Production Of Automotive Parts Research Articles

Introduction of Collaborative Robotics in the Production of Automotive Parts: A Case Study

Incorporating collaborative applications constitutes a challenging and increasingly intricate objective within the context of small and medium-sized enterprises (SMEs). This challenge stems from the shortage of highly specialized personnel in these types of companies when it comes to adopting cutting-edge technologies. The lack of innovation in production processes, however, increases the risk that SMEs will not be able to adapt to rapid changes in the market and the growing needs of consumers, who today are evolving at an unprecedented pace. The importance of adopting collaborative applications can be found in their capacity to harmonize human adaptability with the precision of robotic technology. This synergy contributes to the establishment of a safer work environment while guaranteeing effective and efficient performance. These features not only lead to improved production line performance compared to traditional manual or stationary operations, but also highlight new perspectives in the design, production, and customization of new products. This, in turn, helps companies strengthen their competitiveness in the global market. In this scenario, the primary challenge centers around effectively putting these solutions into practice. Our research aims to highlight how significant benefits can be achieved, both in terms of performance improvements and economically, through the analysis of a simple yet illuminating case study.

Computational Analysis of Mechanical Properties in Polymeric Sandwich Composite Materials.

This article focuses on the computational analysis of sandwich composite materials based on polypropylene, polyester, glass, and cotton fibers. In the automotive components prepared from these fiber materials, the various components are used in different proportions. Through the manufacturing process, isotropic materials become somewhat anisotropic. Part of this article is aimed at obtaining input values of material characteristics for calculations using finite element analysis (FEM) and the comparison of experimental results with FEM-based material models created using the Digimat 2023.1 software. This article analyzes the modeling of two-phase as well as multiphase composite materials. This work focuses on calculations using FEM according to the test defined in the PR375 standard for loading the finished product in the luggage compartment of a car. The defined methodology enables the application of the FEM-based calculation directly to the product design in the initial phase of research. The construction and production of expensive prototypes and the subsequent production of automotive parts is replaced by computer-based simulation. This procedure makes it possible to simulate several optimization cycles over a relatively shorter time. From the results of computational simulations, it is clear that materials based on PP/PET/glass fibers show a much higher modulus of elasticity than materials created using cotton, i.e., materials of the PP/PET/cotton type. In order to achieve a high strength and stiffness, it is, therefore, appropriate to use glass fibers in the composite materials used for such applications.

Employee Engagement Mediation: Employee Performance Through Employee Loyalty and Organizational Commitment

The automotive parts highly value the quality of production results, so it requires employee involvement to mediate employee loyalty and organizational commitment to improve employee performance. The quality demands of automotive parts production must meet customer standards. Therefore, employee performance determines the desired quality of work. Researchers will investigate the relationship between employee loyalty and organizational commitment by examining how employee engagement influences employee performance. The results of this study can provide input to management for future follow-up. Researchers used descriptive statistics using Smart PLS 4.0 to analyze data and identify factors related to employee loyalty and organizational commitment, which increase company productivity by mediating employee engagement to employee performance. Questionnaires were distributed to 158 employees using Google Forms. Engagement and performance are strongly and positively influenced by employee loyalty. While organizational dedication has a positive and significant effect on employee performance. What significantly mediates the relationship between employee loyalty, organizational commitment, and employee performance is employee engagement, which is strongly correlated with it. Employee loyalty and organisational commitment indirectly affect employee performance through employee engagement, suggesting that these factors may indirectly improve performance through employee engagement.

Mechanical Automation Design and Manufacturing of Production Equipment Combined with Artificial Intelligence Technology and Algorithm Implementation

Abstract This paper explores the impact of artificial intelligence and machine automation on productivity. It focuses on analyzing the production model of machinery automation based on Petri nets. Through the invariant analysis method, the article constructs a model and presents its structure as a correlation matrix. The study results show that the model has an error rate of only 2.26% and an accuracy of 90.14% in terms of operational performance. Regarding time performance, its training time is 3854 seconds and response time is 351 milliseconds, which are better than other algorithms. In the practical application of automotive parts production, the method significantly reduces the busy probability and blocking probability during order processing and material delivery, and also improves the equipment load rate, waiting rate and blocking rate in the production process. This indicates that the Petri net-based method of machine automation production has significant advantages in improving productivity and reducing costs.

