Car Paint Research Articles

Conversion of volatile organic compounds in a twin surface dielectric barrier discharge

A voltage and power controlled surface dielectric barrier discharge for the removal of volatile organic compounds (VOCs) from gas streams is studied by means of current–voltage measurements, flame ionization detectors, and gas chromatography–mass spectrometry (GC–MS). The discharge is generated in a defined synthetic air gas stream at atmospheric pressure by application of a damped sinusoidal voltage waveform resulting from a resonant circuit. Multiple organic compounds, namely n-butane, butanol, isobutanol, ethyl acetate, diethyl ether, and butoxyethanol, are tested at concentrations of 50, 100, 200, and 400 ppm (parts per million), as well as peak-to-peak voltages of 8 to 13 kVpp and pulse repetition frequencies of 250 to 4000 Hz. The dissipated power within the system is calculated utilizing the measured voltage and current waveforms. The conversion and absolute degradation of the VOCs are determined by flame ionization detectors. An increasing concentration of VOCs is found to increase the dissipated power marginally, suggesting a higher conductivity and higher electron densities in the plasma. Of the applied VOCs, n-butane is found to be the most resistant to the plasma treatment, while higher concentrations consistently result in a lower conversion and a higher absolute degradation across all tested compounds. Corresponding amounts of converted molecules per expended joule are given as a comparable parameter by weighting the absolute degradation with the dissipated power. Finally, specific reaction products are determined by online GC–MS, further confirming carbon dioxide (CO2) as a major reaction product, alongside a variety of less prevalent side products, depending on the structure of the original compound. The findings of this study are intended to promote the development of energy efficient processes for the purification of gas streams in both, industry and consumer market. Potential applications of the presented technique could be found in car paint shops, chemical plants, hospital ventilation systems, or air purifiers for living space.

Biomarkers of susceptibility and effect in car painters exposed to organic solvents.

Introduction: Car painters are routinely exposed to organic solvents classified as carcinogenic and mutagenic substances. Objective: To characterize the population susceptibility and evaluate the genotoxic effects of exposure to organic solvents. Methods: A cross-sectional study comparing a group of car painters exposed to organic solvents with a non-exposed group. CYP2E1 polymorphisms and the presence of micronuclei in lymphocytes were determined. Results: One hundred twenty-two workers participated in the study: 62 who worked in car paint shops and were exposed to solvents, and 60 who were not exposed. There were statistically significant differences between the two groups regarding micronucleated cells and nucleoplasmic bridges frequencies (p= 0.042 and p= 0.046, respectively; exact likelihood ratio). Significant differences were found at the interaction between the CYP2E1 genotype c1c1 and occupational exposure to solvents, with higher frequencies of micronuclei (p= 0.013) and micronucleated cells (p= 0.015). However, when the frequencies of micronuclei, micronucleated cells and nucleoplasmic bridges in the exposure group were compared between the c1c1 and c2c2/c1c2 allele groups of the CYP2E1 polymorphism, statistically significant differences were found. Conclusions: This study confirms that when workers with CYP2E1 polymorphisms, specifically the c1c1 genotype, are exposed to organic solvents, they are more likely to have somatic cell mutations, a condition associated with increased susceptibility to diseases such as cancer

Temperature dependence of source profiles for volatile organic compounds from typical volatile emission sources

