Automobile Manufacturing Company Research Articles

Study on the compatibility of a treated effluent from automobile industry with conventional municipal activated sludge process

AbstractThe on-site-treated effluent from an automobile manufacturing company is discharged into the public sewage system for further treatment. However, the upgrade of the treatment plant to reduce the effluent pollutant load led to the discharge limit for phenols being occasionally exceeded. The concern of the water authority prompted a study to investigate whether the toxicity of phenols could affect the performance of the receiving municipal wastewater treatment plant. To this end, mixtures of the industrial effluent and synthetic municipal wastewater were tested in a laboratory-scale activated sludge system. The bioreactor was fed with increasing ratios of the industrial wastewater in the combined influent (from 10 to 50%) over 7 months. No significant differences were observed in the system performance fed only with the synthetic wastewater (during the acclimation stage) or with the industrial wastewater. The bioreactor achieved average removal efficiencies of 70% for phenols even when half of the combined influent was the industrial wastewater. Bearing in mind the question of phenols, an important drawback was the high uncertainty in their determination by the conventional phenol index method due to the matrix effect. To overcome this a spectrophotometric procedure based on the serial dilutions of each pair of influent and effluent samples has been developed. Although strong microbial selection was observed by the changing bioreactor environment, the industrial effluent was found to be fully compatible with further treatment by conventional activated sludge process.

Nexus among green intellectual capital, green information systems, green management initiatives and sustainable performance: a mediated-moderated perspective

PurposeSustainability issues are crucial in today’s competitive environment. The integration of technology plays a vital role in the attainment of sustainability objectives. The study aims to investigate the relationship between green intellectual capital (IC), green information systems (IS), green management initiatives (GMI) and green technology adoption in light of natural resource-orchestration theory (ROT). Moreover, digital technology adoption mediates between green IC, green IS, GMI and sustainable performance. Finally, digital transformation strategy is used as a moderator between green technology adoption and sustainable performance.Design/methodology/approachA sample of 484 managers from automobile manufacturing companies was used in this study to evaluate the proposed relationships using the Structural Equation Modeling (SEM) methodology.FindingsFindings reveal that green IC, green IS and GMI significantly influence green technology adoption. Besides, green technology adoption plays a crucial role in improving sustainable performance. Moreover, green technology adoption significantly mediates between green IC, green IS, GMI and sustainable performance. Finally, a digital transformation strategy significantly strengthens the relationship between green technology adoption and sustainable performance.Practical implicationsThe organizations need green technology adoption to address environmental concerns, respond to consumer demand, achieve cost savings and comply with government regulations. Besides, in decision-making, organizations must focus on green IC, green IS, GMI, green technology adoption and digital transformation strategy to boost sustainable performance.Originality/valueThe originality of this study lies in its use of the natural ROT as a framework to examine the impact of multiple green resources on green technology adoption, leading to sustainable performance. Digital transformation strategy is used as a moderator between green technology adoption and sustainable performance. This study provides a comprehensive and integrated perspective on the subject with empirical evidence and relevant insights, contributing to the advancement of the field.

An exact algorithm for unpaired pickup and delivery vehicle routing problem with multiple commodities and multiple visits

This paper addresses a new multi-commodity unpaired pickup and delivery vehicle routing problem in which each vehicle is allowed to visit each customer more than once for both pickup and delivery of each commodity. It is a complex variant of the classical capacitated vehicle routing problem and comes from resource transfer among different plants in a distributed manufacturing environment. Notably, the pairing decisions of pickup and delivery for each commodity and the routing decisions among customers are interdependent, and they need to be made simultaneously and collaboratively. Firstly, a mixed integer programming model is developed, and then new valid inequalities are derived to improve the linear programming relaxation. Afterwards, a branch-and-cut algorithm is proposed by exploring different branching strategies and tailored separation algorithms. Computational results based on real-case instances from an automobile manufacturing company demonstrate that the costs are considerably reduced by considering the multiple visits compared to the single visit of each customer. In addition, our proposed branch-and-cut algorithm outperforms a manual solution method adopted by the company in practice and two solution methods in the literature. Furthermore, two adaptations of our branch-and-cut algorithm also perform better than two state-of-the-art algorithms in solving two closely-related problems in terms of solution quality and computation time. Sensitivity analyses with respect to vehicle capacity, vehicle duration, and vehicle speed are conducted to derive several valuable managerial insights.

