Modeling of Complex Parts for Industrial WaterJet Cleaning

Industrial high-pressure waterjet cleaning is common to many industries. The modeling in this paper functions inside a collaborative robotic framework for high mix, low volume processes where human robot collaboration is beneficial. Automation of pressure washing is desirable for economic and ergonomic reasons. An automated cleaning system needs path simulation and analysis to give the operator insight into the predicted cleaning performance of the system. In this paper, ablation, the removal of a substrate coating by waterjet, is modeled for robotic cleaning operations. The model is designed to work with complex parts often found in spray cleaning operations, namely parts containing hidden portions, holes, or concavities. Experimentation is used to validate and calibrate the ablation model to yield accurate evaluations for how well every feature of a part is cleaned based on the cumulative effect of water affecting the part surface. The ablation model will provide the foundation for optimizing process parameters for robotic waterjet cleaning

Simulation and Planning of a 3D Spray Painting Robotic System

Nesta dissertação é proposto um sistema robótico 3D de pintura com spray. Este sistema inclui uma simulação realista do spray com precisão suficiente para imitar pintura com spray real. Também inclui um algoritmo otimizado para geração de caminhos que é capaz de pintar projetos 3D não triviais. A simulação parte de CAD 3D ou peças digitalizadas em 3D e produz um efeito visual realista que permite analisar qualitativamente o produto pintado. Também é apresentada uma métrica de avaliação que pontua trajetória de pintura baseada na espessura, uniformidade, tempo e desperdício de tinta.In this dissertation a 3D spray painting robotic system is proposed. This system has realistic spray simulation with sufficient accuracy to mimic real spray painting. It also includes an optimized algorithm for path generation that is capable of painting non trivial 3D designs. The simulation has 3D CAD or 3D scanned input pieces and produces a realistic visual effect that allows qualitative analyses of the painted product. It is also presented an evaluation metric that scores the painting trajectory based on thickness, uniformity, time and waste of paint

Visual Servoing in Robotics

Visual servoing is a well-known approach to guide robots using visual information. Image processing, robotics, and control theory are combined in order to control the motion of a robot depending on the visual information extracted from the images captured by one or several cameras. With respect to vision issues, a number of issues are currently being addressed by ongoing research, such as the use of different types of image features (or different types of cameras such as RGBD cameras), image processing at high velocity, and convergence properties. As shown in this book, the use of new control schemes allows the system to behave more robustly, efficiently, or compliantly, with fewer delays. Related issues such as optimal and robust approaches, direct control, path tracking, or sensor fusion are also addressed. Additionally, we can currently find visual servoing systems being applied in a number of different domains. This book considers various aspects of visual servoing systems, such as the design of new strategies for their application to parallel robots, mobile manipulators, teleoperation, and the application of this type of control system in new areas

Automatic offline trajectory generation for surface coverage problem from a 3D drawing

Surface coverage with a robot manipulator is widely used in different industrial processes. For this reason having an automated way to program these robots is really important.In this work we implement an iterative algorithm to automate the process of trajectory generation for surface coverage, given the 3D model of the target object, with a particular focus on spray painting process

INKJET PRINTING: FACING CHALLENGES AND ITS NEW APPLICATIONS IN COATING INDUSTRY

This study is devoted to some of the most important issues for advancing inkjet printing for possible application in the coating industry with a focus on piezoelectric droplet on demand (DOD) inkjet technology. Current problems, as embodied in liquid filament breakup along with satellite droplet formation and reduction in droplet sizes, are discussed and then potential solutions identified. For satellite droplets, it is shown that liquid filament break-up behavior can be predicted by using a combination of two pi-numbers, including the Weber number, We and the Ohnesorge number, Oh, or the Reynolds number, Re, and the Weber number, We. All of these are dependent only on the ejected liquid properties and the velocity waveform at the print-head inlet. These new criteria are shown to have merit in comparison to currently used criteria for identifying filament physical features such as length and diameter that control the formation of subsequent droplets. In addition, this study performs scaling analyses for the design and operation of inkjet printing heads. Because droplet sizes from inkjet nozzles are typically on the order of nozzle dimensions, a numerical simulation is carried out to provide insight into how to reduce droplet sizes by employing a novel input waveform impressed on the print-head liquid inflow without changing the nozzle geometry. A regime map for characterizing the generation of small droplets based on We and a non-dimensional frequency, Ω is proposed and discussed. In an attempt to advance inkjet printing technology for coating purposes, a prototype was designed and then tested numerically. The numerical simulation successfully proved that the proposed prototype could be useful for coating purposes by repeatedly producing mono-dispersed droplets with controllable size and spacing. Finally, the influences of two independent piezoelectric characteristics - the maximum head displacement and corresponding frequency, was investigated to examine the quality of filament breakup quality and favorable piezoelectric displacements and frequencies were identified

COMPUTATIONAL ANALYSIS OF FEASIBILITY AND UTILITY OF DIRECT-ADHESION POLYMER-TO-METAL HYBRID TECHNOLOGIES FOR USE IN LOAD BEARING BODY-IN-WHITE AUTOMOTIVE COMPONENTS

Traditionally, metals and plastics are fierce competitors in many automotive engineering applications. This paradigm is gradually being abolished as the polymer-metal-hybrid (PMH) technologies, developed over the last decade, are finding ways to take full advantage of the two classes of materials by combining them into a singular component/sub-assembly. By employing one of the several patented PMH technologies, automotive original equipment manufacturers (OEMs) have succeeded in engaging flexible assembly strategies, decreasing capital expenditures and reducing labor required for vehicle manufacture. The basic concept utilized in all PMH technologies is based on the fact that while an open-channel thin-wall sheet-metal component can readily buckle under compressive load, with very little lateral support, provided by a thin-wall rib-like injection-molded plastic subcomponent, the buckling resistance (and the stiffness) of the component can be greatly increased (while the accompanied weight increase is relatively small). In the present work, the potential of direct-adhesion PMH technologies for use in load-bearing structural automotive components is explored computationally. Within the direct adhesion PMH technology, load transfer between stamped sheet-metal and injection-molded rib-like plastic subcomponent is accomplished through a variety of nanometer-to-micron scale chemical and mechanical phenomena which enable direct adhesion between the two materials. Multi-disciplinary computations are carried out ranging from: (a) computational investigation of the sheet-metal stamping process including determination of the residual stresses and the extent of stamped-component warping; (b) computational fluid mechanics of the filling, packing and cooling stages of the injection-molding process including determination of flow-induced fiber orientation in the molded plastic and the extent of residual stresses and warping in the injection-molded sub-component: and (c) structural-mechanics computational investigation of the effect of injection-molded component residual stresses and warping on their ability to withstand thermal loading encountered in the paint shop and mechanical in-service loading. The results obtained revealed that a minimal level of the polymer-to-metal adhesion strength (5-10MPa) must be attained in order for the direct-adhesion PMH technologies to be a viable alternative in the load-bearing body-in-white (BIW) components. In the present work, also various PMH approaches used to promote direct (adhesive-free) adhesion between metal and injection-molded thermoplastics are reviewed and critiqued. The approaches are categorized as: (a) micro-scale polymer-to-metal mechanical interlocking; (b) in-coil or stamped-part pre-coating for enhanced adhesion; and (c) chemical modifications of the injection-molded thermoplastics for enhanced polymer-to-metal adhesion. For each of these approaches their suitability for use in load-bearing BIW components is discussed. In particular, the compatibility of these approaches with the BIW manufacturing process chain (i.e. (pre-coated) metal component stamping, BIW construction via different joining technologies, BIW pre-treated and painting operations) is presented. It has been found that while considerable amount of research has been done in the PMH direct-adhesion area, many aspects of these technologies which are critical from the standpoint of their use in the BIW structural applications have not been addressed (or addressed properly). Among the PMH technologies identified, the one based on micro-scale mechanical interlocking between the injection-molded thermoplastic polymer and stamped-metal structural component was found to be most promising. Lastly, the suitability and the potential of various polymer-powder spraying technologies for coating metal stampings and, thus, for enhancing the polymer-to-metal adhesion strength in direct-adhesion PMH load-bearing automotive-component applications is considered. The suitability of the spraying technologies is assessed with respect to a need for metal-stamping surface preparation/treatment, their ability to deposit the polymeric material without significant material degradation, the ability to selectively overcoat the metal-stamping, the resulting magnitude of the polymer-to-metal adhesion strength, durability of the polymer/metal bond with respect to prolonged exposure to high-temperature/high-humidity and mechanical/thermal fatigue service conditions, and compatibility with the automotive BIW manufacturing process chain. The analysis revealed that while each of the spraying technologies has some limitations, the cold-gas dynamic-spray process appears to be the leading candidate technology for the indicated applications

PaintNet: Unstructured Multi-Path Learning from 3D Point Clouds for Robotic Spray Painting

Popular industrial robotic problems such as spray painting and welding require (i) conditioning on free-shape 3D objects and (ii) planning of multiple trajectories to solve the task. Yet, existing solutions make strong assumptions on the form of input surfaces and the nature of output paths, resulting in limited approaches unable to cope with real-data variability. By leveraging on recent advances in 3D deep learning, we introduce a novel framework capable of dealing with arbitrary 3D surfaces, and handling a variable number of unordered output paths (i.e. unstructured). Our approach focuses on predicting smaller path segments, which can be later concatenated to reconstruct long-horizon paths. We extensively validate the proposed method in the context of robotic spray painting by releasing PaintNet, the first public dataset of expert demonstrations on free-shape 3D objects collected in a real industrial scenario. A thorough experimental analysis demonstrates the capabilities of our model to promptly predict smooth output paths that cover up to 95% of the surface of previously unseen object instances. Furthermore, we show how models learned from PaintNet capture relevant features which serve as a reliable starting point to improve data and time efficiency when dealing with new object categories

Microsphere-based Disordered Photonic Structures: Control of Randomness in Langmuir-Blodgett Assembly and Radiative Cooling Applications

Many biological photonic structures in nature exhibit a significant degree of disorder within their periodic framework that enhances their optical properties. However, how such disorder contributes to the unique photonic characteristics is not yet fully understood. To facilitate studies on this topic, we investigated self-assembly of microspheres as a method to controllably introduce randomness to photonic structures. Specifically, we examined Langmuir-Blodgett assembly, a layer-by-layer fabrication technique. We developed and experimentally verified a model for the process and determined a condition of surface pressure and substrate pulling speed that corresponds to a maximum structural order in a layer. Along the trajectory described by this condition, disorder can be controllably introduced by increasing the pulling speed. Our model also describes a condition for maximum structural order for multilayer assembly: as the number of layers increases, the surface pressure should also increase at a fixed pulling speed. Overall, we have demonstrated that by carefully choosing assembly parameters along the optimal trajectory, disorders within Langmuir-Blodgett films can be systematically introduced. To further demonstrate usefulness of disordered photonic structures fabricated from self-assembly methods, we investigated radiative cooling performance of microsphere-based disordered materials under direct sunlight. Radiative cooling is a process in which an object passively loses heat via radiation and thus has a potential to reduce consumption of electricity used for thermal management. Toward a goal of making radiative cooling technology more accessible, we investigated two scalable, and inexpensive methods for fabricating microsphere-based structures that can achieve efficient radiation cooling. Specifically, colloidal sedimentation method and spray coating were employed to create coatings that consist of randomly arranged microspheres. With a systematic study of light scattering in microsphere-based disordered media, we showed how structural parameters influence radiative cooling performance. By combining this understanding with the two facile fabrication methods, we demonstrated that black substrates coated with our microsphere-based materials achieved substantial cooling below ambient temperature even under direct sunlight exposure. Our coatings also outperformed commercially available paints designed for daytime cooling, without use of sophisticated fabrication process or expensive materials. We demonstrated further that cooling capability of our microsphere-based structures was improved by using hollow microspheres instead of solid particles and that mechanical durability was enhanced when the hollow microspheres were embedded in a silicone matrix. Overall, this work provides a path toward wider applications of radiative cooling achieved by microsphere-based disordered systems

Multiscale Design And Life-Cycle Based Sustainability Assessment Of Polymer Nanocomposite Coatings

In recent years, nanocoatings with exceptionally improved and new performance properties have found numerous applications in the automotive, aerospace, ship-making, chemical, electronics, steel, construction, and many other industries. Especially the formulations providing multiple functionalities to cured paint films are believed to dominate the coatings market in the near future. It has shifted the focus of research towards building sustainable coating recipes which can deliver multiple functionalities through applied films. The challenge to this exciting area of research arrives from the insufficient knowledge about structure-property correlations of nanocoating materials and their design complexity. Experimental efforts have been successful in developing certain types of nanopaints exhibiting improved properties. However, multifunctional nanopaint design optimality is extremely difficult to address if not impossible solely through experiments. In addition to this, the environmental implications and societal risks associated with this growing field of nanotechnology raise several questions related to its sustainable development. This research focuses on the study of a multiscale sustainable nanocoating design which can have the application from novel function envisioning and idea refinement point of view, to knowledge discovery and design solution derivation, and further to performance testing in industrial applications. The nanocoating design is studied using computational simulations of nano- to macro- scale models and sustainability assessment study over the life-cycle. Computational simulations aim at integrating top-down, goals/means, inductive systems engineering and bottom-up, cause and effect, deductive systems engineering approaches for material development. The in-silico paint resin system is a water-dispersible acrylic polymer with hydrophilic nanoparticles incorporated into it. The nano-scale atomistic and micro-scale coarse-grained (CG) level simulations are performed using molecular dynamics methodology to study several structural and morphological features such as effect of polymer molecular weight, polydispersity, rheology, nanoparticle volume fraction, size, shape and chemical nature on the bulk mechanical and self-cleaning properties of the coating film. At macro-scale, a paint spray system which is used for automotive coating application is studied by using CFD-based simulation methodology to generate crucial information about the effects of nanocoating technology on environmental emissions and coating film quality. The cradle-to-grave life-cycle based sustainability assessment study address all the critical issues related to economic benefits, environmental implications and societal effects of nanocoating technology through case studies of automotive coating systems. It is accomplished by identifying crucial correlations among measurable parameters at different stages and developing sustainability indicator matrices for analysis of each stage of life-cycle. The findings from the research can have great potential to draft useful conclusions in favor of future development of coating systems with novel functionalities and improved sustainability