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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.

To improve the uniformity of coating thickness and spraying efficiency, new point cloud modeling and slicing algorithm are proposed to deal with free-form surfaces for the spray painting robot in this paper. In the process of point cloud modeling, the edge preservation algorithm is firstly presented to avoid damaging the edge characteristic of the point cloud model. For the spraying gun, the coating deposition model on the free-form surface is determined on the basis of the elliptic double β distribution model. Then, the grid projection algorithm is proposed to obtain grid points between adjacent slices on the free-form surface. Based on this, the analytical solution for calculating the coating thickness at each grid point is obtained. The cross-section contour points are obtained by intercepting the point cloud model with several parallel slices, which is important for the trajectory planning of the spray painting robot. Finally, the uniformity of coating thickness is optimized in terms of the moving speed of the spraying gun and the slice thickness. The simulation and numerical experiment results show that the uniformity of coating thickness and spraying efficiency are improved using the proposed point cloud modeling and slicing algorithm.

The spray painting is widely used in automobile industries, marines and navy, etc. Extensive development of research is going in Robotics for painting application. In which it gives the best qualit...

Background: Application of patterns to enable high-resolution Digital Image Correlation (DIC) at the small scale (μm/nm) is known to be very challenging as techniques developed for the macro- and mesoscale, such as spray painting, cannot be scaled down directly. Moreover, existing nano-patterning techniques all rely on harsh processing steps, based on high temperature, chemicals, physical contact, liquids, and/or high vacuum, that can easily damage fragile, small-scale, free-standing and/or hygro-sensitive specimens, such as MEMS or biological samples. Objective: To present a straightforward, inexpensive technique specially designed for nano-patterning highly delicate specimens for high-resolution DIC. Methods: The technique consists in a well-controlled nebulized micro-mist, containing predominantly no more than one nanoparticle per mist droplet. The micro-mist is subsequently dried, resulting in a flow of individual nanoparticles that are deposited on the specimen surface at near-room temperature. By having single nanoparticles falling on the specimen surface, the notoriously challenging task of controlling nanoparticle-nanoparticle and nanoparticle-surface interactions as a result of the complex droplet drying dynamics, e.g., in drop-casting, is circumvented. Results: High-quality patterns are demonstrated for a number of challenging cases of physically and chemically sensitive specimens with nanoparticles from 1 μm down to 50 nm in diameter. It is shown that the pattern can easily be scaled within (and probably beyond) this range, which is of special interest for micromechanical testing using in-situ microscopic imaging techniques, such as high-magnification optical microscopy, optical profilometry, atomic force microscopy, and scanning electron microscopy, etc. Conclusions: Delicate specimens can conveniently be patterned at near-room temperature ($\sim $ ∼ 37 ∘C), without exposure to chemicals, physical contact or vacuum, while the pattern density and speckle size can be easily tuned.

This paper deals with the multi-objective optimal design of a novel 6-degree of freedom (DOF) hybrid spray-painting robot. Its kinematic model is obtained by dividing it into serial and parallel parts. The dynamic equation is formulated by virtual work principle. A performance index for evaluating the compactness of robot is presented. Taking compactness, motion/force transmissibility, and energy consumption as performance indices, the optimal geometric parameters of the robot are selected in the Pareto-optimal set by constructing a comprehensive performance index. This paper is very useful for the development of the spray-painting robot.

Robots can be used in painting operations like many other automated jobs. It can also perform welding, drilling, grinding, carrying operation, and various industrial process with the integration of proper tools with its arm. Robots are used widely in industrially developed countries to perform many operations of their industrial processes. Though the application of robots is limited in our country, the implementation has been initiated with the recent trend of moving forward to the automated industry.

The 3-D model of workpieces plays a significant role in robotic spray painting, which needs the geometry and shape information for painting-path planning or pose estimation. However, the models are rarely provided beforehand, even if they are available, random pose changes during workpiece conveying on the spray-painting pipeline also necessitates the usage of real-time 3-D reconstruction. In this case, we propose an online modeling approach for automatic spray-painting applications. Specifically, with two consumer RGB-D cameras mounted on the two sides of the pipeline, the data streams of the moving workpiece are continuously collected. Then, incorporating the 3-D contour feature and approximate linear motion characteristics of the workpiece, a modified iterative closest point (ICP) algorithm is proposed for fast registration of multiple workpiece point clouds with varying positions. Finally, based on the spatial distribution and point cloud quality evaluation, a joint weighted algorithm for fusing point clouds from different perspectives is proposed, which is effective for the issues of self-occlusion and has superior noise resistance. To estimate the system performance, an experimental platform was established to simulate the spray-painting production line. According to our experiments, the proposed method can completely model the complex workpieces with irregular polyhedral structure within 1500 ms, and the modeled geometry accuracy can reach less than 8 mm, which has a significant improvement compared with the conventional methods.

