Car Paint Research Articles

Influence of Reclaimed Water on the Visual Quality of Automotive Coating.

In the present study, the possibility of recovering water in a car wash station was presented. The resistance of automotive coatings to washing water recovered at 50% and 70% from wastewater generated at car wash was tested. Wastewater treatment was carried out by ultrafiltration (UF) using tubular polyvinylidene fluoride (PVDF) membranes (100 and 200 kDa) manufactured by the PCI company. The membranes retained oil contamination, suspended solids, and over 60% of surfactants. For comparison, the 0.5% Turbo Active Green solution, used at professional car washes, was also applied in paint resistance studies. The tested solutions washed the painted surfaces of samples taken from car doors for 8 days. The resistance of automotive coatings to washing solutions was assessed by measuring gloss, Log Haze, RIQ, and Rspec parameters. Scratch resistance was also assessed. The results obtained in the current study indicated that the use of water recovered from wastewater did not deteriorate the quality of the car paint coating.

SME: Spatial multi-scale enhanced attention for automated detection of micro-defect on automobile complex paint surfaces

SME: Spatial multi-scale enhanced attention for automated detection of micro-defect on automobile complex paint surfaces

Automatic Optimal Robotic Base Placement for Collaborative Industrial Robotic Car Painting

This paper investigates the problem of optimal base placement in collaborative robotic car painting. The objective of this problem is to find the optimal fixed base positions of a collection of given articulated robotic arms on the factory floor/ceiling such that the possibility of vehicle paint coverage is maximized while the possibility of robot collision avoidance is minimized. Leveraging the inherent two-dimensional geometric features of robotic car painting, we construct two types of cost functions that formally capture the notions of paint coverage maximization and collision avoidance minimization. Using these cost functions, we formulate a multi-objective optimization problem, which can be readily solved using any standard multi-objective optimizer. Our resulting optimal base placement algorithm decouples base placement from motion/trajectory planning. In particular, our computationally efficient algorithm does not require any information from motion/trajectory planners a priori or during base placement computations. Rather, it offers a hierarchical solution in the sense that its generated results can be utilized within already available robotic painting motion/trajectory planners. Our proposed solution’s effectiveness is demonstrated through simulation results of multiple industrial robotic arms collaboratively painting a Ford F-150 truck.

Effects of exposure to volatile organic compounds (VOCs) content from paint on automobile paint workers in Nsukka, South Eastern Nigeria

BackgroundVolatile organic compounds (VOCs) fume in the workplace can act as an inducing agent to many health disorders. ObjectivesThis work investigated the effects of exposure to VOCs content from paint on the automobile paint workers in South Eastern Nigeria. MethodsA total of fifty (50) respondent participated in the study. Following the completion of informed consent form and well-structured questionnaire, blood samples were drawn and used for biochemical analysis. ResultsThe results of the haematological analysis showed a significant (p < 0.05) increase in white blood cell (WBC) cluster of differentiation 4 (CD4), and platelet (PLT), and a significant (p < 0.05) decrease in packed cell volume (PCV), hemoglobin (HB), lymphocytes (LYM) and eosinophil (EOS) of the exposed automobile paint workers compared to the control (unexposed workers). Results also showed significant (p < 0.05) increase in liver marker indices; alanine transaminase (ALT), aspartate transaminase (AST), total bilirubin (TB) and albumin (ALB) as well as significant (p < 0.05) decrease in Alkaline phosphatase (ALP), total protein (TP), direct bilirubin (DB). There was significant (p < 0.05) increase in urea, creatinine, potassium (K+), uric acid and nitric oxide concentrations and decrease in sodium (Na+) and bicarbonate (HCO3−) Again, results showed significant increase in Glutathione (GSH), and Glutathione peroxidase (GPx) and significant (p < 0.05) decrease in Superoxide dismutase (SOD) and Catalase (CAT). The Malondialdehyde MDA concentration showed varied significant (p < 0.05) difference based on ages. There was significant (p < 0.05) increase in luteinizing hormone (LH) and Follicle stimulating hormone (FSH), and significant (p < 0.05) decrease in the Testosterone (TET) concentrations of the exposed automobile paint workers compared to the unexposed workers. ConclusionsResult of this study suggests a toxic outcome due to exposure to VOCs in spray paint workers.

Nano coating containing SiO2 nanoparticles with non-stick properties for easy peeling of car paint from mild steel surfaces

Non-stick latex coating enhanced with mesoporous silica nanoparticles (SiO2 NPs) showed promising peeling properties. In order to see the effect of SiO2 NPs, coatings with and without SiO2 NPs applied on pieces of a hollow section mild steel beam as substrate. The grain size, crystal phase structure, specific surface area (SSA) and pore size distribution of the SiO2 NPs was determined using transmission electron microscopy (TEM), X-ray diffraction (XRD) pattern and Brunauer-Emmett-Teller (BET) analysis. Field emission scanning electron microscope (FESEM) and energy-dispersive X-ray spectroscopy (EDS) was used to observe the surface morphology and composition of the coated samples. The contact angle was measured for three different liquids on the surface of the samples namely, 1-bromonaphthalene (nonpolar), formamide and distilled water (polar) in order to calculate the surface energies per unit area and hysteresis contact angles. The result showed that adding SiO2 NPs increases the hydrophobicity and decreases the surface energy of the surface. One of the applications of such a coating is to protect the surface from paint sticking to it. For this purpose, the coating with and without SiO2 NPs is applied on a mild steel substrate and then painted by resin-based automotive paint. The pull off test showed that the adhesion is reduced by addition of SiO2 NPs. In addition, to see this application in industry, the coating with SiO2 NPs is applied to a skid and placed in the painting line of an automotive factory for 12 working days. After removing from the line, the coating and the paint on it were easily peeled from the skid either manually with a spatula or by a water jet cleaning machine (100 bar at spraying angle of 45°) compared to a bare skid.

Identification of Occupational Safety and Health Hazards at Paint and Welding Workshop using the HIRARC Method

Occupational Health and Safety (OHS) is important for every company to pay attention to. Preventing work accidents can be done by knowing the existing risks, one of which is through the Hazard Identification, Risk Assessment, and Risk Control (HIRARC) method. Body Repair, Paint, and Welding Workshop "Family 99" is a small to medium-sized entrepreneurship that operates in car repair, paint, and welding services. The research aims to analyze the potential dangers found in the Body Repair, Paint and Welding Workshop "Family 99". Hazard identification was conducted in the workshop work area, with research respondents totaling three active workers. The data collection employed observation and interviews with a descriptive approach. According to the research results obtained from a total of 14 work stages analyzed, two stages had the highest risk value, namely the paint peeling stage with a risk value of 12, and the first, second, and third sanding stages with a risk value of 9. Controls that can be carried out to reduce risks include administrative controls and the use of Personal Protective Equipment (PPE) for workers to work safely and comfortably.

Analysis of automotive paint layers on plastic substrates using chemical imaging μ-FTIR and O-PTIR microspectroscopy.

Automobile paint chips are a crucial piece of trace evidence for forensic investigators. This is because automotive paints are composed of multiple layers, including the primer, basecoat, and clearcoat, each of which has its own chemical composition that can vary by vehicle make, model, year, and manufacturing plant. Thus, Fourier-transform infrared (FTIR) spectral databases for automobile paint systems have been established to aid law enforcement in, for example, narrowing search parameters for a suspect's vehicle. Recently, car manufacturers have implemented primers on plastic substrates that are much thinner (~5 μm) than those on metal substrates, making it more difficult to manually separate for analyses. Here, we evaluated FTIR microspectroscopy (μ-FTIR) and optical photothermal infrared spectroscopy (O-PTIR) to chemically image cross sections of paint chips without manually separating the layers. For μ-FTIR, transmission and transflection modes provided the highest quality spectra compared to reflection and μ-ATR analyses. Point analysis was preferable to chemical imaging, as peaks were identified in the point (MCT) detector's lower spectral range that was below the imaging (FPA) detector's cutoff, such as those associated with titanium dioxide. Reduced spectral range can lead to a similar issue in O-PTIR analyses depending on instrument configuration. However, its complementary Raman spectra showed strong titanium dioxide peaks, providing an alternate means of identification. Both techniques are likely to become more relevant as they are non-destructive and avoid manual separation of the layers. O-PTIR is particularly well-suited for analysis of the thin primer layer due to its superior spatial resolution.

Design of Routes for Collaborative Robots in the Automobile Painting Process through a Comparison of Perturbative Heuristics for Iterated Local Search

Design of Routes for Collaborative Robots in the Automobile Painting Process through a Comparison of Perturbative Heuristics for Iterated Local Search

Relationship between benzene concentration, MDA levels and kidney function in car painting workshops in Surabaya: A cross-sectional observational study

Background Car painting workers are at risk because of the use of solvents containing benzene as the main ingredient in the car painting process. One of the clinical effects of systemic benzene is kidney disorders. Therefore, the purpose of this study is to analyze the relationship between benzene and Risk Quotient (RQ) benzene concentrations with Malondialdehyde (MDA), Blood Urea Nitrogen (BUN), and creatinine levels in workers exposed to benzene in car painting workshops in Surabaya. Methods This study used an observational design with a cross-sectional method conducted at two car paint workshops in Surabaya. The study population was all workers exposed to benzene in the two car paint workshops, aged between 20-65 years in 2019. The sample was taken using an accidental sampling method, involving 30 respondents. Inclusion criteria included workers exposed to benzene and willing to participate, while exclusion criteria included workers with a liver or kidney disease history. The variables studied included benzene concentration, benzene RQ (benzene metabolite), malondialdehyde (MDA) levels as a marker of oxidative stress, and indicators of kidney function (BUN and creatinine levels). Data were analyzed using descriptive and bivariate analysis with Pearson correlation test. Results There was no significant relationship between concentrations, RQ benzene, and MDA levels in workers in painting in Surabaya (p&gt; 0.05). There was no significant relationship between benzene concentration, BUN levels, and creatinine levels in paint workers in Surabaya (p&gt; 0.05). There was no significant relationship between benzene RQ and BUN and creatinine levels in paint workers in Surabaya (p&gt; 0.05). Conclusions This study's results indicate that benzene's effects do not lead to impaired kidney function. The benzene RQ variable in this study did not become a determining factor in BUN and creatinine levels in workers.

Impact of Heavy Metal Pollution on Oxidized Low-density Lipoprotein Levels among Car Maintenance Workshop Workers

This study aimed to evaluate the relationship between heavy metal pollution and oxidized low-density lipoprotein (OxLDL) among workers in car maintenance workshops in Baghdad, Iraq. Blood samples were collected from 70 male workers, including car maintenance and vehicle painting workers, along with a control group of healthy males. The levels of heavy metals, specifically cadmium (Cd) and lead (Pb), as well as OxLDL and the marker of lipid peroxidation, malondialdehyde (MDA), were measured. The results revealed a significant increase in the level of Pb in the blood of workers compared to the control group, whereas Cd levels did not exhibit a significant difference. Furthermore, both groups of workers exhibited significantly elevated levels of OxLDL compared to the control group. Additionally, the MDA level was significantly increased across all the study groups. Correlation analysis demonstrated positive associations between OxLDL levels and the extent of Pb and Cd pollution in the car maintenance worker group. These findings indicate an increased risk of developing cardiovascular diseases (CVDs) among workers in car maintenance workshops due to exposure to heavy metals. The observed elevation in the levels of OxLDL and lipid peroxidation markers underscores the potential health issues associated with occupational exposure to these polluted environments.

Extraction of Optical Characteristics of Diffuse Particles for Modelling a Dispersed Medium

Currently, virtual prototyping, i.e. preliminary modelling of processes on a computer has become ubiquitous. It is also applied to modern automobile paints in order to correctly reproduce the colour of the paint. The most practically important task is colour matching: calculation of the paint composition necessary to obtain a given colour. The complexity of modelling the propagation of light in paint is due to its complex structure and the wide variety of pigments, including diffuse ones. This problem can be solved by simulation of the light scattering by the dispersed pigment particles. To do this we need the optical properties of pigments, which are often unknown. In this paper, we propose several different methods for extraction of the pigment properties by measuring the light scattering of specially prepared samples. All methods are based on minimizing the difference between measured and calculated scattering values as a function of pigment properties. The methods differ in the types of paint samples that must be prepared and measured to obtain the pigment data. We describe the operation of the methods and test their robustness. As a result, one method has proven to be much more robust to the measurement errors. The colour of the real sample was also compared with the calculated colour of the paint, in the modelling of which the obtained properties of the pigments were used.

A hybrid finite difference level set–implicit mesh discontinuous Galerkin method for multi-layer coating flows

A mathematical model and numerical framework are presented for computing multi-physics multi-layer coating flow dynamics, with applications to the leveling of multi-layer paint films. The algorithm combines finite difference level set methods and high-order accurate sharp-interface implicit mesh discontinuous Galerkin methods to capture a complex set of multi-physics, incorporating Marangoni-driven multi-phase interfacial flow and the transport, mixing, and evaporation of multiple dissolved species. In particular, we develop several numerical methods for this multi-physics problem, including: high-order local discontinuous Galerkin methods for Poisson problems with Robin boundary conditions on implicitly-defined domains, to capture solvent evaporation; finite difference surface gradient methods, to robustly and accurately incorporate Marangoni stresses; and a coupled multi-physics time stepping approach, to incorporate all the different solvers at play including quasi-Newtonian fluid flow. The framework is applicable to an arbitrary number of layers and dissolved species; here, we apply it in a variety of settings, including multi-solvent evaporative paint dynamics, the flow and leveling of multi-layer automobile paint coatings in both 2D and 3D, and an examination of interfacial turbulence within a multi-layer matter cascade. Our results reproduce several phenomena observed in experiment, such as the formation of Marangoni plumes and Bénard cells. We also use the model to study the impact of long-wave deformational surface modes on immersed interfaces as well as the emergence of the final multi-layer film profile.

Developing a hybrid methodology for green-based supplier selection: Application in the automotive industry

The green performance values of businesses are of great importance in terms of sustainability, which includes long-term economic, social, and environmental effects. Thus, today, enterprises and managers are increasingly interested in this issue, and related topics, including supplier selection, have been inserted into decision-making procedures. However, how to predict the effects of green performance criteria, which represent environmental sustainability, on social and economic sustainability remains unclear. In this regard, the main purpose of this research is to develop a supplier selection methodology considering green performance criteria by applying multiple regression analysis and the Evidential Fuzzy Multi-Criteria Decision Making (F-MCDM) method based on Dempster-Shafer Theory (DST), which are both powerful methods in statistical analysis and decision-making under uncertainty. In the first phase of the research, variables that significantly affect green performance have been determined by testing the eight generated hypotheses with multiple regression analysis. Then, the best supplier was determined using those green supplier selection criteria in the Evidential F-MCDM method. Since using environmentally hazardous paints in the production process continues, the automobile paint production sector has been chosen as the application area of this green-based supplier selection methodology. In this respect, green dynamic capacity, green purchasing, eco-design, investment recovery, and green product innovation variables have been inserted into the Evidential F-MCDM method as the determinant variables of green performance. This research reveals that integrating multiple regression and Evidential F-MCDM methods can be a hybrid methodology in supplier selection. Thus, a different perspective is introduced into the green supplier selection decision-making process by considering the effects of criteria in the MCDM model on green performance. This innovation enhances the criteria determination and selection processes in classical MCDM approaches. In addition, green dynamic capacity is the most critical criterion in supplier selection based on their green performance, especially in the scope of this research.

A Novel LIBS Sensor for Sample Examinations on a Crime Scene.

In this work, we present a compact LIBS sensor developed for characterization of samples on a crime scene following requirements of law enforcement agencies involved in the project. The sensor operates both in a tabletop mode, for aside measurements of swabbed materials or taken fragments, and in handheld mode where the sensor head is pointed directly on targets at the scene. The sensor head is connected via an umbilical to an instrument box that could be battery-powered and contains also a color camera for sample visualization, illumination LEDs, and pointing system for placing the target in focus. Here we describe the sensor's architecture and functionalities, the optimization of the acquisition parameters, and the results of some LIBS measurements. On nano-plotted traces at silica wafer and in optimized conditions, for most of the elements the detection limits, in term of the absolute element masses, were found to be below 10 picograms. We also show results obtained on some representative materials, like fingerprints, swabbed soil and gunshot residue, varnishes on metal, and coated plastics. The last, solid samples were used to evaluate the depth profiling capabilities of the instrument, where the recognition of all four car paint layers was achieved.

Optimal Enhancement Of Hardness, Hydrophobicity, And Surface Durability Of Pu-Coated Galvanized Material Jis G3302 With Polysilazane Nanomaterial

Organic Polysilazane (OPSZ) nano-coatings are applied to the surface of polyurethane car body paint (pu-coated) to improve the hardness, hydrophobicity and durability of the Pu-coated surface. Three types of nano-coatings are used under the brand name Durazane®1500 Rapid cure in the formulas Tutoprom® 3641 and Tutoprom® 3042, along with Nano Coating brand Autoproo under Autoproo. The coating process to the substrate is done using a suede cloth with a wiping method. The coating was done in 1 layer with a dry time of 10 minutes to continue to the second layer. After coating, hardness testing was carried out using pencil hardness and hydrophobicity with Contact Angle measurement. Tests were carried out with curing times of 1 day, seven days, 17 days, and 21 days. To determine the durability, the specimens were left outdoors (exposed to rain and hot sun) for 21 days. Durazane® 1500 Rapid cure in Tutoprom® 3641 and Tutoprom® 3042 formulas increased the hardness up to the H scale, while the Autoproo brand has HB hardness value. Tutoprom® 3641 and Tutoprom® 3042 formulas can cause a taro leaf or hydrophobic effect with a contact angle of 104,5°. From the SEM results, the nano-coating can increase the thickness value and fill the substrate’s pores perfectly, increasing the adhesivity and protecting the pu-coated for a long time. High durability, where after 21 days, the coating still looks glossy and dust-free.

Combining material flow simulation and optimization for sustainable manufacturing – application in automotive paint shops

The necessity for sophisticated decision support in industrial manufacturing has been described manifoldly and simulation approaches as well as optimization methods are continuously developed. This can be especially promising when it comes to decision-making with multidimensional requirements of economic and ecological efficiency. However, due to the required expert knowledge, there is still a gap between theoretically applicable and industrially applied methods. The paper therefore presents results of two use cases as part of the European project ECOFACT where different approaches for the combination of simulation and (heuristic) optimization were applied with industry partners. An overview of recent works and systematic literature reviews of sustainable manufacturing and the approaches for combining simulation and optimization is given. Correspondingly, the investigated use cases of automobile paint shops refer to the reduction of environmental impacts by optimized heating processes and an improved batching process to minimize paint waste. In the first case, setup times for heating color pools and ovens were shifted to avoid load peaks in a calculation time of less than one minute. In the second use case batch size was increased by around 25%.

Dry air compressor for car painting quality improvement

The humidity used in the painting process greatly determines the result of painting the car body. This study aims to develop a dry air compressor that can be used to overcome car paint defects. This system consists of a 2 HP compressor engine for sucking air from the atmosphere, two air collection tubes where the first tube contains air obtained from the atmosphere and the second tube contains dry air obtained from the first tube. The inside of the first tube is given a copper coil measuring 5 mm in diameter which is connected to a 120-watt cooler while the second tube is not given a copper coil. Each tube has a diameter of 50 cm and a height of 100 cm. The addition of copper coil aims to separate air from water by means of the condensation process which is the development of this study. Testing of compressor performance is done by turning on the compressor with the exhaust valve closed. After 60 minutes, the air pressure in each tube increased from 0 Psi to 89 Psi, the humidity decreased from 52 % to 38 %, and the temperature decreased from 31.6 °C to 18.2 °C. To see the effect of cooling on the air, the exhaust valves on both tubes were opened. In the first tube there is water coming out, as much as approximately 100 ml while in the second tube there is no water coming out. The water that comes out of the first tube is caused by the condensation process that separates the air from the water and due to the influence of gravity the water falls to the bottom of the tube. The dry air contained at the top of the first tube is flowed into the second tube and is ready to be used for painting the car body. The painting results show that there are no more small holes or paint defects on the paint surface

Numerical Simulation of Airflow Organization in Paint Spraying System of car Lampshade

According to the design requirements of the airflow organization of the car lampshade paint spraying system, the corresponding physical model is established, and the flow state of the air organization in the entire paint spraying system was simulated using Fluent software. On this basis, the wind speed of all mechanical air supply and air exhaust in the paint spraying system are adjusted to find the optimization and improvement direction of the airflow organization, so that the air pressure and wind direction in the system meet the environmental requirements of the car lampshade painting process, economically reducing the harm of paint, and providing reference for the ventilation design of the paint spraying system.

Towards the identification of the volatile organic compounds emitted by the coatings used in a car factory painting line

AbstractOne of the main reasons for the degradation of working conditions is the lack of air quality. It is known that indoor air contaminants pose a risk to both the human organism and the environment, which constitutes a challenge for employers and major industries. A car factory painting line is an evident example of a work location in which the employers must be especially aware and concerned with the employees' health. Since the coatings are the main VOCs-emitting source, this work studied the analytes emitted by four primers, 17 basecoats and one varnish used in a car factory of a world-renowned automotive brand, with gas chromatography-ion mobility spectrometry (GC-IMS), as a way of identifying all the coating-borne VOCs that can be emitted to the indoor air. The variability of the collected data was assessed, and the repeatability of the results proved the suitability of GC-IMS for this type of study. Among primers, inks and varnish, 45 VOCs were accurately identified using an exclusively developed database of compounds. The presence of the identified analytes in the composition of the coatings represents the potentiality of being emitted to the indoor air of the factory and, consequently, denotes their eventual toxicity for the employees of the painting line. These results represent a step forward in the assessment of the panting line work conditions, so eventual consequences to the employees’ health are theoretically discussed; nonetheless, further studies aim to examine air samples of the factory and evaluate the work conditions and actual consequences to the employees that must be developed.

Relationship between benzene concentration, MDA levels and kidney function in car painting workshops in Surabaya: A cross-sectional observational study

Background Car painting workers are at risk because of the use of solvents containing benzene as the main ingredient in the car painting process. One of the clinical effects of systemic benzene is kidney disorders. Therefore, the purpose of this study is to analyze the relationship between benzene and Risk Quotient (RQ) benzene concentrations with Malondialdehyde (MDA), Blood Urea Nitrogen (BUN), and creatinine levels in workers exposed to benzene in car painting workshops in Surabaya. Methods This is an observational, cross-sectional study conducted at two car painting workshops in Surabaya that use benzene as a solvent in their production process, namely in industries in Kalijudan and Jemursari. The research sample was taken using the accidental sampling method and as many as 30 respondents were involved in this study. The variables studied included benzene concentration, RQ benzene, MDA levels, and kidney function (BUN and creatinine levels). Analysis of the data used is a descriptive and bivariate analysis using the Pearson correlation test. Results There was no significant relationship between concentrations, RQ benzene, and MDA levels in workers in painting in Surabaya (p&gt; 0.05). There was no significant relationship between benzene concentration, BUN levels, and creatinine levels in paint workers in Surabaya (p&gt; 0.05). There was no significant relationship between benzene RQ and BUN and creatinine levels in paint workers in Surabaya (p&gt; 0.05). Conclusions The results of this study indicate that the effects of benzene do not lead to impaired kidney function. The benzene RQ variable in this study did not become a determining factor in BUN and creatinine levels in workers.