Source profiles of volatile organic compounds (VOCs) emitted from the evaporation of various fuels, industrial raw materials, processes and products are still limited in China. The impact of ambient temperature on the VOC released from these fugitive emission sources has also been rarely reported. In order to establish VOC source profiles for thirteen volatile emission sources, a sampling campaign was conducted in Central China, and five types of sources were investigated both in winter and summer. The dominant VOC groups varied in different sources, and they were alkanes (78.6%), alkenes (53.1%), aromatics (55.1%), halohydrocarbons (80.7%) and oxygenated VOCs (OVOCs) (76.0%), respectively. Ambient temperature showed different impacts on VOC source profiles and specific species ratios. The mass percentages of halohydrocarbons emitted from color printing and waste transfer station in summer were 42 times and 20 times higher than those in winter, respectively. The mass percentages of OVOCs emitted from car painting, waste transfer station and laundry emission sources were much higher in summer (7.9–27.8%) than those in winter (0.8–2.6%). On the contrary, alkanes from color printing, car painting and waste transfer stations were about 11, 4 and 5 times higher in winter than those in summer, respectively. The coefficient of divergence values for the source profiles obtained in winter and summer ranged in 0.3–0.7, indicating obvious differences of source profiles. Benzene/toluene ratio varied in 0.00–0.76, and it was in the range of 0.02–0.50 in winter and 0.04–0.52 in summer for the same sources, respectively. Hexanal, isobutene, m,p-xylene, toluene, 2-methylacrolein, styrene, 1-hexane and cis-2-butene dominated the ozone formation potentials (OFP). The OFP summer/winter differences were 5–320 times by MIR method and 1–79 times by Propy-Equiv method, respectively. This study firstly gave direct evidence that ambient temperature modified the mass percentages of VOC species obviously. It is important for improving VOC source apportionment and chemical reactivity simulation.

Determination Reference of Concentration (RfC) Xylen Exposure Based on Xylen NOAEL in White Rats and Workers’ Body Weight and Height in Surabaya Car Painting Area, Indonesia

This study aims to calculate the value of RfC from xylen exposure around the car painting area of �Surabaya, Indonesia. This is an observational cross-sectional study with quantitative data analysis methods conducted manually. The population in this study was groups of car painting workers and groups of car repairer on Jalan Pengenal Kota Surabaya. The sampling technique was proportionate stratified random sampling to take 51 people. The measurement of xylen concentration around the car painting area was 635.98 mg/m3 (146.47 ppm). This value is above the threshold value according to Minister of Manpower and Transmigration Regulation Number 13 of 2011 and Minister of Manpower Regulation Number. 5 of 2018 is 434 mg/m3 (100 ppm). RfC of car painting workers with NOAEL 50 mg/kg was 7.76 mg/kg. © 2020, Indian Journal of Forensic Medicine and Toxicology. All rights reserved.

Procedural generation of materials for real-time rendering

The use of Procedural Content Generation techniques in the production of Video Games has seen a large diffusion in these last years. Regarding the procedural generation of Computer Graphics content, several works have been proposed about the automatic construction of complex models and environments, or about the instancing of several copies of a reference model, each with peculiar differences to introduce variety. However, very few works have proposed techniques for the procedural production of complex materials to be assigned to these generated models. In this paper, we present a method for the automatic generation of realistic layered materials based on the application of a Genetic Algorithm. We show that, with the proposed approach, is possible to generate several instances of a target material (e.g., a car paint, or a rusty metal), maintaining a desired level of closeness to the overall characteristics of the simulated interaction between the light and the surface, but introducing also a controlled amount of differences in the final reproduction of the perceived appearance.

Source Composition Spectrum of Volatile Organic Compounds in Typical Industries in Sichuan

In this study, typical industries that act as sources of volatile organic compound (VOCs) emission in Sichuan, including automobile manufacturing, wooden furniture, wood-based panel manufacturing, and paint production, were selected and GC-MS national standard analysis to study the organized emission VOC components of every procedure. The spectra of VOCs in the automobile industry were obtained by means of total emission normalization. The results showed that the VOC components of automobile manufacturing, wooden furniture, and oil paint manufacturing enterprises were mainly aromatic hydrocarbons and oxygen-containing compounds, accounting for more than 70% of total VOCs; the emissions from automobile part manufacturing enterprises were mainly aromatic hydrocarbons, with a ratio of over 90%. The proportion of oxygen-containing compounds in the wood-based panel manufacturing industry was found to be up to 97%, mainly caused by the emission of formaldehyde, which accounts for 75%, followed by isopropanol, acetone, and other substances. The proportion of aromatic hydrocarbon and olefin in synthetic resin enterprises is relatively high at over 80%. The olefin species are mainly 1,3-butadiene and 1-butene. Although there are some differences in emission species between different industries, they are mainly composed of aromatic hydrocarbons and oxygenates. Therefore, it is necessary to improve the identification and control of components with high concentration, activity, and toxicity for aromatic hydrocarbons and oxygenates. The source, process, and end process control should be monitored to achieve the effect of total emission reduction.

