Paint Shop Research Articles

Психофизиологическое состояние операторов при ротации рабочих недель «день — вечер»

Modern industrial society is characterized by the growing threat of accidents and catastrophes caused by the human factor. This is a very broad concept. It includes many aspects of human interaction with the technogenic environment, including the probability of operator errors caused by the instability of his psychophysiological state, which is incompatible with the strict technological regulations. At the shift work, this instability is often caused by disturbances in the physiological rhythm of sleep — wakefulness followed by a biological conflict between the forced activity and certain phases of the natural circadian rhythm in the cognitive structures of the brain. This situation known for thy night shift modes can also occur in the evening shift modes. However, the influence of the «day — evening» mode on the psychophysiological state of the shift workers is studied to a lesser extent. The objective of this study was to identify the dynamics of the psychophysiological state of the employees of a certain «model» collective of the paint and varnish shop of the automobile plant, working in the shift mode «5 days — 2 days off — 5 evenings». Test persons were tested immediately after the 1st, 3rd and 5th shifts using a questionnaire describing their self-assessment ranked in points according to four categories (scales). Mathematical analysis of the results revealed a weak trend towards a decrease in the psychological indicators during the daytime work week, but a strong and statistically significant decrease in the evening shifts in relation to the daytime. Thus, the investigated rotational mode of work causes an increasing deterioration in the employee state in the evening shifts, which creates a risk of the impact of the psychogenic human factor on the occupational safety.

Solution Approaches for an Automotive Paint Shop Scheduling Problem

In the paint shops of the automotive supply industry, a large number of synthetic material pieces need to be painted every day to provide the large variety of items required for car manufacturing. Because of the sophisticated automated production process and the tight due dates requested by car manufacturers, finding an optimized production schedule becomes a challenging task that is at the present time performed by multiple human planners.In this paper, we formulate and solve a novel real-life paint shop scheduling problem from the automotive supply industry which introduces unique constraints and objectives that do not appear in the existing literature. Additionally, we provide a new collection of benchmark instances based on real-life planning scenarios that can be used to evaluate solution techniques for the problem.An exact approach based on constraint programming is able to provide optimal solutions for smaller instances, but many larger instances could not be solved yet. Therefore, we propose a metaheuristic method based on local search that uses novel neighborhood relations and various ways to escape local optima. Our approach is able to provide feasible solutions for all instances within reasonable running time.

Development and adaptation of the technology of air biotreatment in trickle-bed bioreactor to the automotive painting industry

The automotive painting industry is a source of environmental pollution caused by Volatile Organic Compounds (VOCs) present in the discharged ventilation air. To contribute to the mitigation of this type of air pollution, Ekoinwentyka Ltd. developed – from pilot scale to full scale – and adapted the technology of Compact Trickle Bed Bioreactor (CTBB) whose operating principle builds upon co-current downflow of the gas phase (polluted air) and liquid phase (solution of mineral salts) through a packed bed where active microorganisms are immobilized in the biofilm on the surfaces of packing elements. Pilot-scale bioreactor 0.32 m in diameter and 1.50 m total height had its packed bed inoculated with a consortium of microorganisms dominated by Pseudomonas fluorescens bacteria. During the experimental programme that lasted several months, the flow rate of air drawn from the ventilation system of the painting shop was changing between 1.0 and 10.0 m3/h and the inlet concentration of VOCs ranged from 10 to 200 ppm. By measuring VOC concentration in the purified air, the factor of VOC biodegradation was found to range between 85 and 99%. Based on pilot-scale experiments, full-scale CTBB has been developed 2.8 m in diameter and 10 m total height and installed as an add-on component of the ventilation system of the painting shop. Test operation at gas flow rates up to 6000 m3/h, confirmed VOC biodegradation factor at the level of 85–99% thus proving a positive result of CTBB technology adaptation to the conditions of the automotive painting industry.

Dürr Builds Scalable Paint Shop for E-Car Manufacturer in China

Dürr Builds Scalable Paint Shop for E-Car Manufacturer in China

Color Trend of Residential Houses in Denpasar City as a Sociopsychological Reflection of the Covid-19 Pandemic

Purpose: This study aims to determine the psychological condition of the people in Denpasar City, seen from the phenomenon of the trend of choosing color paint for homes during the COVID-19 pandemic.
 Research method: The survey was conducted in 12 paint shops and buildings spread across Denpasar City. The method used is structured interviews. The research method is qualitative with descriptive presentation. The results of data mining were studied using color psychology theory.
 Results and discussion: Based on the results of the study, it shows that the choice of white and bright colors has implications for the desire of the community to create peaceful, calm, clean and pleasant conditions in their homes during the COVID-19 pandemic.
 Implication: The color selection implicitly shows the expectations of the people of Denpasar City. Hopes for a better future, which had rocked many sectors of life during the COVID-19 pandemic.

Thickness sensor for drying paints using THz spectroscopy.

Optical terahertz technology has, despite its exciting properties, such as transparency of visibly opaque materials, 30 years after its technological breakthrough, not found a widespread application with societal relevance. Main causes are its maturity and costs. If, however, the uniqueness of both THz radiation and time-domain spectroscopy is used to close a technological gap in the right market sector, we here show that successful applications are in reach. We have chosen the automotive industry, where the optimization of coatings applied in the paint shop is of longstanding concern for this most expensive unit of the car production line. Here we report on the development of a THz-based sensor system. We study the light-matter interaction of drying polymer coatings and use advanced novel signal processing algorithms to determine the state of matter of drying paints. This very first sensor system for the inspection of wet coatings that accurately predicts the eventual dry thickness without requiring paint-type calibration. Industrial robustness is guaranteed by a bespoke optical beam design. Our sensor demonstrator outperforms state-of-the-art thickness sensors applied on dry coatings by a factor three and is expected to become a game changer for the paint shop, where today's scrap rates worldwide are as high as one car body per minute.

BiDrac Industry 4.0 framework: Application to an Automotive Paint Shop Process

To implement an Industry 4.0 Framework in an ongoing industrial manufacturing process to prepare it for complex Artificial Intelligence use cases is not an easy task. The automotive industry is undergoing a large transformation due to a variety of disruptive factors through the introduction of CASE (Connected, Autonomous, Shared, Electrified) technologies. Production improvements will enable future development of CASE capabilities. This paper presents an Industry 4.0 framework, named BiDrac, that integrates computing, communication and control under an Industrial Cyber–Physical​ System (ICPS) ecosystem. It combines Artificial Intelligence and Industrial Internet of Things (IIoT) inside the Industry 4.0 paradigm for the Predictive Maintenance of an Automotive Paint Shop Process inside an Industrial Cloud (IC) as an open platform that provides community of cloud-based solutions to enable the development of new digital solutions. Several real use cases of the proposed platform have been included in the results section to illustrate the potential of the proposed framework.

Two approaches to car sequencing in the paint shop

The problem of car sequencing has been considered in the literature many times, but very often with the assumption of many simplifications, which meant that the discussed issue was far from the problems occurring in reality. The article presents an attempt to capture the real problem of sequencing, in particular in paint shop, because from the point of view of economic indicators, painting process is today a complex, multistage, extremely energy consuming and cost intensive operation. The main goal is therefore to minimize the number of costly changeovers of painting guns, resulting from color changes and synchronize those with periodic cleanings, forced by technological requirements. For this purpose, a buffer located in the paint shop is applied. In the paper a game-theoretic framework is presented to analyze the considered problem. Two games: Buffer Slot Assignment Game and Buffer-OutShuttle are compared with algorithms based on priority rules. Based on the performed simulations the effectivity of presented algorithms is verified using several datasets.

Constraint-based Scheduling for Paint Shops in the Automotive Supply Industry

Factories in the automotive supply industry paint a large number of items requested by car manufacturing companies on a daily basis. As these factories face numerous constraints and optimization objectives, finding a good schedule becomes a challenging task in practice, and full-time employees are expected to manually create feasible production plans. In this study, we propose novel constraint programming models for a real-life paint shop scheduling problem. We evaluate and compare our models experimentally by performing a series of benchmark experiments using real-life instances in the industry. We also show that the decision variant of the paint shop scheduling problem is NP-complete.