Taguchi L9 orthogonal array is used to conduct the IRB1410 robot spray painting experiments to investigate the surface characteristics of Cold Rolled close Annealed (CRCA) steel workpiece. The main...

This study is investigating three-dimensional numerical simulation of a Newtonian droplet impact and break on two square cylinders based on dynamic contact angle of droplet at the spatial interface between two solid–fluid phases. The droplet impact details and morphology studied in the present work could provide ideas for the spray wall impingement modeling in the simulation of many industrial applications, such as spray painting and liquid cooling of surfaces. The droplet impact is investigated on two square cylinders in 9 different modes with different droplet diameters and physical conditions such as different positions of droplet. The volume of fluid (VOF) method was used with open-source software. The results have been compared and validated quantitatively and qualitatively with the experimental results. Results represent droplet diameter into cylinder dimension and velocity profiles are affected on number of broken droplets, break times and droplet deformation. Also, mean velocities of droplet after impact on two square cylinders at first break time were 0, 0.025, 0.12, 0.47, 0.11, 0.08, 0.2, 0.012, 0.19 m/s for cases 1–9, respectively. Moreover, in case 7 that droplet diameter into cylinder dimension was 2, the maximum number of break-up into secondary droplets was 10 drops that occurred for 4 times.

In computational fluid dynamics, the modeling of paint application processes by electrostatic rotary bell sprayer is mostly performed using an Euler–Lagrange approach. The initial conditions of the discrete phase—position, velocity, size, and charge—have an essential influence on the resulting film thickness distribution and the total charge transferred to the object. Typically, so-called injection models are used to specify these initial conditions, whereby the determination of the injection model coefficients is crucial. In this paper, a framework is proposed that combines experimental input data, an injection model, and a metamodel-based optimization. The painting tests for the generation of input and validation data were carried out in a technical center in the industrial standard. The simulations were performed using ANSYSFluent. Initial droplet conditions could efficiently be determined via the framework so that the painting-specific objectives were achieved with reasonable accuracy. In addition to the framework, a turbulence study of the strongly swirled shaping air of this atomizer was carried out, whereby a substantial underestimation of the axial air velocity was found in the turbulence models being investigated. The initial droplet conditions were also used in this study to draw conclusions about the accuracy of the airflow simulation. The proposed framework can be adapted to other solvers and efficiently finds injection model coefficients for other paint applicators.

We propose a novel human-swarm interaction system, allowing the user to directly control a swarm of drones in a complex environment through trajectory drawing with a hand gesture interface based on the DNN-based gesture recognition. The developed CV-based system allows the user to control the swarm behavior without additional devices through human gestures and motions in real-time, providing convenient tools to change the swarm's shape and formation. The two types of interaction were proposed and implemented to adjust the swarm hierarchy: trajectory drawing and free-form trajectory generation control. The experimental results revealed a high accuracy of the gesture recognition system (99.75%), allowing the user to achieve relatively high precision of the trajectory drawing (mean error of 5.6 cm in comparison to 3.1 cm by mouse drawing) over the three evaluated trajectory patterns. The proposed system can be potentially applied in complex environment exploration, spray painting using drones, and interactive drone shows, allowing users to create their own art objects by drone swarms., ACM SIGGRAPH 21. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. arXiv admin note: substantial text overlap with arXiv:2106.14698

Spraying trajectory planning for complex surface has always been a challenging problem. On the basis of a spraying path generated with the 3D point cloud slice, this paper proposes a Non-dominated Sorting Genetic Algorithm (NSGA-II) based spraying trajectory optimization method for complex surfaces. Firstly, the point cloud slicing method is used to generate the initial spraying path of complex surfaces. In particular, aiming at the possible path self-intersection problem near the high curvature region on complex surfaces, a path smoothing method based on monotone chain is proposed to eliminate invalid path loops. Then, a multi-objective NSGA-II spray trajectory optimization method is proposed to optimize spray efficiency and spray quality by improving the spray speed distribution along the spray path. Finally, the proposed approach is verified on real automotive surfaces, the results show its robustness and efficiency in solving spray trajectory planning problems on complex surfaces.

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 −6 but not up to the level (1.0 × 10−4) that requires remedial action.

PaintCopter is an autonomous unmanned aerial vehicle (UAV) capable of spray painting on complex three-dimensional (3D) surfaces. This letter aims to make PaintCopter more user-friendly and to enable more intuitive human–robot interaction. We propose a virtual reality interface that allows the user to immerse in a virtual environment, navigate around the target surface, and paint at desired locations using a virtual spray gun. A realistic paint simulator provides a real-time previsualization of the painting activity that can either be processed right away or stored to a disk for later execution. An efficient optimization based planner uses this information to plan the painting task and execute it. The proposed planner maximizes the paint quality while respecting the spray nozzle constraints and platform dynamics. Our experiments show that the interface allows the user to make precise modifications to the target surface. Finally, we demonstrate the use of virtual reality interface to define a painting mission, and then the PaintCopter carrying out the mission to paint a desired multicolored pattern on a 3D surface.

Nowadays, off-line robot trajectory generation methods based on pre-scanned target model are highly desirable for robotic spray painting application. For actual implementation of the generated trajectory, the relative pose between the actual target and the model needs to be calibrated in the first place. However, obtaining this relative pose remains a challenge, especially from a safe distance in industrial setting. In this paper, a pose estimation system that is able to meet the robotic spray painting requirements is proposed to estimate the pose accurately. The system captures the image of the target using RGB-D vision sensor. The image is then segmented using a modified U-SegNet segmentation network and the resulting segmentation is registered with the pre-scanned model candidates using iterative closest point (ICP) registration to obtain the estimated pose. To strengthen the robustness, a deep convolutional neural network is proposed to determine the rough orientation of the target and guide the selection of model candidates accordingly thus preventing misalignment during registration. The experimental results are compared with relevant researches and validate the accuracy and effectiveness of the proposed system.

A novel, simple, and low-cost spray painting technique has been developed for the fabrication of microfluidic paper-based devices. The devices that we developed utilize aerosol spray paint to build hydrophobic barriers and employ a hole puncher to obtain paper-based patterned layers and paper dots without using any specialized instruments (e.g., without a laser cutter). The entire manufacturing process is extremely simple, inexpensive, and rapid, which means that it can be applied broadly. Furthermore, the application of the device to iron detection was demonstrated. A linear relationship between the colour value and the iron concentration was observed from 0 to 0.02 g/L. The developed microfluidic paper-based device for iron detection exhibited a low detection limit (0.00090 g/L), good selectivity, and acceptable recovery.

The objectives of the study were to measure and characterize exposure to airborne nanoscale titanium dioxide during airless spraying and sanding of a nano-enabled paint, and to evaluate the effectiveness of dust capture methods in reducing airborne nanoparticle concentrations. A tradesperson performed the work activities in an environmentally controlled chamber. Samples were collected in the tradesperson's breathing zone and in surrounding areas to assess bystander exposure. Filter-based samples were analyzed using gravimetric methods, scanning electron microscopy, and energy dispersive spectroscopy. Differential particle count data were obtained by means of a scanning mobility particle sizer. Local exhaust ventilation provided statistically significant reductions of airborne nanoparticle concentrations during sanding. Sanding the paint after drying with a handheld power sander generated relatively low levels of airborne titanium dioxide. In contrast, task-based exposure measurements collected during the initial airless spray application of the nano-enabled paint suggested a potential for occupational exposures to exceed the time-weighted average exposure limit for ultrafine titanium dioxide recommended by the National Institute for Occupational Safety and Health. Painters applying nano-enabled coatings may have little recourse but to rely, in some instances, on lower tiers of the hierarchy of controls, such as personal protective equipment. In light of these findings, employers and industrial hygienists should characterize exposures and implement the hierarchy of controls to ensure painters are sufficiently protected.

Purpose This paper aims to present a new trajectory optimization approach targeting spray painting applications that satisfies the paint thickness requirements of complex-free surfaces. Design/methodology/approach In this paper, a new trajectory generation approach is developed to optimize the transitional segments at the junction of adjacent patches for straight line, convex arc and concave arc combinations based on different angles between normal vectors of patches. In addition, the paint parameters including the paint gun velocity, spray height and the distance between adjacent trajectories have been determined in the generation approach. Then a thickness distribution model is established to simulate the effectiveness of trajectory planning. Findings The developed approach was applied to a complex-free surface of various curvatures, and the analysis results of the trajectory optimization show that adopting different transitional segment according to the angle between normal vectors can obtain the optimal trajectory. Based on the simulation and experimental validation results, the proposed approach is effective at improving paint thickness uniformity, and the obtained results are consistent with the simulation results, meaning that the simulation model can be used to predict the actual paint performance. Originality/value This paper discusses a new trajectory generation approach to decrease the thickness error values to satisfy spray paint requirements. According to the successfully performed simulation and experimental results, the approach is useful and practical in overcoming the challenge of improving the paint thickness quality on complex-free surface.

Due to the complex dynamic characteristics of a hybrid spray-painting robot, the motion accuracy fluctuates in the workspace. In order to reduce the accuracy fluctuation of the hybrid robot, this paper proposes an engineering-oriented motion accuracy assurance method by considering dynamic characteristics, including workspace optimization and control parameters design. First, the dynamic model of the hybrid spray-painting robot is derived based on the virtual work principle, and a dynamic evaluation index is investigated to describe the possible maximum dynamic load. Then, based on the evaluation index, the relative location of the task workspace for painting an aircraft wing in the whole workspace is optimized. Then, a control parameters design approach is presented to ensure that the robot always has desired accuracy in the optimized task workspace. Finally, some experiments are performed, and the results show that the robot has better performance in the optimized task workspace with the designed control parameters, which proves the effectiveness of the proposed method.

An increasing interest in the development of special climbing robots has been witnessed in last decade. Motivations are typically to increase the operation efficiency in dangerous environments or difficult-to-access places, and to protect human health and safety in hazardous tasks. Climbing robots with the ability to maneuver on vertical surfaces are currently being strongly requested by various industries and military authorities in order to perform dangerous operations such as inspection of high-rise buildings, spray painting and sand blasting of gas tanks, maintenance of nuclear facilities, aircraft inspection, surveillance and reconnaissance, assistance in fire fighting and rescue operations, etc. Such capabilities of climbing robots would not only allow them to replace human workers in those dangerous duties but also eliminate costly scaffolding.

In aero gas turbine engine, copper nickel indium (CuNiIn) and molybdenum loaded disulphide (MoS2) duplex coating is applied on Ti6Al4V blades in bladed disk configuration of low pressure and high pressure compressor. Coating between blade and disk is provided to prevent fretting wear due to direct metal to metal contact of Ti6Al4V. Generally, grit blasting will be done for preparation of the surface before the application of coating. Laser surface texturing (LST) process can be explored by aero engine industry as a new surface preparation process for compressor blades. To compare two different surface preparation methods, Ti6Al4V surface is prepared by two different processes, conventional grit blasting as well as laser surface texturing (LST). LST with different elliptical and square patterns are created on Ti6Al4V. Surface topography is analyzed by SEM and WLI. CuNiIn is sprayed by atmospheric plasma spray (APS) and MoS2 on top of CuNiIn by painting and curing. Effects of surface preparation on coating adherence as well as on tribological properties are studied. The results showed that geometry and dimensions of LST pattern influences the coating adherence and wear performance. LST process can be optimized for better performance and explored as an alternative surface preparation process in industry for thermal spray coatings.

Automobile spray painters are often prone to chemical toxicity due to their routine work. This study was aimed at the occupational effect of spray painting fumes on some biochemical parameters in automobile spray painters. Five milliliters of blood specimen were collected into lithium heparin anti-coagulated bottles from twenty five automobile spray painters with ≤ 10 years working experience (experimental group one), ≥ 11 years working experience (experimental group two) and non-automobile spray painters which were monitored as control group respectively. After this, plasma alanine aminotransferase, aspartate aminotransferase, C-reactive protein, urea and creatinine were measured quantitatively using a spectrophotometer. The mean values of all the measured biochemical parameters showed no statistically significant differences (p>0.05) in the automobile spray painters with ≤ 10 years working experience as compared with that of the control group with the exception of plasma C-reactive protein, while those with ≥ 11 years working experience showed statistically significant differences (p0.05). In conclusion, the concentration of plasma alanine aminotransferase, aspartate aminotransferase and C-reactive protein may be altered in automobile spray painters with ≥ 11 years working experience, thus these biochemical parameters should be monitored regularly in spray painters within this category of working experience

Spray painting after vehicle body inspection is one of the most important aspects of automobile manufacturing and assembling industries. There are many methods available to identify the defects such as dents, scratches or some deformity containing both on a vehicle body using manual labor to closely look and identify the defects and then transfer to spray painting area which may be controlled either manually or semi-autonomously, but this method is not cost- effective as it require more labors and may result in slowing down the speed of manufacturing in a plant leading it to not achieving the target goals set. In this paper, we proposed a defect detection and inspection system using Faster RCNN approach for image processing on a car body to check type of defects apart from the ones which are planned on it and spray painting using a fully autonomous robotic arm having 6 degree of freedom with a sprayer attached to its end effectors and other robotic arm with a camera for inspection. The decision making is provided by classified neural networks through continuous monitoring the vehicle body by the camera. Here the case study takes up the spraying and defect detection in a car body. A similar setup can be used to detect deformity in any other vehicle.

The increasing diversity of products and variants requires a flexible and fast path generation in robot-based painting processes. In the state of the art, path generation in the painting industry is a time consuming and cost-intensive iteration process in which the generated paths are evaluated and optimized via painting trials. In this paper, we present a novel concept for a self-programming painting cell, which is based on the key technologies 3D-scanning, multi-physics painting simulations, and a contactless film thickness measurement using terahertz technology. The core element of this cyber-physical painting system is a unique combination of numerical painting simulations with a gradient-based multi-objective optimization method, to virtually compute painting paths that produce a homogeneous thickness on the painted object. In order to drastically reduce the time and computationally intensive numerical fluid dynamic simulations, a step-by-step coupling of an offline and online simulation was implemented. In a final step, a collision free robot motion without singularities is generated automatically from the computed painting path. The concept was validated under pilot plant conditions by the painting of a fender using an electrostatically assisted high-speed rotary bell atomizer. The paint film thickness, measured with terahertz technology was used as the target and validation criterion, as it shows a strong correlation to other quality values. The results show that the achieved film thickness was within the process specification, although deviations between simulated and measured film thicknesses were found in the edge zones of the workpiece.

Since the last decade, human efforts have replaced manual works in terms of automatic (robotic) solutions dramatically for safety and precision purposes. Present review highlights the various robotic technologies used for solving the need to paint any surface. Many advancements in the sphere of painting robots have been discovered and utilized for high rise buildings painting, wall painting, and other surface painting. Still, there is a need to increase the effectiveness, precision, durability, and reliability in such automatic techniques [1]. In this regards, the present review accumulates the various aspects of recent automatic techniques, working methodologies, and innovative technologies used in the spray painting robots by considering the various mechanical and electrical components. These databases can significantly assist the researchers who are looking for this solution or working on the mentioned application. In addition, present review also discusses about a few technologies for environment friendly and economically effective options in spray painting.

Inverse kinematics is an important issue for redundant robot. This paper studies the inverse kinematics of a 7 degree of freedom (7-DOF) spray-painting robot with a telescopic forearm. The mapping relationship between the joint and the end-effector is studied and a method to find the solution of the inverse solution is proposed. The position of the end point of the painting gun are affected by five joints and the position of the two joints from the five joints are taken as independent variables. Except the two joints with their position taken as independent variables, the analytical solutions of other five joints are written as function of the two independent variables. An objective function that considers the joint limit is presented to optimize the two independent variables. The proposed method is compared with the direct Jacobian iteration method.

Emulsions formed using ionic surfactants, such as carboxylates, sulphonates and quaternary amines, are readily handled. However, emulsions formed with nonionic surfactants, such as ethoxy- and propoxy alkyl adducts, cause very stable emulsions and require clever chemical methods to economically address waste treatment. The chapter describes how Nalco has applied emulsion breaking expertise to a process which scrubs volatile organic compounds (VOC), from the exhaust air of an automotive spray painting process. Nalco1s process, the Hydrocarbon Emissions Control Process, provides a cost-effective, viable solution to a major air pollution problem facing the United States automotive industry today. In October of 1979 standards of performance were proposed under the Clean Air Act to limit emissions of VOC from automotive surface coating processes. The screening tool permitted the spraying of water-based coatings, high solids enamels, dispersion lacquers, and the base coat/clear coat coatings. The emulsion process acts by absorbing VOCs, paint resins, and pigments into the oil phase of the water continuous emulsion.

In the manufacturing industry, spray painting is often an important part of the process. Especially in the automotive industry, the perceived quality of the final product is closely linked to the exactness and smoothness of the painting process. For complex products or low batch size production, manual spray painting is often used. But in large scale production with a high degree of automation, the painting is normally performed by industrial robots. There is a need to improve and simplify the generation of robot trajectories used in industrial paint booths. A method for spray paint optimization is presented, which can be used to smooth out an initial trajectory and minimize paint thickness deviations from a target thickness. By fitting a spline function to experimental data, an applicator footprint profile is determined, which is a two-dimensional reference function of the applied paint thickness. This footprint profile is then projected to the geometry and used as a deposition model at each point along the trajectory. The positions and durations of all trajectory segments are used as optimization variables. They are modified with the primary goal to obtain a paint applicator trajectory, which will closely match a target paint thickness when executed. The algorithm is shown to produce satisfactory results on both a simple 2-dimensional test example, and a nontrivial industrial case of painting a tractor render. The final trajectory shows an overall thickness close to the target thickness, and the resulting trajectory is feasible to execute directly on an industrial robot.

Background. Automobile spray painters in Nigeria are exposed to organic solvents due to the hazardous nature of their work. Inadequate use of personal protective equipment (PPE) may intensify exposure to high levels of chemical hazards with resultant health problems. Objectives. The present study assessed PPE use and work practices and compared work-related health problems of spray painters and controls in Ile-Ife, Nigeria. Methods. A cross-sectional study was conducted among 120 spray painters and 120 controls (electronic technicians). Data on socio-demographics, work practices, knowledge about organic solvent-related hazards and self-reported health symptoms were obtained using a semi-structured questionnaire. Clinical examinations were performed for all respondents and the composition of organic solvents in paints and paint products were derived from material safety data sheets. Results. All respondents were male, and the mean age was 32.7±13.8 years for painters and 33.9±15.5 years for controls. Few (7.5%) painters perceived their use of PPE to be adequate. All spray painters worked in enclosed workshops and N-butyl acetate was the most commonly used organic solvent. Spray painters reported excessive tear production, recurrent cough, and short-term memory loss more frequently than controls (P Conclusions. Spray painters in the study area worked amidst chemical hazards and had poor use of PPE. Exposure to organic solvents may be responsible for the higher prevalence of self-reported health problems among spray painters. Interventions to enforce the use of PPE and improve the knowledge of organic solvent-related hazards among spray painters are essential. Participant Consent. Obtained Ethics Approval. Ethical approval to conduct the study was obtained from the Health Research and Ethics Committee of the Institute of Public Health, Obafemi Awolowo University, Ile-Ife Nigeria (HREC No: IPHOAU/12/463). Competing Interests. The authors declare no competing financial interests.

Toluene is an important constituent of various commercial products including aints,dyes,cosmetics,pharmaceuticals, various chemicals and plastic articles. It is a natural component of crude petroleum and petroleum products such as gasoline and diesel fuel. The aim of present study is to isolate and characterize toluene-degrading bacteria from contaminated soil surrounding Car spray painting workshops. Four soil samples were collected from car spray painting workshops in Kolenchery. Totally 12 different bacterial isolates were obtained from the samples. Three were (TDB 3, TDB 9, TDB 12) finally selected through secondary screening by agar well diffusion method using Toluene as carbon source. These isolates were selected based on highest zone of degradation on agar well diffusion method. Biochemical tests and GC-MS of these strains were performed. Based on the GC MS result one strain(TDB 3 is selected for PCR analysis. The nucleotide sequence of 16S r RNA gene shown the isolated strain , TDB 3 belongs to Bacillus sp. were the most effective in degrading toluene and this may be used for environmental bioremediation. &nbsp

In this paper, aiming at the problem of poor quality and low spraying efficiency of irregular for complex freeform surfaces, a new spray painting robot trajectory planning method based on point cloud slicing technology is proposed. Firstly, the point cloud data of the workpiece to be sprayed is obtained by laser scanning. The point cloud data is processed to obtain the point cloud model of the sprayed workpiece. Then the section polysemy line is obtained after slice acquisition and section data processing of the point cloud model. The section polysemy line is sampled on average, and the normal vector of all sampling points is estimated. Finally, interpolation algorithm is used to connect the data points to obtain the space trajectory of spraying robot. In addition, the droplet trajectory model for electrostatic spray painting is established. The experimental results show that the method fully meets the requirements of coating thickness and improves the spraying efficiency and uniformity of coating.

Cleaning, applying and testing coatings on corrosion-susceptible surfaces, such as those in Oil & Gas and extreme environments such as offshore Oil & Gas assets, currently requires extensive manual labor. Further, cleaning, coating and measuring coatings at height can create a dangerous occupational environment. Drones, also known as unmanned aerial systems (UAS), unmanned aerial vehicles (UAV), or small unmanned aerial vehicles (sUAV) can be leveraged to perform some of these tasks, including cleaning, coating, and inspection while keeping workers safely on the ground. Of note are some current aerial robotic inspection platforms in the market that make physical contact with structures for nondestructive testing (NDT) in addition to visual inspection. Drone capabilities have significantly evolved over the past decade, and it is expected that the ubiquity of such systems will continue to increase in the years to come. While no coating or cleaning drone is commercially available at the time of this publication, one company has an existing prototype currently under development as part of a Joint Development Agreement with a large international coatings manufacturer for industrial application that is expected to be tested in industrial environments this year. This prototype is a custom-manufactured drone with a tether to the aircraft from the ground that delivers power and cleaning or coating material. An on-board computer manages flight navigation along with intelligent spraying. While the utilization of this new technology faces many challenges, it is important to recognize the potential and projected growth in use of such systems. An introduction to the current state of coating and cleaning drones will be discussed, along with limitations and benefits the system can provide to the coatings and corrosion control in the Oil & Gas industry.

Research into carbon nanotubes (CNTs) has been a hot topic for almost 3 decades, and it is now that we are beginning to observe the impact of advanced applictions of this nanomaterial in areas such as electronics. Currently, in order to mass produce CNT devices, either large-scale synthesis, followed by numerous energy-intensive processing steps or photolithography processes, including several sputter-deposition steps, are required to pattern this material to fabricate functional devices. In the work reported here, through the utilization of a universal catalyst precursor (cyclopentadienyl iron dicarbonyl dimer) and the optimization of solution parameters, patterned high-quality vertically aligned arrays of single- and few-walled CNTs have been synthesized via various inexpensive, commercially scalable methods such as inkjet printing, stamp printing, spray painting, and even handwriting. The two-step process of precursor printing, followed immediately by CNT growth, results in CNTs with a Raman ID/IG ratio of 0.073, demonstrating very high-quality nanotubes. This process eliminates time-consuming and costly CNT post processing techniques or the deposition of numerous substrate barrier and catalyst layers to achieve device manufacturing. As a result, this method has the potential to provide a route for the large-scale synthesis of high-quality single- and few-walled CNTs that can be applied in industrial settings.

When it comes to quality and efficiency, droplet diameters have a substantial impact on paint application processes. To determine droplet diameter distributions, Malvern-type laser diffraction and phase Doppler anemometry are common techniques. This has changed since 2014, as SpraySpy-type time-shift instruments became available. In this study, an industrial spray-painting atomization process using a rotary bell atomizer and an automotive clearcoat paint will be individually characterized using laser diffraction and time-shift measurements. Atomizer rotational speed and paint flow rate are varied in the experiments, while the remaining parameters are kept constant. The commonly used measurement setups are adapted and their respective outputs are converted to allow for a direct comparison. Analyzing the volumetric and number distributions of single measurements, it turns out that the laser diffraction device measures far more fine droplets than the time-shift instrument. The measurements of the latter indicate the presence of a considerable volume fraction in droplets larger than 100 mm, which has not been pointed out before. Analyzing the measurements of variations in atomizer rotational speed and paint flow rate, the laser diffraction device shows notably smaller droplet diameters, and its metrics are more strongly influenced by changes in atomizer rotational speed than those of the time-shift instrument, which is more sensitive to changes in paint flow rate with some metrics. Concerning the differences in absolute values, biases influencing the measurements are being discussed. For the time-shift instrument, a procedure to correct the biased measurements is introduced.

This study was conducted to determine the emission characteristics of volatile organic compounds associated with coating methods including brush, roll, and spray. A concrete waterborne paint, three concrete oil-borne paints, and four wood oil-borne paints were selected in this work. It was observed that the emission of volatile organic compounds from paints was affected by the coating methods. The emission time of volatile organic compounds from a spray painting process was faster than that of brush and roll painting. In contrast, the emission characteristics of volatile organic compounds from coating materials applied by brush and roller was statistically similar. The α-dicarbonyl formation potential in the indoor air according to the reaction of volatile organic compounds and OH radical was also estimated. It was observed that the concentration of alpha-dicarbonyl might reach 2.2 μg/m3 (product A2, spray method). Spray method might help to control volatile organic compounds and the formation of α-dicarbonyl from coating process in the indoor environment more effectively than other methods because the accumulative emission of volatile organic compounds during spray coating process could be removed easily.

The spray painting robots with mounted electrostatic rotating bell (ESRB) atomizers have been widely used to maintain high painting quality for various car models in rapid automotive production. The focus of this study is on developing the optimum coating path pitch while considering automobile painting quality. We define a deposition model optimized for the ESRB atomizer and introduce a method to optimize the path pitch with a cost function for painting thickness uniformity, which plays an important role in painting quality. In addition, experimental results are presented to verify the validity of the optimal path pitch simulation results. By using the results of this study, it is possible to improve the painting quality and thus the productivity of spray painting robots.

This letter describes a system for autonomous spray painting using an unmanned aerial vehicle (UAV), suitable for industrial applications. The work is motivated by the potential for such a system to achieve accurate and fast painting results. The PaintCopter is a quadrotor that has been custom fitted with an arm plus a spray gun on a pan-tilt mechanism. To enable long deployment times for industrial painting tasks, power and paint are delivered by lines from an external unit. The ability to paint planar surfaces, such as walls in single color, is a basic requirement for a spray painting system. But this work addresses more sophisticated operation that subsumes the basic task, including painting on three-dimensional (3D) structure, and painting of a desired texture appearance. System operation consists of (a) an offline component to capture a 3D model of the target surface, (b) an offline component to design the painted surface appearance and generate the associated robotic painting commands, and (c) a live system that carries out the spray painting. Experimental results demonstrate autonomous spray painting by the UAV, doing area fill and versatile line painting on a 3D surface.

In this paper, a novel method for planning spray painting trajectories for industrial robots is presented. The proposed method takes as input an arbitrary parametric description of the end-effector path in the operative space. The method is aimed at providing feasible motion profiles without resorting to optimization routines and without the need for a dynamic description of the painting robot. The motion law is then defined by the algorithm to achieve end-effector speed limitation, in order to comply with the constraints imposed by the spray painting process and by the manipulator specifications. Subsequently, a sequence of look-ahead filtering operations on the speed profiles ensures joint acceleration limitation. The proposed method has been tested on an industrial painting robot, showing its effectiveness, which is experimentally evaluated against the results obtained with the original manufacturer’s proprietary planning method. The improvements include, other then the required end-effector speed and joint acceleration limitation, a sensible reduction of the cycle time, and of the torque effort requirement. The method is of simple implementation and can be useful for other robot-oriented industrial tasks.

Objectives To assess the determinants of airborne solvent exposures in contemporary vehicle collision repair workplaces. Methods Personal, full-shift airborne solvent exposures (n = 97) were assessed in 85 vehicle collision repair workers from 18 workshops. Peak exposures were assessed using a small number of video exposure monitoring measurements. Results Solvent exposures were highest in spray painters (geometric mean = 2.7 ppm) followed by panel beaters (0.5 ppm), but were well below workplace exposure standards. The lowest exposure levels were observed for mixing room extraction located away from the mixing bench [exposure ratio (ER) = 0.51, 95% confidence interval (CI) = 0.30-0.87]. Time spent mixing paint was associated with higher exposures (ER for every 10-min increase = 1.14, 95% CI = 1.05-1.24), as was time spent cleaning equipment with solvents (ER = 1.11, 95% CI = 0.88-1.39), spraying primer (ER = 1.10, 95% CI = 0.96-1.27), and spraying clear coat paint (ER = 1.07, 95% CI = 1.00-1.15). Overall, the combined non-spray painting tasks (mixing paint, degreasing, and cleaning equipment) were more strongly associated with exposure (ER = 1.10, 95% CI = 1.03-1.18) than the combined spray painting tasks (ER = 1.03, 95% CI = 1.00-1.05). Peak exposures ranged from 10 to 1100 ppm with the strongest and most frequent peaks occurring during paint mixing, decanting of solvents, cleaning of equipment, and painting in a cross-draft spray booth. Conclusions Airborne solvent exposures in the collision repair industry were associated with job title, the design and location of exhaust ventilation and emission sources, and time spent on specific tasks, with the highest average and peak exposures shown for non-spray painting tasks. These findings provide a contemporary basis for intervention programmes to reduce airborne solvent exposures in this industry.

Robotic spray path planning is still a challenging task for large-scale structures because deformation is difficult to consider in conventional path planning, which can lead to the nonuniformity of paint film. To overcome this problem, a visual servoing approach based on fringe pattern projection is proposed to optimize the robotic spray path in this paper. In this method, the spray gun orientation is optimized to be perpendicular to the part surface at a desired distance during the spray procedure. Due to the textureless property of the surface of large-scale structures, the fringe pattern is shot onto the surface; thus, the deformed pattern directly reflects the position and orientation of the robot end-effector. Simulation experiments and real scenarios are used to demonstrate the validity and robustness of the proposed method. The results show that the proposed method would make automatic spray painting more feasible for large-scale structures.

A crucial factor for ensuring the reliability of chip packages is the measurement and control of warpage. The warpage of chip packages, printed wiring boards (PWBs), and PWB assemblies (PWBAs) are typically measured by moire techniques (i.e., shadow moire, laser fringe projection, and digital fringe projection), which have noncontact, full-field, and high-resolution capabilities. The application of moire techniques typically involves spraying a mist of reflective paint on the surface of a sample to ensure the uniformity of surface reflectance and to obtain better fringe image contrast and better sinusoidal waveforms in the fringe patterns for the measurement process. However, since painted samples may no longer be re-used, the process of spray painting is not suited for inline inspection; a new technique for measuring warpage without painting is required. In this research, a dynamic digital fringe projection (DDFP) technique for measuring the warpage of unpainted plastic ball grid array (PBGA) packages and boards was developed. The DDFP technique dynamically determines proper fringe intensity distributions for PBGA packages and PWBs and uses them to produce a better fringe image contrast and better sinusoidal waveforms without painting. Experimental results showed that the DDFP technique successfully measures the warpage of PBGA packages and PWBs in unpainted PWBAs accurately.

Value stream is a set of all the specified actions of process (s) for product (s) which are required to convert the raw material into finished product and all the steps through which material has to travel from stage of raw material to become finished goods. After initial research, the group of small enterprises was selected and work was started on them. It is out of which two of them are of same product family and another two produce different types of product. An E-draw software version 6.5.3 consulted by EdrawSoft consultancy, Sheung Wan, HongKong is used for constructing the current and future state maps. After applying VSM on these industries, it is resulted out that abrupt changes are expected in terms of productivity improvement if proposed future state are implemented. There will be the increase in production as 42% in Swan Mechanical Works, 36.46% for Kotla Auto Parts, and 35.37% increase is expected in B.S. Spray Painting Works. Another remarkable change as productivity improvement have been found in unnecessary movements in terms of distance travelled by material for Swan Mechanical Works is reduced by 80.97%, 63.73% decrease is estimated in Kotla Carton Box, and for B.S. Spray Painting Works and Kotla Auto Parts, it is 44.18% and 50% respectively. In this regard, research work concludes that value stream mapping can be saviour of Indian MSMEs.

In this paper we present a unique Fraunhofer approach that aims towards a vision to automate the product preparation in paint shops by automatically generating robot paths and process conditions that guarantee a certain wanted paint coverage. This will be accomplished through a combination of state-of-the-art simulation technology, inline quality control by novel terahertz thickness measurement technology, and surface treatment technology. The benefits of the approach are a shortened product preparation time, increased quality and reduced material and energy consumption. The painting of a tractor fender is used to demonstrate the approach.