Automotive Paint Shop Research Articles

Predicting Enamel Layer Defects in an Automotive Paint Shop

The appearance of the painted surface of the vehicle is key in the quality that the automotive customer perceives. The assurance of this quality starts in the automotive paint shop and compromises the effectiveness of the painting process as every paint defect is reworked. This entails material and labour costs, reducing the efficiency of the process and affecting the competitiveness of the product. To improve the efficiency while guaranteeing the quality, predictive control rather than corrective must be implemented. In order to achieve this control, a predictive model of quality is needed. As a first step to generate said model, this article demonstrates the correlation between the variables of the enamel coating process and the quality of the paint film of the vehicle. As there are no available application examples in the industry, a procedure is proposed in which the necessary steps for the creation of an industrial data set and a predictive model of quality are defined. The procedure is tested in an automotive paint shop. As a result, relevant variables for the quality assurance are identified and the correlation between process variables and the resulting quality is verified, concluding that the implementation of predictive control in the process is feasible.

Investigations on a material-specific joining technology for CFRP hybrid joints along the automotive process chain

Due to the excellent mechanical properties fiber-reinforced plastics (FRP) are increasingly being used in technical lightweight products in order to achieve a multimaterial design. Due to different melting temperatures, the use of conventional thermal joining technologies is restricted, and the demand of efficient mechanical and adhesive joining technologies is increasing. Within the scope of this publication, the damage behavior of self-piercing riveted hybrid joints using carbon fiber reinforced plastics and metals is analyzed and evaluated in detail regarding the requirements of the automotive industry. Subsequently, hybrid joints are subjected to a thermal profile, which is modelled on the cathodic dip coating drying process in the automotive paint shop. It is shown that the oven process induces damage in the CFRP to self-piercing full riveted joints, which is shown in the form of fiber breaks as well as inter-fiber breaks and delamination. Also, with regard to these effects, geometric optimizations of the self-piercing rivet are carried out, which prevent damages occurring during the oven process. A combination of both optimizations, resulting from the joining and the oven process, leads to a material- and requirement-compliant joining technology, which enables the low-damage joining of CFRP with metals along the automotive process chain.

Development of a visual inspection system and the corresponding algorithm for the detection and subsequent classification of paint defects on car bodies in the automotive industry

Increasing expectations of customers on the appearance of cars force the automotive paint shops to inspect all car bodies with great care. Currently, skilled workers visually inspect each car body to detect and repair occurring paint defects. However, humans can neither detect nor judge the blemishes objectively and reliably over a longer period. Hence, this paper focuses on the development and validation of an algorithm for a surface inspection system, which improves the accuracy of detecting paint defects through an image processing system. Once they are detected, a reliable classifier is necessary to gain further information about the paint defects. The generated data can be utilized for improving the paint application process and for identifying the perpetrator of the paint defects once the defect classification is operational. As a consequence, the quality control circuit can be shortened, the surface quality of different paint formulae can be evaluated objectively, and actions can be taken in order to reduce the occurrences of certain defect types. This paper presents the physical setup of the visual inspection system and a detailed description of the algorithm for detecting the defects in the acquired images. Further research is essential to generate a classifier to differentiate the types of paint defects.

Vibration Analysis Utilizing Unsupervised Learning

Many manufacturing environments have implemented methods of collecting data from their processes relating to vibration, temperature, or sound. With the data stored, manufacturers can run analytics to plan maintenance schedules and track machine health. However, in many cases, these maintenance schedules and health tracking are largely reactionary, largely implemented through experience rather than through predicting the onset of critical events and taking measures to prevent them. This paper describes a case of using time series data analytics of vibration from an automotive paint shop PVC dispensing pump (doser) attached to a robot using a novel combination of unsupervised learning and feature extraction. The goal is the determination of healthy versus unhealthy data and the implementation of predictive maintenance on the machine cell. Since the robot is a multi-axis robot, direct application of traditional health monitoring methods is lacking; instead a combination of methods suitable to the multidimensional nature of the robotic pumping process is employed. The goal of the first phase of the project is to build the tools to aid in this feature extraction using unsupervised learning and begin to establish a baseline of healthy data versus unhealthy data or fault data. The doser cell has been monitored for six months gathering data from seven sensor sets. Traditional methods of data analysis such as spectral analysis through Fast Fourier Transforms (FFTs) were used to establish the capability of reading vibration signals before moving to feature extraction of the time series data. For feature extraction, a Gaussian Mixture Model is utilized for the learning and the model building. These methods utilized not only determine the vibration of each specific component, but also help differentiate between the nozzle flow rate and angle. In extracting these features from the data, patterns can be traced from the variation of each production process and differentiation can take place based on what is healthy and unhealthy data. The goal of the continuing process phase is to inform the predictive maintenance function to improve equipment uptime.

Influence of the automotive paint shop on mechanical properties of continuous fibre-reinforced thermoplastics

Continuous fibre-reinforced thermoplastics offer advantages over their thermoset counterparts. Thermoplastics are often overlooked, as they must pass through the high temperature automotive paint shop for application in structural body parts. Tensile-, flexural-, and impact properties of polyamide 6, polyamide 66, and polyphthalamide reinforced with woven glass fibre fabrics were investigated. It is shown that the entire painting process mostly yielded a predominant improvement on the investigated mechanical properties of glass fibre-reinforced polyamide 6 due to a raised degree in crystallinity. There is no unanimous trend visible for glass fibre-reinforced polyamide 66. The examined shear properties of glass fibre-reinforced polyphthalamide were decreased by the painting process.

Accelerated dynamic programming algorithms for a car resequencing problem in automotive paint shops

• Novel exact and heuristic algorithms for resequencing cars to minimize setup costs in automotive paint shops are proposed. • Incorporating strong lower and upper bounds in the dynamic programming framework reduces computation time significantly. • Proposed algorithms are more efficient than existing approaches and also more practically applicable. • Shows well-tailored exact algorithms can be more efficient than meta-heuristic algorithms. In this paper, a car resequencing problem (CRP) for automotive paint shops is considered, whereby a set of cars conveyed from an upstream shop to one of the multiple conveyors is retrieved sequentially before the painting operation. The aim of the CRP is to find a car retrieval sequence that minimizes the sequence-dependent changeover cost, which is the cost that is incurred when two consecutive cars do not share the same color. For this problem, we propose accelerated dynamic programming (ADP) algorithms that utilize strong combinatorial lower bounds and effective upper bounds in a standard dynamic programming framework, thus outperforming existing exact algorithms. Testing of our algorithms over a wide range of instances confirmed that they are more efficient than the existing approaches and are also more applicable in practice.

Modelling Electrical Energy Consumption in Automotive Paint Shop

Industry players are seeking ways to reduce operational cost to sustain in a challenging economic trend. One key aspect is an energy cost reduction. However, implementing energy reduction strategy often struggle with obstructions, which slow down their realization and implementation. Discrete event simulation method is an approach actively discussed in current research trend to overcome such obstructions because of its flexibility and comprehensiveness. Meanwhile, in automotive industry, paint shop is considered the most energy consumer area which is reported consuming about 50%-70% of overall automotive plant consumption. Hence, this project aims at providing a tool to model and simulate energy consumption at paint shop area by conducting a case study at XYZ Company, one of the automotive companies located at Pekan, Pahang. The simulation model was developed using Tecnomatix Plant Simulation software version 13. From the simulation result, the model was accurately within ±5% for energy consumption and ±15% for maximum demand after validation with real system. Two different energy saving scenarios were tested. Scenario 1 was based on production scheduling approach under low demand situation which results energy saving up to 30% on the consumption. Meanwhile scenario 2 was based on substituting high power compressor with the lower power compressor. The results were energy consumption saving of approximately 1.42% and maximum demand reduction about 1.27%. This approach would help managers and engineers to justify worthiness of investment for implementing the reduction strategies.

Modelling the deformation of continuous fibre-reinforced thermoplastics subjected to hygrothermal loading

For the application of continuous fibre-reinforced thermoplastics in car body structures it has to be ensured that they can pass through the automotive paint shop. There are substantial chemical, hygroscopic and thermal impacts throughout this process that can affect the shape of such components. The aim of this study is to model the deformation behaviour of continuous fibre-reinforced thermoplastics under hygrothermal loading. Relaxation tests were performed to assess temperature-dependent and viscoelastic behaviour. Input parameters for temperature and moisture distribution were determined experimentally and computed using finite difference method. A straightforward approach based on classical laminate theory is presented that comprises anisotropic viscoelasticity as well as hygroscopic, thermal and polymer-chemical effects. The introduced phenomenological model was successfully used to describe the deformation of five different laminate layups both dry and fully saturated with moisture.

A study on implementing color-batching with selectivity banks in automotive paint shops

The color-batching problem is frequently raised in automotive paint shops. This paper focuses on the implementation issues in obtaining color-oriented batches of cars with selectivity banks prior to painting. Two batching strategies, conventional physical resequencing and integrated physical & virtual resequencing, are considered. A rule-based fill approach and a heuristic-based release approach are presented, which can be jointly utilized on a rolling horizon basis when the strategy of conventional resequencing is applied. Moreover, two virtual resequencing techniques are introduced, both of which can be individually integrated into physical resequencing while integrated resequencing is used. Computational experiments are carried out to evaluate the performance of the proposed strategies and approaches. It is shown that integrated resequencing can generally obtain noticeably better batching results than conventional resequencing. Additionally, the impact of several factors on color-batching, including bank configuration, WIP, and size of look-ahead area, are discussed.

The Hidden Benefits of an LED Lighting Upgrade in an Automotive Paint Shop

Retrospective energy optimization in a continuous manufacturing environment, such as an automotive paint shop, is limited in scope. This is due to the difficulty in not having a negative impact on production speeds.Typically, energy projects target one of three types of improvement: business process change (for example, optimizing start-up times or reducing idle times); technical interventions (for example installing variable speed drives); or capital replacement (for example, installing more efficient motors).Out of the four main process activities in an automotive plant, up to 75% of the total plant's energy bill can be attributed to the paint shop.The quality of output in a paint shop, in terms of color matching and paint quality, needs to remain at a constant 100% - this means that there is an inspection process at each major activity.Besides the need for facility level ambient lighting, the need for high quality task lighting is critical to keep the quality of the painting process at the required standard.With the higher quality of LED lighting now available, there is an opportunity for industrial scale retrofits to make relatively large energy savings. This has been successfully demonstrated in a large European automotive paint shop involving the retrofit of 12,600 T8 LED tubes and replacement of 200 high bays and area lights to LED versions. This has reduced the electricity usage by 1.2 MW per hour in the paint shop.This article will outline the project from concept to delivery, show the financial benefits derived from retrofitting lamps rather than installing new fittings, and will describe the other hidden benefits, such as the increase in downstream defect rate detection, that have arisen as a result of the project.

Development of Universal Portable Spray Stand for Touch-Up Process in The Automotive Paintshop

A spray stand is a custom-made tool used to hold the automotive body parts as well as the devices used to facilitate the operator during the Touch Up process in Paint shop production. This paper discusses about the development of Universal Portable Spray Stand (UPSS) as a tool to hold various types of automotive body parts and model of car during the painting process. The main objective of this study is to determine the effective application of UPSS at the International College of Automotive (ICAM) and also in the automotive industry. This will be helpful to add features to the current spray stand in ICAM and to add value to the spray stand based on selected criteria which are universal, portable and cost saving. In addition, study in the UPSS is also expected to bring reduction in cycle time during the touch up process, in the paint defects and in the ergonomics issues among the operators.

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Quality flow model in automotive paint shops

Improving paint quality is of significant importance for vehicle manufacturing. In this paper, a quality flow model is presented to analyse and improve quality in automotive paint shops. Specifically, we study the vehicle-painting process with multiple inspection stations. After each inspection, vehicles failed to achieve quality requirement will be repaired before moving to the next operation. In such systems, the quality variations may propagate along the painting process. To address this, a three-state quality flow model has been developed, and analytical formulas to evaluate product quality have been derived. In addition, to improve quality performance, a bottleneck analysis method has been introduced to identify the most critical stage that impedes product quality in the strongest manner. Two case studies at automotive paint shops are introduced to illustrate the applicability of the method.

Energy Savings in Automotive Paint Ovens: A New Concept of Shroud on the Carriers

The rising cost of energy and increasing emphasis on environmental issues in today's world make it necessary to search for energy conservation methods in automotive paint shops. Paint curing ovens consume a sizeable portion of the total energy utilized. We present here an overview of the energy consumption in paint ovens, followed by a novel method to reduce the energy consumption. Although conventional ovens are designed to operate very efficiently, the carriers used to traverse the bodies in white (BiWs) in a paint shop also take part in heat transfer in an oven, and thus waste energy. Proposed here is a concept of using a shroud to cover the carriers and partially shield them from hot air of the oven. The concept is evaluated using a semicomputational model of an actual paint oven bake process. The computational model uses a computational fluid dynamics (CFD) and a thermal solver to obtain detailed metal temperatures on a BiW and carrier as they traverse in the oven. The numerical results of temperature rises in an unshrouded carrier are compared to that from a shrouded carrier. It is seen that the usage of a shroud results in a significant reduction in the energy consumption of an oven.

Quality bottleneck transitions in flexible manufacturing systems with batch productions

A Markov chain model to analyze quality in flexible manufacturing systems with batch productions is developed in this article. The cycles when good quality and defective parts are produced are defined as the good and defective states, respectively, and transition probabilities are introduced to characterize the changes between these states. The product quality is presented as a function of these transition probabilities, and the transition that has the largest impact on quality is referred to as the quality bottleneck transition (BN-t). Analytical expressions to quantify the sensitivity of quality with respect to transition probabilities are derived, and indicators to identify the BN-t based on data collected on the factory floor are developed. Through extensive numerical experiments, it is shown that such indicators have a high accuracy in identifying the correct bottlenecks and can be used as an effective tool in quality improvement efforts. Finally, a case study at an automotive paint shop is presented to illustrate the applicability of the method.

Modeling Quality Propagation in Automotive Paint Shops: An Application Study

Improving paint quality is of significant importance for vehicle manufacturing. In this paper, a quality propagation model is presented to analyze and improve quality in automotive paint shops. Specifically, we study the vehicle painting process with multiple inspection stations. After each inspection, vehicles failed to achieve quality requirement will be repaired before moving to the next operation. In such systems, the quality variations may propagate along the painting process. To study it, a three-state quality propagation model has been developed, and analytical formulas to evaluate product quality have been derived. In addition, to improve quality performance, a bottleneck analysis method has been introduced to identify the most critical stage that impedes product quality in the strongest manner so that its improvement will lead to the largest improvement of the whole system. To illustrate the applicability of the method, a case study to improve paint quality at an automotive paint shop is introduced.

Automotive finishing: Improving filtration in the automotive paint shop

Environmental pressures are driving changes in filtration in the automotive finishing business. Jane Howarth and Professor S Anand of the Centre for Materials Research and Innovation at the University of Bolton argue that a fundamental look at the process is required to find the best possible outcome.

Energy-Efficient Production Systems Through Schedule-Based Operations

Control of production operations is considered as one of the most economical methods to improve energy efficiency in manufacturing systems. This paper investigates energy consumption reduction in production systems through effective scheduling of machine startup and shutdown. Specifically, we consider serial production lines with finite buffers and machines having Bernoulli reliability model. This machine reliability model is applicable in production situations, where the downtime is relatively short and comparable to machine cycle time (e.g., automotive paint shops and general assembly). In this paper, using transient analysis of the systems at hand, an analytical performance evaluation technique is developed for Bernoulli serial lines with time-dependent machine efficiencies. In addition, tradeoff between productivity and energy-efficiency in production systems is discussed and the energy-efficient production problem is formulated as a constrained optimization problem. The effects and practical implications of operations schedule are demonstrated using a numerical study on automotive paint shop operations. Note to Practitioners - This paper develops an effective analytical tool to evaluate the performance of production systems with time-varying parameters of machine reliability. Using this tool, production engineers and managers can predict the performance of the production systems in real-time with high accuracy. In addition, based on this tool, production operators can determine the machine startup and shutdown schedule based on the current status of the line and production requirement. Numerical experiments show that significant energy savings can be obtained by applying effective machine operations schedule.

Indicators for quality improvability and bottleneck sequence in flexible manufacturing systems with batch production

In this paper we study product quality in flexible manufacturing systems with batch production using a Markov chain model. To improve the quality performance in such systems, the notions of quality improvability and bottleneck sequence are introduced. Indicators for identifying the quality improvability and bottleneck sequence, based on data measured on the factory floor rather than complicated calculations, are developed. A case study of improving quality at an automotive paint shop is introduced.

Numerical prediction of thermal panel distortion in automotive paint shop

Challenging automotive design in the face of modern lightweight strategies for weight reduction as well as legislative regulations, impose higher requirements for future car body development. This trend has led to the use of thinner sheet metal blanks and implies the need for narrow process windows especially within the coating process where thermal loads might cause local shape deviations. Moreover, developments in multimaterial design induce material configurations with complex deformation behaviour due to different expansion characteristics. For this reason, there is a need to improve the numerical prediction of surface quality in the early car development process. This paper deals with the effect of thermomechanical material properties relating to the final part characteristics, whereby the influence of time and heat dependent material properties affecting the yield point and flow characteristics is shown. In further investigations, the influence of initial yield strength, pre-stretching and subsequent thermal loads to the final yield strength is dealt with.