Assessing the Feasibility of Cold Forming of Automotive Parts from Quenched and Partitioned Martensitic Stainless Steels

Sheet metal forming is among the most widely employed processes in manufacturing. Its economic feasibility relies on many factors, including the mechanical properties of the processed materials, energy efficiency of the metal‐forming processes, and quality of the manufactured parts. This work focuses on developing a computational approach to assess the mechanical behavior of quenched and partitioned (QP) martensitic stainless steels (MSSs) undergoing cold forming, aiming at the serial production of automotive parts. The Johnson–Cook (J–C) constitutive model and forming limit diagram (FLD) are derived and validated for each alloy using the experimental data from tensile and Nakajima tests. From the simulated FLD, a theoretical forming limit stress diagram (FLSD) is calculated. The latter is used as a fracture criterion for the cold‐forming process. Cold stamping of two automotive parts, B‐pillar and tunnel, is modeled using the J–C constitutive model and the FLSD. It is demonstrated that the tunnel can be successfully cold‐formed from all three studied steels. In contrast, extensive cracking is expected during the cold forming of the B‐pillar from all materials. It is envisaged that these computational models can be employed for the assessment of any comparable part manufacturing procedure from the QP MSSs.

Visual color inspection with a hyperspectral camera: inline application for automotive parts production

The development of cars is becoming increasingly focused on colour, which is a major challenge for both suppliers and manufacturers. Manufacturers must establish strict colour tolerances for each coloured component and specify both colour and appearance. On the other hand, suppliers must maintain colour accuracy in part production, regardless of the type of material used, to ensure acceptance of colour by automotive manufacturers. In the colour industry, colour difference formulas are used to make unbiased judgments about whether manufactured goods should be approved or disapproved. These objective judgments are based on instrumental colour measurements that must accurately predict subjective colour variations. Hyperspectral imaging (HSI) has proven to provide helpful data for a variety of applications in numerous industries, including colour science. To measure and analyse colour differences between automotive parts, we proposed to use conventional colour science algorithms in conjunction with the Specim FX10 hyperspectral camera, which has a flexible infrastructure that can receive data from a Generic Interface for Cameras (GenICam) compatible with the Gigabyte Ethernet interface. The results showed that the use of hyperspectral imaging in production offers great potential for providing real-time colour information so that colour shifts can be detected early and costly errors in the production line can be avoided.

Improving the Quality of Automotive Components through the Effective Management of Complaints in Industry 4.0

The fundamental problems with component production in the automotive industry are the low quality of the components, the high number of failures, and the subsequent number of complaints. The quality of automotive components is a prerequisite for automated production in a SMART Factory 4.0 in the context of Industry 4.0. Managing complaints is a critical area in the automotive manufacturing industry. The primary goal of this article is to indicate the significance of a CRM system and the importance of complaints management in automotive manufacturing, which improves the quality of the process of producing components while improving the quality of the inputs—the quality of materials, the quality of the human factor, and the quality of the services provided in connection with the components. (1) A Slovak company was selected as the subject of this research, which focuses on the production of automotive parts. (2) The methods of research focused on using economic analysis and instruments of quality management such as the QRQC method, FMEA method, the Ishikawa diagram, and the Pareto analysis and Lorenz curve. This article presents the results of complaints about automotive components: locksets in vehicles. (3) This research shows the basic cause of the problem: a bent pin after riveting in the process of producing the components. In the frame of this research, we suggested corrective measures to eliminate the actual causes of failure in the production of the components. The RPN index reached a level below the limit of 150 (the critical level of the customers’ requirements) after implementing the corrective measures. The total costs of complaints in this year were calculated to be EUR 13.575 and the costs will be reduced gradually after changes are implemented in the production process. (4) A new complaints information system and a new training center are beneficial for solving problems in the production of automotive components. The implementation of a CRM system and other systems are prerequisites for solving customer complaints.