Mathematical modeling and heuristic approaches for a multi-stage car sequencing problem

This paper addresses the scheduling problem in three successive processes in car production including the paint shop, painted body storage (PBS) and the assembly shop. The paint shop, which aims to reduce the costs for color changes, is connected to the final assembly shop, which aims to level the usage of the options. A linear PBS is set in between to change the sequence from the upstream shop to the downstream shop. The joint sequencing problem is formulated as a mixed integer linear programming (MILP) model and some properties including the lower bounds are presented. A structural architecture is designed to solve the large-scale real-life instances, and several meta-heuristic algorithms are embedded in the architecture to enhance the ability of finding good solutions. Numerical experiments validate the quality of the proposed algorithms.

Achieving Energy Efficiency With Led Lighting

Abstract Rational use and energy management is very important for the business of industrial companies. This paper will present some of the measures to establish energy efficiency in the company. The realization of the project of improving energy efficiency by replacing the existing lighting with new, more energy efficient, LED lighting in order to reduce electricity consumption and emissions will be presented. A previous lighting design in the production halls will be presented. Nine production halls will be analysed, as well as a paint shop that requires equipment in Ex proof design. Analysis and modelling of electricity consumption, proposals and measures to improve energy efficiency will also be presented. The choice of appropriate LED lighting and Ex LED lighting with photometric calculations is crucial. This is followed by the determination of energy and economic savings, evaluation of the proposed measures, as well as the calculation of CO2 emission reductions. The management system and monitoring of electricity consumption, as well as future planned measures with LED lighting will also be presented in this paper.

Conversion of volatile organic compounds in a twin surface dielectric barrier discharge

A voltage and power controlled surface dielectric barrier discharge for the removal of volatile organic compounds (VOCs) from gas streams is studied by means of current–voltage measurements, flame ionization detectors, and gas chromatography–mass spectrometry (GC–MS). The discharge is generated in a defined synthetic air gas stream at atmospheric pressure by application of a damped sinusoidal voltage waveform resulting from a resonant circuit. Multiple organic compounds, namely n-butane, butanol, isobutanol, ethyl acetate, diethyl ether, and butoxyethanol, are tested at concentrations of 50, 100, 200, and 400 ppm (parts per million), as well as peak-to-peak voltages of 8 to 13 kVpp and pulse repetition frequencies of 250 to 4000 Hz. The dissipated power within the system is calculated utilizing the measured voltage and current waveforms. The conversion and absolute degradation of the VOCs are determined by flame ionization detectors. An increasing concentration of VOCs is found to increase the dissipated power marginally, suggesting a higher conductivity and higher electron densities in the plasma. Of the applied VOCs, n-butane is found to be the most resistant to the plasma treatment, while higher concentrations consistently result in a lower conversion and a higher absolute degradation across all tested compounds. Corresponding amounts of converted molecules per expended joule are given as a comparable parameter by weighting the absolute degradation with the dissipated power. Finally, specific reaction products are determined by online GC–MS, further confirming carbon dioxide (CO2) as a major reaction product, alongside a variety of less prevalent side products, depending on the structure of the original compound. The findings of this study are intended to promote the development of energy efficient processes for the purification of gas streams in both, industry and consumer market. Potential applications of the presented technique could be found in car paint shops, chemical plants, hospital ventilation systems, or air purifiers for living space.

Careful Timing - High Paint Shop Throughput in a Small Space

Careful Timing - High Paint Shop Throughput in a Small Space

Artificial Intelligence for Paint Shops

Artificial Intelligence for Paint Shops

Decomposition-based real-time control of multi-stage transfer lines with residence time constraints

It is commonly observed in the food industry, battery production, automotive paint shop, and semiconductor manufacturing that an intermediate product’s residence time in the buffer within a production line is controlled by a time window to guarantee product quality. There is typically a minimum time limit reflected by a part’s travel time or process requirement. Meanwhile, these intermediate parts are prevented from staying in the buffer for too long by an upper time limit, exceeding which a part will be scrapped or need additional treatment. To increase production throughput and reduce scrap, one needs to control machines’ working mode according to real-time system information in the stochastic production environment, which is a difficult problem to solve, due to the system’s complexity. In this article, we propose a novel decomposition-based control approach by decomposing a production system into small-scale subsystems based on domain knowledge and their structural relationship. An iterative aggregation procedure is then used to generate a production control policy with convergence guarantee. Numerical studies suggest that the decomposition-based control approach outperforms general-purpose reinforcement learning method by delivering significant system performance improvement and substantial reduction on computation overhead.

