR]