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Paint path planning for industrial robots is critical for uniform paint distribution, process cycle time and material waste, etc. However, paint path planning is still a costly and time‐consuming process. Currently paint path planning has always caused a bottle‐neck for manufacturing automation because typical manual teaching methods are tedious, error‐prone and skill‐dependent. Hence, it is essential to develop automated tool path‐planning methods to replace manual paint path planning. The purpose of this paper is to review the existing automated tool path‐planning methods, and investigate their advantages and disadvantages.

The approach takes the form of a review of automated tool path‐planning methods, to investigate the advantages and disadvantages of the current technologies.

Paint path planning is a very complicated task considering complex parts, paint process requirements and complicated spraying tools. There are some research and development efforts in this area. Based on the review of the methods used for paint path planning and simulation, the paper concludes that: the tessellated CAD model formats have many advantages in paint path planning and paint deposition simulation. However, the tessellated CAD model formats lack edge and connection information. Hence, it may not be suitable for some applications requiring edge following, such as welding. For the spray gun model, more complicated models, such as 2D models, should be used for both path planning and paint distribution simulation. Paint path generation methods should be able to generate a paint path for complex automotive parts without assumptions, such as presupposing a part with a continuous surface.

The paper makes possible automated path generation for spray‐painting process using industrial robots such that the path‐planning time can be reduced, the product quality improved, etc.

The paper provides a useful review of current paint path‐planning methodologies based on the CAD models of parts.

The purpose of this paper is to establish a paint deposition pattern model applied to robotic air spray painting in order to achieve the accuracy and uniformity of paint film thickness on free‐form surface.

The paper opts for an exploratory study using the curvature circle method for air spray painting on free‐form surface to construct a spray gun model. First, a paint deposition pattern model of ellipse dual‐β distribution is fitted on the basic of experimental data from robotic air spray painting. Second, a spray gun model is proposed using the curvature circle method for air spray painting on free‐form surface. The theoretical result is coincident with the film thickness in verification experiment spraying a cylinder surface. The biggest error of the sample points between the theoretical and experimental results is less than 4 μm, thereby the correctness and effectiveness of the proposed model is validated.

The paper provides a specific theoretical and methodological support for the realization of process planning and simulation system in surface spray manufacturing. It will make the future developed system meet the actual processing requirement. At the same time, it is more representative.

The paper finds an approach to solve paint deposition pattern model suitable to free‐form surface. The present method can be applied to the complex reality of topological relation for actual workpiece surface to be painted.

The purposes of this paper are to review the progress of and conclude the trend for paint thickness simulation for painting robot trajectory planning.

This paper compares the explicit function-based method and computational fluid dynamics (CFD)-based method used for paint thickness simulation. Previous research is considered, and conclusions with the outlook are drawn.

The CFD-based paint deposition simulation is the trend for paint thickness simulation for painting robot trajectory planning. However, the calculation of paint thickness resulting from dynamically painting complex surface remains to be researched, which needs to build an appropriate CFD model, study approaches to dynamic painting simulation and investigate the simulation with continuously changing painting parameters.

This paper illustrates that the CFD-based method is the trend for the paint thickness simulation for painting robot trajectory planning. Current studies have been analyzed, and techniques of CFD modeling have also been summarized, which is vital for future study.

This paper aims to present a new offline robot programming approach for automated trajectory generation on free-form surfaces targeted toward spray painting application.

In this paper, an incremental trajectory generation approach is developed where new paint passes are generated based on paint deposited on the surface as a result of previous paint passes. The trajectory is generated on real surfaces where optimal velocity is calculated using genetic algorithm considering parameters such as surface model, spray gun model, paint distribution model and task constraints.

The developed approach was implemented on various surfaces for different paint distribution patterns, and the simulation results reveal that the approach is flexible and efficient to handle variety in part geometry and paint distribution. From experimental validation and analysis of results thus obtained, the developed approach is highly promising compared to the existing methods.

The approach assumes that the computer-aided design (CAD) model of the surface is available and is limited to surjective surfaces in a structured environment where the spray gun characteristics and process parameters are known beforehand.

The problem of programming a robot manually is overcome by automatically generating a sub-optimal trajectory which can be easily transferred to an industrial robot for spray painting the surface.

This paper discusses a new approach for automated trajectory generation from CAD model. The experimental validation of the developed approach is successfully performed on a highly curved test surface, and obtained results are in agreement with the simulation results.

This paper aims to present a new trajectory optimization approach targeting spray painting applications that satisfies the paint thickness requirements of complex-free surfaces.

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.

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.

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.

Aims to experimental determination of paint flow rate flux for elliptical paint sprays. Paint flow rate flux distribution is necessary for computer simulation of the spray painting process.

Different painting strokes at different spray distances and painting velocities are made on flat surfaces by using paint sprays with elliptical spray areas. Then, thickness measurements are made across the strokes after the paint dries out completely. Thickness distributions are used for determination of the paint flow rate flux distribution by making use of the developed formulation and algorithm.

Finds that it is possible to determine the paint flow rate flux for elliptical paint sprays by making use of the painting strokes made on flat surfaces at different spray distances and painting velocities.

Computer simulation of the spray painting process for elliptical paint sprays is made possible. Simulation software for circular paint sprays has been developed previously by the authors.

Paint flow rate flux distribution is necessary for computer simulation of the spray painting process. Such simulation software has been developed previously by the authors.

Researchers heavily investigated the use of industrial robots to enhance the quality of spray-painted surfaces. Despite its advantages, automating process is not always economically feasible. The manual process, on the other hand, is cheaper, but its quality is prone to the mental and physical conditions of the worker making it difficult to operate consistently. This research proposes a mathematical cost model that integrates human factors in determining optimal process settings.

Taguchi's robust design is used to investigate the effect of fatigue, stability of worker's hand and speed on paint consumption, surface quality, and processing time. A crossed array experimental design is deployed. Regression analysis is then used to model response variables and formulate cost model, followed by a multi-response optimization.

Results reveal that noise factors have a significant influence on painting quality, time, and cost of the painted surface. As a result, a noise management strategy should be implemented to reduce their impact and obtain better quality and productivity results. The cost model can be used to determine optimal setting for different applications by product and by industry.

Hardly any research considered the influence of human factors. Most focused on robot trajectory and its effect on paint uniformity. In proposed research, both cost and quality are integrated into a single objective. Quality is measured in terms of uniformity, smoothness, and surface defects. The interaction between trajectory and flow rate is investigated here for the first time. A unique approach integrating quality management, statistical analysis, and optimization is used.

For high torque-density permanent magnet synchronous in-wheel motor, service life and electromagnetic performance are related directly to winding temperature. The purpose of this paper is to investigate the equivalent stator slot model to calculate the temperature of winding accurately.

This paper analyzes the the law of heat flux transfer in slot, which points the main influence factors of equivalent stator slot model. Thermal network model is used to investigate the drawbacks of conventional equivalent model. Based on the law of heat transfer in stator slot, a new layered winding model is put forward. According to winding type and property of impregnations, detailed method and equivalent principle of the new model are presented. The accuracy of this new method has been verified experimentally.

An accurate equivalent stator slot model should be built according to the low of heat transfer. According to theory analysis, the drawbacks of conventional equivalent stator slot model are pointed: it cannot reflect the temperature gradient of winding; the maximum and the average temperature of winding are much higher than actual value. For the new layered model, equivalent principle is related to winding type and property of impregnations, which makes the new model widely used.

This paper presents a new layered model, and shows detailed method, which is more meaningful for designers. The new layered model takes winding type and property of impregnations into account, which makes the new model widely used. It is verified experimentally that layered model is applicable to not only steady-state temperature field but also transient temperature field.

The Physical Internet (PI) application in a supply chain is explored by automakers to achieve a digital supply chain to challenge timely delivery while maintaining high customised production at the lowest operating cost.

A bi-objective mixed integer model is formulated, where production is performed in multistage manufacturing systems (MMS) and then delivered in a two-level distribution system. Next, a hybrid iterative method algorithm is developed to solve the practical-scale problem within an admissible time. Finally, PI's benefits on production and supply chain operation are discussed through extensive computational experiments in different supply chain configurations.

Three significant findings are obtained. First, PI can achieve a comparable or better service level, while the cost is always lower. Second, PI can improve the utilisation of production and transportation resources. Third, with a more complex supply chain and a higher production cost or truck fixed cost, PI's advantages over traditional supply chain become more vigorous, but the increase in orders will weaken it.

The auto enterprise should adopt a PI-enabled supply chain (PI-SC), especially with the increase of network complexity and specific cost factors.

Importance should be attached to the PI-SC to make customers better involved in the supply chain.

First, the application of PI in the existing plant is described. Second, MMS production with multi-mode transportation is jointly scheduled. Third, the decision support of the PI-SC is provided for auto enterprises.