A novel ternary mica-titania@rGO composite pearlescent pigment for the photocatalytic degradation of gaseous acetaldehyde

The photocatalytic application of TiO2 is limited due to low light harvesting abilities in the whole solar spectrum and fast recombination of the photoinduced electron-hole pairs. Herein, we report a TiO2-based ternary composite photocatalyst (MT@rGO-x; x = 0.05–0.2) with a pearlescent color effect, which incorporates a mica reflection core and a rGO multifunctional shell as cocatalysts. The micro flake composites were synthesized by a facile precipitation route and applied first to photodegrade gaseous acetaldehyde. MT@rGO-0.1 composite has optimal performance, which is 2.5 times photodegradation efficiency and 3 times CO2 mineralization efficiency higher than those of pure TiO2. The enhanced photocatalytic performance of MT@rGO composite is associated with effectively improved light harvesting of TiO2 by mica reflection. The presence of rGO facilitates the separation of electron-hole pairs and pollutant absorption. In addition, the superoxide radical was proved as the decisive active species for the photodegradation of acetaldehyde by electron spin resonance analyses and radical quenching tests. Our MT@rGO photocatalyst is expected to be applied as a functional and decorative additive of car paint, which is subject to photodegradation due to air pollutants.

Improving discrimination of Raman spectra by optimising preprocessing strategies on the basis of the ability to refine the relationship between variance components

Discrimination of the samples into predefined groups is the issue at hand in many fields, such as medicine, environmental and forensic studies, etc. Its success strongly depends on the effectiveness of groups separation, which is optimal when the group means are much more distant than the data within the groups, i.e. the variation of the group means is greater than the variation of the data averaged over all groups. The task is particularly demanding for signals (e.g. spectra) as a lot of effort is required to prepare them in a way to uncover interesting features and turn them into more meaningful information that better fits for the purpose of data analysis. The solution can be adequately handled by using preprocessing strategies which should highlight the features relevant for further analysis (e.g. discrimination) by removing unwanted variation, deteriorating effects, such as noise or baseline drift, and standardising the signals. The aim of the research was to develop an automated procedure for optimising the choice of the preprocessing strategy to make it most suitable for discrimination purposes. The authors propose a novel concept to assess the goodness of the preprocessing strategy using the ratio of the between-groups to within-groups variance on the first latent variable derived from regularised MANOVA that is capable of exposing the groups differences for highly multidimensional data. The quest for the best preprocessing strategy was carried out using the grid search and much more efficient genetic algorithm. The adequacy of this novel concept, that remarkably supports the discrimination analysis, was verified through the assessment of the capability of solving two forensic comparison problems - discrimination between differently-aged bloodstains and various car paints described by Raman spectra - using likelihood ratio framework, as a recommended tool for discriminating samples in the forensics.

Applied Research of Industrial Robots in Automotive Intelligent Manufacturing Production Line

In recent years, most Chinese car manufacturers have seen the use in industrial robots as the key to intelligent transformation in the car manufacturing industry. Industrial robots consist of several major divisions of labor, with the technical advantages of a small footprint and high availability, which can improve the work efficiency of the automobile manufacturing industry. Therefore, it is fully utilized in various fields of intelligent manufacturing production lines for automobiles, such as material mixing, car body painting, car body welding, and vehicle assembly. This article introduces the application status and characteristics of industrial robots and describes industrial robot applications in the intelligent manufacturing line of automobiles.