Material variability effects on automotive part production process

The current efforts to reduce the carbon footprint throughout the chain in the automotive industry by increased use of recycled materials poses new challenges for materials production and their use. The increase of steel scrap fraction in the current primary steel making processes, used for producing steel sheet metal for automotive components, possibly affects the material properties variability beyond the limits observed in the materials produced today despite mitigating actions in steel production. In this paper material variability increase was modelled by selecting deterministic values outside the range of the material grade used to design and manufacture an automotive part. The values were selected from an experimental data set representing the cold rolled mild steels material class range. The effects were studied numerically on a reverse engineered model of an existing automotive part production process. It was found that the manufacturing feasibility in this particular case is mainly affected by the weighted average plastic strain ratio and less by the degree of planar anisotropy.

THE PROPERTIES OF BÖHLER K340 STEEL DEPENDING ON THE APPLIED HEAT TREATMENT

In the mass production of automotive parts, the tool life of the manufacturing tool is very important from an economic site. The tool life is determined by the material quality and the properties of the tool achieved by heat treatment. Böhler K340 Isodur grade tool steel is considered one of the best cold forming tool steels due to its chemical composition and its electro-slag remelting manufacturing. In our experiments, samples made from this steel were subjected to two different heat treatment technologies. The first one (CT-conventional treatment) was tempered three times at high temperature after high temperature hardening, and the second one (DCT-deep cryogenic treatment) was deep frozen – with nitrogen – after high temperature hardening and then tempered three times at high temperature. After the heat treatment, the pieces were subjected to microscopic, toughness, hardness and wear tests. The results of the measurements showed that the structure of the DCT steel is much finer and more homogeneous than the CT steel, the impact strength is higher, there is no difference in hardness, but the wear resistance of the CDP specimen is better than the CT specimen.

Feasibility of one-shot forming for manufacturing of steel/CFRP hybrid B-pillar

ABSTRACT In this study, the feasibility of one-shot forming for manufacturing of steel/CFRP hybrid B-pillar was investigated using a steel sheet with a CFRP patch. The design of one-shot forming process has been described in three stages. First, CFRP reinforcement was designed to substitute for the steel reinforcements for weight reduction. The thickness of CFRP reinforcement was determined through structural analysis by comparing the strengths of the conventional and hybrid B-pillars. Second, the stamping of B-pillars using only the steel sheet was preliminarily designed to determine a proper blank shape that could be used as an initial blank shape in one-shot forming. Third, one-shot forming of the steel/CFRP hybrid B-pillar was designed by finite element (FE) simulation to investigate if fracture and wrinkling occur during the forming process. The feasibility of the designed one-shot forming was evaluated by experimentally manufacturing a steel/CFRP hybrid B-pillar. The FE simulation and experimental analysis indicated that one-shot forming is efficient and suitable for manufacturing steel/CFRP hybrid structures and can be used for mass production of automotive parts at low cost without an additional assembly process.

Digital Twin-Based Integrated Assessment of Flexible and Reconfigurable Automotive Part Production Lines

The manufacturing industry has witnessed rapid changes, including unpredictable product demand, diverse customer requirements, and increased pressure to launch new products. To deal with such changes, the reconfigurable manufacturing system has been proposed as one of the advanced manufacturing systems that is close to the realisation of smart manufacturing since it is able to reconfigure its hardware, software, and system structures in a much quicker manner. Conventional simulation technologies lack convergence with physical manufacturing systems, and reconfigurable manufacturing lines require the manual construction of production line models for each reconfiguration. This study presents a digital twin-based integrated reconfiguration assessment application that synchronises with real-time manufacturing data and provides accurate, automated simulation functionality to build and analyse a manufacturing system. The paper discusses the architectural design and implementation of the application, an information model, and an assessment model that enable quantitatively assessment on reconfigurations of manufacturing systems from various aspects. The effectiveness of the proposed application is verified via application to an automotive parts production line to assess the reconfiguration indicators of the manufacturing system under different scenarios. The results reveal that the proposed application provides faster and more accurate reconfiguration assessments compared to existing methods. The findings of this study are expected to facilitate accurate and consistent decision making for evaluating the various indicators of production line performance.

Continuous Productivity Improvement Using IoE Data for Fault Monitoring: An Automotive Parts Production Line Case Study.

This paper presents a case study of continuous productivity improvement of an automotive parts production line using Internet of Everything (IoE) data for fault monitoring. Continuous productivity improvement denotes an iterative process of analyzing and updating the production line configuration for productivity improvement based on measured data. Analysis for continuous improvement of a production system requires a set of data (machine uptime, downtime, cycle-time) that are not typically monitored by a conventional fault monitoring system. Although productivity improvement is a critical aspect for a manufacturing site, not many production systems are equipped with a dedicated data recording system towards continuous improvement. In this paper, we study the problem of how to derive the dataset required for continuous improvement from the measurement by a conventional fault monitoring system. In particular, we provide a case study of an automotive parts production line. Based on the data measured by the existing fault monitoring system, we model the production system and derive the dataset required for continuous improvement. Our approach provides the expected amount of improvement to operation managers in a numerical manner to help them make a decision on whether they should modify the line configuration or not.

A concurrent decision-making approach toward uncertainty, vagueness and risk appetite for sustainable manufacturing systems

The present work relates to devising a decision-making framework to select suitably the best material alternative for the production of automotive parts produced through the high-pressure die casting process. The problem has been addressed keeping in view the quintessential aspects of sustainability and energy efficiency in the metal casting process. The presented decision-making approach has the potential ability to handle the uncertainty and vagueness concurrently with the fluctuations in the data for a given phase of time. These have been incorporated through the conceptual framework of the complex interval-valued intuitionistic fuzzy model. Moreover, the psychological behavior of the decision-maker toward risk perspective has also been given due consideration in the devised decision-making framework through the TOmada de Decisao Interativa Multicriterio (TODIM) method based on cumulative prospect theory approach. The proposed approach has been referred to as the complex interval-valued intuitionistic fuzzy TODIM approach. A total of three material alternatives have been evaluated under the influence of eighteen conflicting criteria. Aluminum turns out to be the best material alternative, while on the other hand magnesium alloy was revealed to be the worst-performing among considered materials. Sensitivity analysis revealed the robustness of the ranking results, emphasizing the importance of the risk appetite of the decision-maker. Comparative analysis reveals a strong correlation between the ranking results and hence the validity. The decision-making approach therefore can be employed to promote sustainable engineering practices by minimizing the material wastage in other energy-intensive manufacturing processes.

PENGARUH WAKTU PENGELASAN TITIK (SPOT WELDING) TERHADAP KEKERASAN, KEKUATAN GESER DAN DIAMETER NUGGET PADA BAJA SPCEN 1,6 mm

The development of technology in manufacturing is currently very fast. One of the important processes involved is joining, including the process of resistance spot welding or better known as spot welding. The use of point welding has several advantages, including a neat shape of the joint, the process is faster, the connection is tighter and the operation is relatively easy and does not require filler metal. The connection of relatively thin plate-shaped steel using resistance spot welding is an alternative option that is widely used by the automotive parts production industry. However, there are no data regarding the best time and data regarding the hardness test, nugget diameter, and shear test on SPCEN steel material. This study aims to determine the effect of spot welding time on hardness, shear strength and nugget diameter on SPCEN steel material. This study used an experimental method with a time variable of 1 second, 2 seconds and 3 seconds with standard material SPCEN JIS G 3141, standard hardness testing using DIN 50103 and standard shear testing using ASTM D 1002. equal that is 3.3 mm. The lowest average nugget hardness results are found on steel plates marked with the name ABC, time of 1 second with an average nugget hardness of 116.6 HRB and the highest average nugget hardness is found on GHI steel within 3 seconds with an average nugget hardness of 117 , 9 HRB. The lowest average yield of shear strength is found in ABC steel at 1 second with a maximum shear strength of 294.82 N / m² and a maximum load of 1592.01 Newton, the highest average yield of shear strength is found on steel plates marked with the name GHI time 3 seconds with a maximum tension of 415.89 N / m² and a maximum load of 2245.83 Newton. Thus the longer the spot welding time (spot welding), the greater the current used, the greater the heat generated and the hardness and shear strength become stronger. Shows the best time for spot welding (spot welding) of 1.6 mm SPCEN steel plate in 3 seconds.

Use of CAM Strategies for Tool Movement in Machining Surfaces of Various Shapes

Implementation of the CAD systems in the field of machine design allowed more possibilities for the design of free-form surfaces, which are especially used in the field of shape design within the automotive and consumer industries. The connection of the CAD systems with the CAM machining technologies has brought a revolution in the field of machining these surfaces. What until recently could be machined with a great effort on copy milling machines, where the clay or laminate model was an original, can now be produced using a virtual model, whereby the tool copies the shape of this model. The CAD/CAM systems already offer analyses during design, which can verify the manufacturability of the modelled surface. The CAM systems offer a number of tool movement strategies for machining a given surface. This paper is focused on the selection of the most suitable strategy for machining the shaped surfaces of the active parts of press tools for the production of automotive parts. It points out the importance of the CAD/CAM data needed in the stage of technological preparation of production, because they have a significant impact on the achieved surface quality. This paper deals with strategies of machining a planar inclined surface using horizontal and vertical machining strategies. The next part of the paper deals with machining of the Free Form Surface and the final part of the paper uses the described strategies for machining the shapes of the die cavity for connecting rod fittings. The experimental part is concentrating on the selection of the most suitable strategy of die milling for the production of the connecting rod (car internal combustion engine part). Simulations of production and the production of details from two different materials are realized on individual details of the mould. The resulting quality of the treated surface was evaluated based on the evaluation of surface roughness.

A fully-coupled thermal-stress model to predict the behavior of the casting-chill interface in an engine block sand casting process

The sole use of light alloys in the production of automotive parts might not be the best strategy to reduce the emission of CO2, as for this purpose, one should consider the life-cycle of the final part. One way to address this issue is to increase the in-service life of the components by modifying the manufacturing process. In the first phase of this study, we used a different chill format in the bonded sand casting process for the production of engine blocks, and it was concluded that this method might increase the fatigue life of the component by refining the microstructure. However, to better understand the dynamics of the casting-chill interface, the development of a thermal-stress model was necessary. This paper summarizes the methodology used to develop a thermal-stress model that predicts the evolution of temperature within the casting and the chill and the evolution of gap and/or pressure at the casting-chill interface. The work identified that the gap size between the H13 chill and the casting at the bottom of the chill in the main bearing bulkhead could reach a maximum of 0.17 mm. Additionally, it was found that the heat transfer coefficient decreased from a peak value of 2500 W m−2 K−1 to 500 W m−2 K−1 at a gap size of 0.2 mm. The numerical analysis uncovered a couple of important factors that play a major role in the development of the gap at the interface including the thermal contraction/deformation of the casting; the thermal expansion/deformation of the chill; the constitutive behavior of the casting; the constitutive behavior of the bonded sand mold cap; and, the geometry of the casting-chill interface. Overall, the modeling results show that the interface gap/pressure dynamics are complicated and play a critical role in governing heat transport across the casting-chill interface.