ERGONOMIC CONDITIONS ASSESSMENT OF A BUS FACTORY


 Eventhough the production technology and capacity have been improved, manpower is indispensable. Coach production industry is one of the heavy industries. Production processes are mostly manpower in addition to automation and mechanization in these factories. Ergonomics is the one of the most important subject to increase the production efficiency and job security in heavy industry factories which use manpower heavily. Ergonomics is the field which aims to reduce the accidents and job related illnesses, anatomic problems in human body, psychological and physiological fatigue and minimize the workforce loss. Ergonomic statement evaluation is possible with providing ergonomic criteria such as anthrometric, environmental condition, and work place.
 
 In this study, some experimental studies are done in order to evaluate the ergonomical conditions in chassis frame production, cataphoresis, paint shop, assembly, and quality inspection processes. The experimental studies include static and dynamic anthrometric measurements on a choosen process and experimental subject workers. The environmental conditions namely, temperature, humudity, lightening, air quality, and noise level are periodicly meausured with proper measuring devices and these data are recorded. The results are used to make an inference with comparing literature. Furthermore, inconvenient results are studied in order to determine the relation with work accidents, work related illnesses and total efficiency parameters in the factory. This study is considered to be a guidance for the effects of ergonomical conditions on workplace safety and health, work accidents and occurences, and production efficiency.

Application of Semi-Analytical Methods in Production Systems Engineering

Production lines can be designed by an analytical, semi-analytical, or numerical approach. This paper gives a brief introduction to the analytical approach of a single buffer line, the aggregation method, and the analytical approach of a multi-buffer line. An automotive paint shop production system will be used as a figurative example to compare the aggregation method and the recently developed analytical approach for a multi-buffer line. A discussion at the end will show the advantages and disadvantages of the analytical approach.

Digital Process Monitoring in the Paint Shop

Digital Process Monitoring in the Paint Shop

Biomarkers of susceptibility and effect in car painters exposed to organic solvents.

Introduction: Car painters are routinely exposed to organic solvents classified as carcinogenic and mutagenic substances. Objective: To characterize the population susceptibility and evaluate the genotoxic effects of exposure to organic solvents. Methods: A cross-sectional study comparing a group of car painters exposed to organic solvents with a non-exposed group. CYP2E1 polymorphisms and the presence of micronuclei in lymphocytes were determined. Results: One hundred twenty-two workers participated in the study: 62 who worked in car paint shops and were exposed to solvents, and 60 who were not exposed. There were statistically significant differences between the two groups regarding micronucleated cells and nucleoplasmic bridges frequencies (p= 0.042 and p= 0.046, respectively; exact likelihood ratio). Significant differences were found at the interaction between the CYP2E1 genotype c1c1 and occupational exposure to solvents, with higher frequencies of micronuclei (p= 0.013) and micronucleated cells (p= 0.015). However, when the frequencies of micronuclei, micronucleated cells and nucleoplasmic bridges in the exposure group were compared between the c1c1 and c2c2/c1c2 allele groups of the CYP2E1 polymorphism, statistically significant differences were found. Conclusions: This study confirms that when workers with CYP2E1 polymorphisms, specifically the c1c1 genotype, are exposed to organic solvents, they are more likely to have somatic cell mutations, a condition associated with increased susceptibility to diseases such as cancer

The extent of job automation in the automobile sector in South Africa

This study argues that the automobile sector’s body shop is fully automated, the paint shop is 80% automated, there is about 20% technology utilization in the car assembly line, and the supply for logistics is making a lot more use of machines as well. These percentages are an indicator of how workers have lost the contest with technology in the industry. Many workers are being deskilled and the remaining workers are being reshuffled to assembly lines likely to be automated with time. There should be interventions to ready the workers to adapt to society and the economy, or there will be massive unemployment.