Complex Workpiece Positioning System With Nonrigid Registration Method for 6-DoFs Automatic Spray Painting Robot

To reduce the labor effort in hazardous environments like spray painting, an automatic car part spray painting machine has been set up. This article presents an intelligent location procedure for this machine. The location procedure assumes that the car part is placed with a tiny arbitrary pose, furthermore some kinds of parts under inspection undergoes through the deformation and thus it contains a nonrigid model. To tackle this problem, a workpiece positioning system works though multicamera is established first. Subsequently, a novel modified iterative closest point (ICP) algorithm is proposed which registers the nonrigid shape to the undeformed source shape in the training library. The modified ICP combines the ideas from traditional ICP and deformation estimation from bounded biharmonic weights. It solves a nonlinear cost function by using Levenberg–Marquardt algorithm. As a result, it estimates the transformation of the target point cloud with regards to the source point cloud. Additionally, it improves the accuracy of traditional ICP and increases its scope to nonrigid shapes. By employing these results in our location procedure, it can estimate the 6-DOF pose of the car part to be painted in addition to that it also estimates the deformation compared to the source cloud in the training library. This information is subsequently used to modify the guidance trajectory of the spray gun. In this article, a test case of front bumper is given, as it is commonly made of soft plastic materials and undergoes deformation under the influence of the external force. All the stated results support the efficacy of our algorithm.

Polarization-coded material classification in automotive LIDAR aiming at safer autonomous driving implementations.

LIDAR sensors are one of the key enabling technologies for the wide acceptance of autonomous driving implementations. Target identification is a requisite in image processing, informing decision making in complex scenarios. The polarization from the backscattered signal provides an unambiguous signature for common metallic car paints and can serve as one-point measurement for target classification. This provides additional redundant information for sensor fusion and greatly alleviates hardware requirements for intensive morphological image processing. Industry decision makers should consider polarization-coded LIDAR implementations. Governmental policy makers should consider maximizing the potential for polarization-coded material classification by enforcing appropriate regulatory legislation. Both initiatives will contribute to faster (safer, cheaper, and more widely available) advanced driver-assistance systems and autonomous functions. Polarization-coded material classification in automotive applications stems from the characteristic signature of the source of LIDAR backscattering: specular components preserve the degree of polarization while diffuse contributions are predominantly depolarizing.

Production scheduling problem in a factory of automobile component primer painting

In a factory of automobile component primer painting, various automobile parts are attached to overhead hangers in a conveyor line and undergo a series of coating processes. Thereafter, the components are wrapped at a packaging station. The packaging process should be fully balanced by an appropriate sequence of components to prevent the bottleneck effect because each component requires different packaging times and materials. An overhead hanger has a capacity limit and can hold varying numbers of components depending on the component type. Capacity loss can occur if the hanger capacity is not fully utilized. To increase hanger utilization, companies sometimes mix two or more component types on the same hangers, and these hangers are called mixed hangers. However, mixed hangers generally cause heavy workload because different items require additional setup times during hanging and packing processes. Hence, having many mixed hangers is not recommended. A good production schedule requires a small number of mixed hangers and maximizes hanger utilization and packaging workload balance. We show that the scheduling problem is NP-hard and develop a mathematical programming model and efficient solution approaches for the problem. When applying the methods to solve real problems, we also use an initial solution-generating method that minimizes the mixing cost, set a rule for hanging the items on hangers considering eligibility constraint, and decrease the size of tabu list in proportion to the remaining computational time for assuring intensification in the final iterations of the search. Experimental results demonstrate the effectiveness of the proposed approaches.

Forensic evaluation and comparison of Indian automobile paint chips using FTIR

Identification of trace evidence is one of the most challenging aspects, especially in criminal and road accident investigations, where automobile paint chips may acquit as substantial evidence. In a hit and run case, the trace evidence of automobile paint can be found from the victim as well as from the crime scene by following Principle of Exchange. This study undertaken to assess the comparison of Indian automobile paint chips wherein distinguishing patterns of solubility and profiling of functional groups using FTIR can be done. The present study carried out on 40 samples of Indian automobiles of 2 different companies (Mahindra and Mahindra and Ashok Leyland). The solubility test results have shown that all the paint samples of both the automobile companies gave reactions to different chemical solvents. Out of five different chemical solvents, almost all the samples got solubilised in sulphuric acid with various observations and gave the least reaction in Acetone. The attenuated total reflectance infrared spectroscopy gave effective results to characterise the clear coats from a collection of automotive paint samples representing 10 vehicles. The results shown that Urethane present in almost all the paint samples but amines and hydroxyl group was prominent in the samples of Mahindra and Ashok Leyland respectively with some other resin components. In this study, a database has been created based on solubility and FTIR analysis.