Two Hybrid Approaches to Fatigue Modeling of Advanced-Sheet Molding Compounds (A-SMC) Composite

To reinforce the environmental standards, we need to strengthen the lightening of vehicles and to generalize new composite materials in order to reduce weight. To use these innovative composite materials in the mass production of automotive parts, it is essential to propose a predictive approach of the S-N curves, which must be established for each new composite formulation and for several types of microstructure within real components. Although these preliminary characterizations consume time and money, this paper proposes two hybrid methodologies to predict the fatigue life during the fatigue test. Both methodologies are based on micromechanical modeling which is developed under monotonous loading with fatigue effects under different amplitudes. The suggested methodology is based on an experimental analysis of monotonic behavior under fatigue loading and on multi-scale modeling of damage. In the results, the proposed model and the used approaches are in good agreement with the experimental results.

Accurate sheet metal forming modeling for cost effective automotive part production

Recent implementations of accurate material and tribology models in finite element codes for sheet metal forming process development have the potential to reduce development time and the associated development costs significantly. Adoption of new models requires validated material parameters and assessments of the overall accuracy. The paper presents a study aimed at accuracy estimation by comparing strain measurements and finite element simulation results for a laboratory flat bottom hole expansion test and an industrial automotive component produced at Volvo Cars. The use of the tensile test based Tata Steel Vegter yield locus model results in accurate prediction of dimensions and plastic deformation distribution in sheet metal forming applications.

ETEKINA: Analysis of the potential for waste heat recovery in three sectors: Aluminium low pressure die casting, steel sector and ceramic tiles manufacturing sector

Abstract In the framework of the ETEKINA project, waste energy streams have been analysed at an aluminium automotive parts production facility in Spain, at a steel foundry in Slovenia and at a ceramic tile production unit in Italy. The aim is to recover more than 40% of the waste heat contained in the exhaust streams and reuse it within the industrial plant rather than emitting it to the atmosphere. To select the applications where the profitability of heat recovery can be demonstrated, the flow rates and temperatures of the applicable exhaust streams have been measured and analysed to select the processes for waste heat recovery and it's re-used in the three industrial plants. The demonstration of the cost-effective waste heat recovery is to be made by using heat pipe heat exchangers (HPHEs) and the processes whereby the heat recovery installations will be erected have already been selected. HPHEs were selected as a heat recovery technology due to their advantages and key features over convectional heat exchangers considering space restrictions, pressure drop limitations, and other waste stream challenges. The challenges include high temperature of the waste and the heat sink streams, fluctuations in the waste stream flow rate and temperature, presence of corrosive moisture such as sulphuric acid in the waste stream, and the presence of particles in the waste stream which can cause fouling leading to failure of convectional technologies. Furthermore, HPHEs are maintenance-free and can have payback period of less than three years.

Quality and yield improvement of ductile iron casting by simulation technique

Foundries contribute to production of major automotive parts. These foundries now a days suffering from poor quality and productivity due to different parameters of the casting process. Casting quality depends on the solidification process after pouring. Computerized casting modeling and solidification simulation is being extensively used by foundries to design the casting process for manufacturing of castings before castings are prepared or before equipment is constructed or improved. The basic objective of using computerized casting modeling and solidification simulation is to increase the quality of the casting manufactured, both in the existing produced casting and first ever castings made and to reduce cost expenses. The shop floor trials can be reduced effectively by casting solidification simulation and defect free castings can be assured. The casting simulation approaches are based on finite element method (FEM), finite difference method (FDM), finite volume method (FVM). In this paper an attempt has been made to use finite difference method (FDM) and finite volume method (FVM) for casting solidification simulation and optimization of casting gating system to assure maximal yield. Modeling and simulation of Flange is analyzed in this study. The material for the flange is ductile iron and produced using shell molding process. Ductile iron has wide range of mechanical properties suitable for production of automotive parts. The 3D model of flange and gating system is created using CATIA and it is simulated using Solid CAST and Auto CAST-X software’s. The simulation software results will predict the location and level of shrinkage. Optimization of gating system will improve casting yield. This will suggest the modifications needed in gating system.