Automobile Manufacturing Plant Research Articles

Variability modeling of products, processes, and resources in cyber–physical production systems engineering

Cyber-Physical Production Systems (CPPSs), such as automated car manufacturing plants, execute a configurable sequence of production steps to manufacture products from a product portfolio. In CPPS engineering, domain experts start with manually determining feasible production step sequences and resources based on implicit knowledge. This process is hard to reproduce and highly inefficient. In this paper, we present the Extended Iterative Process Sequence Exploration (eIPSE) approach to derive variability models for products, processes, and resources from a domain-specific description. To automate the integrated exploration and configuration process for a CPPS, we provide a toolchain which automatically reduces the configuration space and allows to generate CPPS artifacts, such as control code for resources. We evaluate the approach with four real-world use cases, including the generation of control code artifacts, and an observational user study to collect feedback from engineers with different backgrounds. The results confirm the usefulness of the eIPSE approach and accompanying prototype to straightforwardly configure a desired CPPS.

IoT Real-Time Production Monitoring and Automated Process Transformation in Smart Manufacturing

Conventional automobile manufacturing plants involve intricate assembly, testing, and debugging processes heavily reliant on manual operations. This study aims to explore the application of industrial internet of things (IIoT) and deep learning algorithms to achieve process automation in manufacturing. Firstly, utilizing IIoT technology, OPC UA, and point cloud fitting techniques, a comprehensive modeling of most equipment and materials within the factory is conducted, constructing a digital twin (DT) model as a virtual representation of actual equipment. Subsequently, the study innovatively introduces the deep Q network algorithm, facilitating the automatic transition of the production process and improving production efficiency. Through comparison with ten baseline models, the proposed model demonstrates an improvement in production efficiency of at least four percentage points compared to other models. Experimental validation confirms the effectiveness of the proposed model in the smart factory for electric vehicle manufacturing.

Material substitution to reduce the environmental impacts in construction of car body manufacturing plants

The efficient use of resources is a key driver for reconciling nature and technology in the automotive manufacturing process. Resource efficiency not only considering the final product but also the construction of the manufacturing system is therefore essential for achieving the sustainability goals pursued by global automotive manufacturers. In this context, the substitution of energy-intensive primary materials with renewable raw materials represents a significant potential for reducing the environmental impacts of automotive plant engineering. However, the use of new materials often leads to conflicting objectives in terms of environmental and economic aspects as well as technical feasibility. To ensure an effective contribution to sustainability, it is necessary to evaluate the entire product life cycle of the substitute material, to localize the resulting secondary effects and to develop target-oriented solution concepts. Against this background, an approach is presented for the implementation of material substitution. The feasibility is demonstrated with a case-study on the substitution of energy-intensive steel with renewable wood material for the structural elements of a vertical conveyor pallet in the car body construction. The technical development and series testing is described and subsequently a comparative environmental and economic evaluation is carried out to analyze the potential benefits compared with the status quo while considering the resulting secondary effects. Finally, a potential assessment is made based on a reference body shop.

Long-term influenza antibodies profiles in previously vaccinated and non-vaccinated adults

ABSTRACT The aim of this work is to describe the dynamics of influenza antibodies after vaccination in adults. We conducted a case-cohort serological study in the automobile manufacturing plants of the Renault España S.A. group in Valladolid and Palencia (Spain), including 550 workers (66.9%) previously vaccinated against influenza (group V), and 272 (33.1%) never vaccinated (group NV). A pre-vaccination serum sample was collected, another after 30–40 days and another after 6 months. The dynamics of antibodies were analyzed. A lower seroprotection of NV before vaccination was observed, but an antibody response between 2 and 4 times higher than in V was assessed. After 6 months, antibodies declined in both groups until equalize. Antibodies titers decrease with age, and no differences were found among underlying pathologies. Adults never vaccinated against influenza had lower seroprotection than those previously vaccinated, but influenza vaccination produces a more intense serological response in them, acquiring significantly higher antibody titers than those previously vaccinated. The antibodies, although in lower titers, persist and equalize among both groups at least 6 months after vaccination, which allows the individual to be protected during the entire circulation of the influenza virus in the same season.

Choosing the optimal balance for the production assembly lines at the Volvo car manufacturing plant in Babylon

Choosing the optimal balance for the production assembly lines at the Volvo car manufacturing plant in Babylon

A hybrid model for value‐added process analysis of manufacturing value chains

AbstractIn the digital era, realising intelligent digital transformation is a major challenge in the manufacturing field. Digital transformation means bringing more profit appreciation. To improve the analysis reliability of value‐added processes, this study proposes a method for assessing enterprises value‐adding activities. For this purpose, a hybrid model is constructed based on data and mathematics, bridged by a server. The research builds an element group model that identifies data from different sources, and also gives a mathematical model to describe the relationship of the supply, marketing and service. Taking an automobile manufacturing value chain as an example, to theoretically analyse the composition of value‐added activities. Then, the assembly process of an automobile manufacturing plant was used as a value‐added case study. The simulation results show the impact of changing production layout and product handling angle on the whole value chain. The study can provide new ideas for the intelligent digital transformation of the manufacturing industry.

Effects of individual factors and labor organization on neck pain in auto assembler

Objective: To investigate the influence of individual factors and labor organization on the prevalence of neck pain (hereinafter referred to as neck pain) in automotive assemblers, and to provide a basis for enterprises to optimize neck pain interventions. Methods: A cluster random sampling method was taken in January 2021, at an automobile manufacturing plant in Shiyan, 656 assemblers with ≥1.0 years of service were selected, the "Musculoskeletal Disorder Questionnaire" was used to investigate the incidence and influencing factors of neck pain. Pearson χ(2) test or trend χ(2) test was used to compare the data rates. The influencing factors of neck pain were analyzed by multivariate logistic regression. Results: The prevalence rate of neck pain (hereinafter referred to as the prevalence rate of neck pain) of automobile assemblers within one year was 53.94% (342/634) . The prevalence of neck pain in women was higher than that in men (69.1% vs 48.6%, P<0.01) . The prevalence of neck pain was related to length of service, self-assessment of fatigue, working hours per week, working in the same workshop, rest days per shift, and accumulated rest time per shift (P<0.05) . Multivariate logistic regression analysis showed that the risk of neck pain in women was 2.434 times higher than that in men; The risk of neck pain increased by 18.9% for each hour of work per week; Rest during work was a protective factor for neck pain. The number of rest per shift increased and the risk of neck pain decreased (r=0.405, 0.311, 0.302, 95%CI=0.205~0.803, 0.169~0.572, 0.142~0.642, P<0.05) . Conclusion: The annual prevalence of neck pain was higher in automobile assemblers. Enterprises should fully consider the influencing factors such as gender, working hours per week and the number of breaks when arranging production.

Neck musculoskeletal disorders and their influence factors among welders in an automobile factory

Objective: To explore the prevalence and risk factors of neck musculoskeletal diseases (MSDs) of welders among an automobile factory. Methods: In June 2019, a cluster random sampling method was used to select 677 electric welders from an automobile manufacturing plant in Shiyan City as the survey objects, and a questionnaire survey was conducted using the "Musculoskeletal Disorders Questionnaire" to analyze the prevalence and influencing factors of neck MSDs, and used logistic regression to analyze the relationship between the influencing factors and the prevalence of cervical MSDs. Results: The prevalence rate of MSDs in neck of welders was 54.8% (371/677) . The exposure rate of occupational factors, from high to low, were neckin a bent formord porsure was 71.6% (486/677) , repetitive head movements was 55.1% (373/677) , working in uncomfortable postures was 48.7% (330/677) and neck twisted was 46.8% (317/677) respectively. Sex, age, educational level, length of service, smoking, neck tilt, neck twist, working in uncomfortable posture and head repetitive movements were the risk factors of neck MSDs (P<0.05) . Multiple logistic regression analysis showed that, the main influencing factors of neck MSDs were sex, education level, age, length of service, smoking, neck tilt, working in uncomfortable posture (OR = 2.11, 2.03, 1.83, 1.21, 1.78, 1.90, 1.58, 95%CI: 1.28~3.48、1.47~2.81、1.33~2.52、1.03~1.41、1.22~2.60、1.28~2.83、1.11~2.27, P<0.05) , rest had protective effect on neck MSDs (OR= 0.38, 95%CI: 0.17~0.88, P<0.05) . Conclusion: Welders in automobile factory was highly exposed to occupational risk factors for neck MSDs. Occupational risk factors such as neck in a bent forward posture, working in an uncomfortable posture, prolonged siting, repetitive head movement should be the focus of intervention.

Application of the BASNEF Model in Safety Training in Automobile Manufacturing Plants

After controls, including engineering and management, the final way to control noise is to use hearing protection devices. Due to the lack of a standardized questionnaire regarding investigating workers’ use of hearing protection devices on the basis of the BASNEF behavioral model, the present study was conducted to investigate the effect of health education based on the BASNEF model on the use of hearing protection devices in workers of an automobile manufacturing plant in Iran. This quasi-experimental and prospective intervention study was performed on 80 workers at an automobile manufacturing plant who are exposed to noise levels above 85 decibels and do not use hearing protection devices. In this study, 40 people working in a cast iron foundry were selected as the intervention group, and 40 working in aluminum casting were chosen as the control group. Questionnaires were analyzed at the beginning of the intervention and three months after the intervention in the intervention and control groups. There was no significant difference between the intervention and control groups before the intervention. There was a significant difference between the intervention and control groups after the intervention in the area of knowledge. A significant correlation was observed between the intervention and control groups after the intervention program in all areas of the BASNEF educational model except behavioral intention. In this study, the effect of educational intervention on the use of hearing protection devices was investigated, and with the educational intervention, it was tried to get help from influential people and enabling factors in education based on the BASNEF model. The results showed that the educational intervention based on the BASNEF model can improve the knowledge of individuals in both the intervention and control groups.

Racial disparities in alcohol-related liver disease mortality in a 75 year follow-up study of Michigan autoworkers

BackgroundSuicide, drug overdose, and alcohol-related liver disease (ALD) mortality have been rising in the United States. While suicide and overdose have received a great deal of attention, far less public health concern has focused on chronic ALD. To address this gap, we examine ALD mortality rates, by race, in a cohort of autoworkers to describe trends over the past 75 years, from the peak in automobile manufacturing employment through its decline. MethodsBased on the United Autoworkers-General Motors (UAW-GM) cohort we estimated temporal trends in age-adjusted ALD mortality rates from 1941 through 2015 at three automobile manufacturing plants in Michigan. We compared these rates to county, state, and U.S. rates, directly standardized to the 2000 U.S. census, to assess the roles of race and employment on ALD mortality. ResultsThe overall age-adjusted ALD mortality rate among 41,097 male autoworkers peaked at 46.1 per 100,000 in the 1970s, followed by a gradual decline and a recent rise. Rates were slightly higher for black than white men until early 2000s, when rates increased only for white men. ALD mortality rates in the study cohort tracked national, state, and county rates for white men until the most recent time period, but were lower throughout the study period for black men, especially in the 1970s and 1980s. ConclusionsEmployment in automobile manufacturing may have offered some protection against death from ALD for black men, and loss of those manufacturing jobs may have impacted white men without a college degree more in recent decades.

TQM, employee outcomes and performance: the contingency effect of environmental uncertainty

PurposeThe purpose of this study is to investigate the relationship between total quality management (TQM), employee outcomes and performance. Moreover, how environmental uncertainty (EU) influences the relationship between employee outcomes and performance is regarded in the context of automobile part manufacturing and suppliers of Iran. Four theories namely resource-based view theory, ability, motivation, opportunity framework, contingency theory and quality management theory have been adopted in this research.Design/methodology/approachA research project is conducted in 191 automobile part manufacturing and suppliers plants using the questionnaire method. Confirmatory factor analysis is applied to assess the reliability and validity of the measurement instrument. The correlations between latent constructs are examined through partial least squares method.FindingsThe results show positive relationship between TQM, employee outcome and performance. The EU also moderates the relationship between employee outcome and performance.Research limitations/implicationsIt is recommended that some contextual factors such as culture be noticed in future research studies. Data were collected from Iranian automobile part manufacturing and suppliers plants, which may limit the generalization of results to other organizations in other countries.Practical implicationsIn this paper, some beneficial insights are addressed to assist managers in recognizing the organizational problems, which weaken implementing TQM, employee outcomes and the effect of EU on organizations.Social implicationsBy improving the quality of management practices and employee outcomes, the society gains benefits such as customer satisfaction.Originality/valueThis study contributes to the TQM advance and human resource management literature and provides better foundations for employee outcomes improvement through TQM practices in the Middle East. By investigating the effect of EU, this study fills the current gap in this field.

Operational efficiency of tow trucks: a case based evidence from an Indian automobile manufacturer

PurposeThe purpose of this paper is to examine and model the in-plant operational efficiency of tow trucks of an automobile manufacturing plant. Even though, tow trucks contribute toward the improvement of operational performance, little case-based evidence prevail in the literature. For this purpose, a case study has been conducted in an Indian automobile manufacturer to address the prevailing issues in material handling (MH).Design/methodology/approachInitially, this paper focuses on grouping of the sequence parts and finding the shortest path among the groups. To elucidate this, an analytical framework based on the distance and stuffing quantity is proposed. A fuzzy Dijkstra’s algorithm is used to solve the issues in grouping of the sequence parts and shortest path among the groups.FindingsThis study addressed the four aspects of MH: move cost, time, distance and material by integrating the function of grouping, finding the shortest path and communication with low cost devices. The result shows that logistics routes and activities should not be interrupted by any of the external factors. The availability of stock is a key performance variable to attain efficiency. In addition to this, effective communication between the truck operators and the production line managers is key performance indicator.Originality/valueThe paper helps the automobile practitioners on increasing the efficiency of tow truck by systemizing the routes. Logistics routes and activities should not be interrupted by any of the external factors. The availability of stock is a key performance variable to attain efficiency. In addition to this, effective communication between the truck operators and the line managers is key performance indicator.

The relationship between chronotypes and musculoskeletal problems in male automobile manufacturing workers.

BackgroundPrevious studies have shown that morning types are less sensitive to pain. This study aimed to examine the relationship between chronotypes and musculoskeletal problems in workers with musculoskeletal burdens at work.MethodsThis cross-sectional study included 119 male production workers from a large automobile manufacturing plant. All the participants worked 2 shifts and worked on the automobile assembly line. Data were obtained using structured questionnaires, including the reduced Morningness-Eveningness Questionnaire (rMEQ), and musculoskeletal symptom questionnaire. Participants with an rMEQ score of 18 points or more were defined as morning-type workers (MTWs). Participants whose scores were less than 18 points were defined as neither-type workers (NTWs).ResultsThe arithmetic mean age was 51.8 ± 5.3 years. MTWs and NTWs accounted for 35.3% and 64.7% of the total participants, respectively. Evening- and intermediate-type workers accounted form 6.7% and 58.0% of the participants, respectively. There was no significant difference in the health indicators when the MTW and NTW groups were compared. However, the musculoskeletal symptom questionnaire demonstrated a significant difference between the MTW and NTW groups. In the preceding year, the MTW group had significantly lower musculoskeletal pain and treatment ratios compared to the NTW group (35.7% vs. 62.3%, p = 0.005 and 14.3% vs. 32.5%, p = 0.031, respectively). After adjusting for variables, the odds ratio (OR) for musculoskeletal pain was significantly higher in the NTW group than in the MTW group (OR, 3.112; 95% confidence interval, 1.285–7.535; p = 0.012).ConclusionsIn this study, the musculoskeletal pain ratio was significantly lower for MTWs when compared to NTWs. Chronotypes could play an important role in work-related musculoskeletal disorders. Further, larger-scale, follow-up studies on chronotypes are required to assist in the prevention of musculoskeletal disorders in future.

Self-Corrective Sensor Fusion for Drone Positioning in Indoor Facilities

Drones may be more advantageous than fixed cameras for quality control applications in industrial facilities, since they can be redeployed dynamically and adjusted to production planning. The practical scenario that has motivated this paper, image acquisition with drones in a car manufacturing plant, requires drone positioning accuracy in the order of 5 cm. During repetitive manufacturing processes, it is assumed that quality control imaging drones will follow highly deterministic periodic paths, stop at predefined points to take images and send them to image recognition servers. Therefore, by relying on prior knowledge about production chain schedules, it is possible to optimize the positioning technologies for the drones to stay at all times within the boundaries of their flight plans, which will be composed of stopping points and the paths in between. This involves mitigating issues such as temporary blocking of line-of-sight between the drone and any existing radio beacons; sensor data noise; and the loss of visual references. We present a self-corrective solution for this purpose. It corrects visual odometer readings based on filtered and clustered Ultra-Wide Band (UWB) data, as an alternative to direct Kalman fusion. The approach combines the advantages of these technologies when at least one of them works properly at any measurement spot. It has three method components: independent Kalman filtering, data association by means of stream clustering and mutual correction of sensor readings based on the generation of cumulative correction vectors. The approach is inspired by the observation that UWB positioning works reasonably well at static spots whereas visual odometer measurements reflect straight displacements correctly but can underestimate their length. Our experimental results demonstrate the advantages of the approach in the application scenario over Kalman fusion, in terms of stopping point detection and trajectory estimation error.

The Toxic Legacy of an Industry and it’s Impacts on a Native American Tribe

From the early 1960s through the late 1970s, millions of gallons of paint sludge and other toxic materials were dumped by a large car manufacturing plant into abandoned mines, forested areas, and lands near homes in Ringwood, NJ. As a result, upper Ringwood became riddled with toxic metals in the soil, water and air. This placed a large environmental burden on the people who have lived on this land for generations, the Ramapough Lenape Turtle Clan Nation. Samples of soil, water, plants, and fish from this partially-remediated 500 acre Superfund site (from community-identified areas) were collected by citizen scientists and NYU graduate assistants. Soil samples were collected at different sites throughout upper Ringwood and analyzed for metal contents using a XRF and ICP-OES. Additionally, drinking water samples were collected, at different timepoints, from a local church and tested for metals concentration using an ICP-MS. Results showed that both As and Pb were found in several different soil samples collected around the Ringwood church, at levels exceeding the NJ soil standards of 19 and 400 mg/kg, respectively. Additionally, Pb levels - exceeding the national and federal standard of 15 ppb - were found in drinking water from the church, depending on the faucets tested. As Ramapough children play at the Church area; the Tribes’ tradition of growing their own food; and the fact that both heavy metals can cause acute and chronic diseases, the results were quickly reported back to the community, local governing body and media. These never-before identified contaminated water findings has led to the decision to switch the church water source from a local (previously-untested well) to the municipal water supply. This study demonstrates the importance of community-academic partnerships and citizen science for protecting the environmental health of marginalized populations.This study is supported by NYU NIEHS Center ES-000260-5.

The feasibility of using a combined heat and power system in a car factory with different consumption and investment scenarios

ABSTRACT Decreasing energy consumption, greenhouse gases, and fuel cost motivate researchers toward using Combined Heat and Power (CHP) systems. Of course, finding suitable scenarios for consumption, sales, and investment is very important in using the CHP system. In some countries like Iran due to the non-consideration of the environmental taxes and low fuel prices implementing the CHP projects is still a challenge. Although the economic and technical benefits of CHP projects are truly registered, the methods of financing are still a dilemma. In the present study, the feasibility of using the gas engine to generate electricity and recovering the exhaust waste heat to supply the required heat of a car-manufacturing plant in northeastern Iran was investigated. The different numbers of gas engines to supply heat and electricity were analyzed. Based on the results, the use of three gas engines supplied more than 75% of the annual required heat of the car factory. Also, two different investment scenarios for attracting investors were proposed. These scenarios improved the conditions to attract the investors via displaying the financing landscapes of the project and providing its detailed information. Considering the results, when the car factory is the investor, the strategy of electricity sales to the grid and exhaust heat consumption in the car factory is the most cost-effective selection.

Enhancement in Quality Estimation of Resistance Spot Welding Using Vision System and Fuzzy Support Vector Machine

The current nondestructive testing methods such as ultrasonic, magnetic, or eddy current signals, and even the existing image processing methods, present certain challenges and show a lack of flexibility in building an effective and real-time quality estimation system of the resistance spot welding (RSW). This paper provides a significant improvement in the theory and practices for designing a robotized inspection station for RSW at the car manufacturing plants using image processing and fuzzy support vector machine (FSVM). The weld nuggets’ positions on each of the used car underbody models are detected mathematically. Then, to collect perfect pictures of the weld nuggets on each of these models, the required end-effector path is planned in real-time by establishing the Denavit-Hartenberg (D-H) model and solving the forward and inverse kinematics models of the used six-degrees of freedom (6-DOF) robotic arm. After that, the most frequent resistance spot-welding failure modes are reviewed. Improved image processing methods are employed to extract new features from the elliptical-shaped weld nugget’s surface and obtain a three-dimensional (3D) reconstruction model of the weld’s surface. The extracted artificial data of thousands of samples of the weld nuggets are divided into three groups. Then, the FSVM learning algorithm is formed by applying the fuzzy membership functions to each group. The improved image processing with the proposed FSVM method shows good performance in classifying the failure modes and dealing with the image noise. The experimental results show that the improvement of comprehensive automatic real-time quality evaluation of RSW surfaces is meaningful: the quality estimation could be processed within 0.5 s in very high accuracy.

Yury Nagibin and shadows of the Niernsee House

The article reveals the names of the prototypes of certain characters in Nagibin’s long story My Golden Mother-in-Law [Moya zolotaya tyoshcha] (the mother-in-law being A. Likhachyova, the wife of the director of the Moscow Car Manufacturing Plant ZIL). For the first time we read the names and learn about the destiny of M. and L. Kostromin, the real people behind the characters of Matvey Matveevich, the neighbour, and Nina Petrovna, the female protagonist’s best friend. The life story of these personalities, residents of the legendary Niernsee House in Bolshoy Gnezdnikovsky Lane, enables the authors, who are related to L. Kostromina, to explain the underpinnings of the relationships between the prototypes of Nagibin’s characters, often a mystery for the writer himself, and share first-hand accounts that confirm his amazing flair for imagination. The article uses materials of family lore, the authors’ private archive (letters and photographs), as well as hitherto unsearched materials from state archives.

Design of an Automated Guided Vehicle System for Press Shop of Automobile Manufacturing Plants in India

The study is focused on the implementation of the Automated Guided Vehicle System for the feeding of raw material from storage into the press line in automobile manufacturing companies. The primary objective is to develop an AGV technology which increases the efficiency of the press line by reducing the errors or delay times caused during the feeding of the raw material. The secondary objective is to make a robust system that is in sync with the industrial revolution 4.0 and ensures enhanced safety. For this purpose, the approach is discussed which can satisfy the purpose and which is more efficient and satisfy the objectives of the study. The working of system is explained with flow charts and diagrams.

Workplace processes and employment opportunities for vulnerable social groups

Employment opportunities and conditions of vulnerable social groups are affected by multiple agencies (including unions and employers) and labour market institutions. This study, drawing on iterative long-term research within workplaces, aims to discover the key interrelations among factors that are peculiar to different contexts. The research questions are pursued through a comparison of the treatment of women and migrants, respectively, in an Italian and a US car-manufacturing plant. Labour legislation is particularly important in the US case, whereas in the Italian context employers have more discretion. In both environments, unions have only a limited role.