ANOVA and regression model of slurry erosion parameters of a polymeric spray paint film

In this paper, slurry erosion behaviour of a polymeric paint film coated on steel and impacted with silica was investigated. The investigated spray paint is commonly used in automobile paint systems to provide protection against mechanical and corrosive damages. Slurry erosion tests were conducted on the designed samples to investigate the effect of the common slurry erosion parameters, namely, slurry concentration, impact angle, and impact velocity, on the mass loss of the paint material as a response. Analysis of variance (ANOVA) was used to study the contribution of the individual parameters and investigate the significant effect of them on the mass loss of the paint material. Moreover, a regression model was developed based on the ANOVA results to predict the response (mass loss) in terms of different values of the input parameters. The developed regression model was validated with the experimental results and found to be feasible. The results revealed that the slurry erosion increases by increasing the slurry concentration and impact velocity. In addition, the rate of erosion increases with the increase of the impact angle until the angle reaches 66°. Furthermore, the ANOVA illustrated that slurry concentration and impact angle are the most significant parameters influencing the mass loss of the paint material, whilst the impact velocity had the less significant impact. The obtained statistical results were confirmed by conducting extra experimental works.

ANOVA and regression model of slurry erosion parameters of a polymeric spray paint film

In this paper, slurry erosion behaviour of a polymeric paint film coated on steel and impacted with silica was investigated. The investigated spray paint is commonly used in automobile paint systems to provide protection against mechanical and corrosive damages. Slurry erosion tests were conducted on the designed samples to investigate the effect of the common slurry erosion parameters, namely, slurry concentration, impact angle, and impact velocity, on the mass loss of the paint material as a response. Analysis of variance (ANOVA) was used to study the contribution of the individual parameters and investigate the significant effect of them on the mass loss of the paint material. Moreover, a regression model was developed based on the ANOVA results to predict the response (mass loss) in terms of different values of the input parameters. The developed regression model was validated with the experimental results and found to be feasible. The results revealed that the slurry erosion increases by increasing the slurry concentration and impact velocity. In addition, the rate of erosion increases with the increase of the impact angle until the angle reaches 66°. Furthermore, the ANOVA illustrated that slurry concentration and impact angle are the most significant parameters influencing the mass loss of the paint material, whilst the impact velocity had the less significant impact. The obtained statistical results were confirmed by conducting extra experimental works.

The Analysis of Determine The Criteria of Car Painting Service Quality

Pertumbuhan kendaraan bermotor memberikan kesempatan kepada bisnis bengkel pengecatan mobil. Dewasa ini bisnis bengkel pengecatan mobil meningkat dan persaingan untuk memenuhi keinginan konsumen. Persaingan bisnis bengkel pengecatan mobil semakin ketat karena keinginan konsumen yang dinamis. Hal ini dikarenakan bisnis bengkel pengecatan mobil menawarkan pilihan jasa pengecatan sesuai dengan permintaan konsumen. Ogick Paint Art merupakan salah satu bengkel pengecatan mobil, perbaikan kendaraan dan modifikasi yang menerima hampir semua pengerjaan pengecatan seperti sepeda motor, mobil, dan aksesoris kendaraan bermotor lainnya. Tujuan dai penelitian ini adalah untuk mengidentifikasi bagaimana memperoleh kriteria kualitas yang sesuai dengan keinginan konsumen menggunakan kuesioner Voice of Customer (VoC). Data yang telah diperoleh dari kuesioner Voice of Customer (VoC) kemudian akan digunakan sebagai panduan dalam membangun House of Quality (HoQ). Berdasarkan perhitungan House of Quality (HoQ) diketahui bahwa kriteria kualitas yang memiliki nilai prioritas paling tinggi adalah daya tahan kilap dan daya tahan intensitas warna yang memperoleh nilai 5 dari nilai tingkat kepentingan konsumen. Sedangkan peringkat kepentingan spefikasi teknis tertinggi adalah 251.29 dengan nilai kepentingan absolut dan nilai kepentingan relatif secara berutut-turut adalah 81,87 dan 7,23% untuk spesifikasi teknis kesesuaian rasio pernis dan hardener.

Automotive painting process: Minimizing energy consumption by using adjusted convective heat transfer coefficients

The process of drying/curing automobile painting is characterized as one of the main stages in automobile assembly. To guarantee the final painting quality, optimal operating conditions (mainly the temperature profile in the painting chamber) must be satisfied, and they are empirically defined in most cases. The availability of a mathematical model in transient regime enables the prediction of the drying/curing process behavior and consequences of possible operational changes on the final quality of the paint. However, obstacles continue to exist with respect to the implementation of the aforementioned types of models given the large number of parameters and complexity involved in their determination among which convection heat transfer coefficients are notable. Thus, the study presents a methodology to adjust the mathematical model of a paint-curing oven via determining convection heat transfer coefficients based on industrial data. The adjusted model was used to predict new operational scenarios for the most commonly used oven in automobile painting processes, namely the Elpo oven. The results indicate that the proposed methodology can be applied as a tool to develop operational optimization strategies that result in decreasing rework and energy costs without compromising painting quality.

Manufacturing of sustainable ceramics with improved mechanical properties from hazardous car paint waste to prevent environment pollution

Paint waste sludge (PWS) is one of the most polluted wastes of automobile construction industry. The main objective of this study was the experimental control of the neutralization of hazardous PWS (up to 20 wt%) in kaolin clay composites during the sintering of their mixtures at temperatures of 1000 °C, 1050 °C, 1100 °C, 1150 °C, 1200 °C, 1250 °C, and 1300 °C in order to manufacture environmentally clean white ceramics. These raw materials and the developed ceramics were characterized by following methods: X-ray diffraction, X-ray fluorescence, atomic absorption spectroscopy, energy-dispersive spectroscopy, and laser micro-mass analyses. The flexural resistance of the ceramics reached 12.77 MPa, the linear shrinkage varied between − 3.32 and 11.29%, the water absorption values ranged between 1.61 and 3.02%, and the density diverged from 1.53 to 1.62 g/cm3. These numbers significantly exceeded the values of the control samples without PWS during ceramics sintering at all temperatures. The decomposition of the crystalline structures of kaolin, gibbsite, muscovite, barite, and calcite was determined; instead, small amounts of mullite and cristobalite crystals with a high prevalence of glass-like amorphous material appeared. The values of the experimental leaching and solubility tests of heavy metals from the developed ceramics were significantly lower than those permitted by Brazilian standards. So, high values of mechanical and chemical properties of the developed ceramics permit to utilize PWS as valuable raw material for production of environmentally clean white bricks, blocks, and tiles and to decrease ecological damage of automobile industry.

Forensic analysis of automobile paint of Indian company

Forensic analysis of automobile paint of Indian company

Risk assessment of human exposure to potentially toxic metals in indoor dust from some small and medium scale enterprise workplace environments in southern Nigeria

This study concerns an assessment of indoor dust from printing press, car spray painting and metal design workshops, with the aim of evaluating the occupational risk arising from exposure to metals present in the dust. The levels of Cd, Pb, Cr, Ni, Cu, Co, Mn, Zn and Fe in the dust samples were quantified by means of atomic absorption spectrometry. The concentrations of metals (mg kg−1) in the indoor dust from these workplace environments varied from <0.003–208 for Cd, 26.5–1530 for Pb, 7.80–346 for Cr, 10.5–490 for Ni, 32.0–1915 for Cu, 3.50–232 for Co, 169–20,300 for Zn, 87.5–7260 for Mn and 8900–661,000 for Fe. The hazard index values were above one for different age groups except for the exposure of teenagers and adults to metals in dusts in the printing press studios and car spray painting workshops. The carcinogenic risk for all age groups relating to human contact with metals (Cd, Pb, Cr and Ni) in dust from these workplace environments via three exposure pathways: oral ingestion, inhalation and dermal contact, were above the safe level of 1.0 × 10−6 but not up to the level (1.0 × 10−4) that requires remedial action.