Flexible thickness control of hydroforming by forced lubrication method in arbitrary region and time

The elastic and plastic properties of metal can be used in various applications. Junior Associate Professor Hiroaki Kubota is working to improve manufacturing design through the application of elasto-plastic mechanics. He is particularly interested in hydroforming; a process in which steel tubes are inflated by water pressure. This can be used to produce hollow, lightweight automobile parts. Kubota previously worked in the body design and advanced development department of a car manufacturing company, learning of the importance of thickness distribution of vehicle components. It was this that inspired his current work. At the Department of Mechanical Engineering, School of Engineering, Tokai University, Japan, where Kubota is based, he is conducting research on hydroforming technology and applied research on the optimisation of plastic working using finite element analysis (FEM) and artificial intelligence (AI). Through their research on lubrication hydroforming, the team developed a forced lubrication technology that supplies high-pressure lubricant between a die and a tube during tube hydroforming, leading to even distribution and uniform wall thickness. The researchers want to expand the application of high-strength steel tubes to contribute to more lightweight and rigid cars. In their work the team confirmed that when a high-pressure lubricant was injected between the die and the steel tube, uniform wall thickness was achieved and cracking prevented. This was the very first time that forced lubrication was found to be effective in hydroforming. The team also discovered that by managing the forced lubrication, the thickness of parts can be freely controlled.

Comparative Assessment of the Prospects for Hydrogen Fuel Cell Electric Vehicles

Today, road transport is one of the main environmental pollutants. It accounts for more than half of all emissions. In this regard, the issue of developing measures to reduce the impact of cars on the environment is gaining relevance. There are various approaches to solve this issue, but the most promising direction is the use of electric vehicles. It should be noted that we cannot talk about their absolute environmental friendliness, since there is still an indirect impact on the environment.The paper examines the prospects for the use and disadvantages of two types of electric vehicles powered, respectively, by battery or hydrogen fuel cells. Currently, production of battery electric vehicles is a more popular direction, which is largely due to development of technologies in the field of battery production. At the same time, one should not completely exclude other areas, such as hydrogenfuelled vehicles. Such vehicles are distinguished by good environmental friendliness, which is determined by the nature of the combustion product and the possibility of obtaining this type of resource. However, the use of hydrogen as a fuel for internal combustion engines is not relevant. Development of a car with an electrochemical generator is more promising. Today, a fairly large number of the world’s leading car manufacturing companies are advancing in this direction.The electric vehicles considered in the work have similar emissions of harmful substances, which, under equal conditions, approach zero. However, both types of vehicles leave a carbon footprint, the bulk of which comes from electricity generation and hydrogen production. The study carried out a comparative assessment of the quality characteristics, carbon footprint and operating costs of electric vehicles with various types of power plants under Russian operating conditions. Based on the comparison, the main advantages, and disadvantages of those types of electric vehicles have been identified. Actions are proposed to increase the environmental friendliness of electric vehicles and solve problems that complicate their operation.

Study of inbound logistics supply chain of an automobile manufacturing company

Study of inbound logistics supply chain of an automobile manufacturing company

Smart Cars – Predicting Future Customers

This document gives Smart cars which are also known as autonomous cars or self-driving cars which moves with little or no human input. They are efficient and avoid accidents so many car manufacturing companies have started working on these autonomous cars and for this process they are investing huge money in R&D for best and efficient cars. But the main issue is as they are investing more money they are expecting to get huge profits, so we came up with a solution. In this paper we will set up a machine learning model which will predict the future sales or customers buying these car sand this will increase the income for the companies. So as to achieve this predictive model, we will make use of frame works and libraries of python.

Mitigating Disruption from Global Increment Price of Material in Car Manufacture Industry: Analysis of Supply Chain Business Process Analysis, and Process Re-Engineering

The existence of raw materials is crucial for Car Manufacturers and their suppliers in the production process. The Covid-19 pandemic has affected the global economy and led to a global increase in material prices. This has had a significant impact on production costs and the competitiveness of companies. In order to maintain competitiveness, companies need to implement the appropriate supply chain management strategies. This research utilizes the SCOR Framework and BPMN to evaluate and enhance the supply chain operations performance in Car Manufacturing companies. The purpose of this study is to evaluate the current supply chain performance and provide recommendations for the appropriate supply chain business processes in addressing the phenomenon of global material price increases. This research is conducted through qualitative and exploratory quantitative methods using the SCOR framework and BPMN. The research findings indicate that the supply chain performance is still lacking in the procurement area. Therefore, business process re-engineering needs to be conducted by transforming the current supplier-led raw material purchasing into self-purchase by the Car Manufacturer. The recommendation for the new business process is for the Car Manufacturer to directly purchase the raw materials for the supplier's needs, thereby eliminating the handling fee charged by the supplier.

A Study on Impact of Green Marketing Influences on Consumers' Decision to Purchase Electric Vehicles in the Automobile Industry, with Reference to Raipur City

The paper helps us identify the effect of green marketing practices of automobile manufacturing companies on consumers. It is important for the researcher to know how "Green" the consumers are in terms of their knowledge, their attitudes and behavior. This study finds how far advertising that promotes environmental friendliness influences people in Raipur to buy electric Vehicles. Electric vehicles are getting more attention because they're seen as better for the environment than regular vehicles that run on gas. Figuring out what makes people want to buy electric vehicles is important for getting more of them on the roads and dealing with environmental problems. The research adopts a quantitative research design and collects data through a structured questionnaire survey. The target population consists of residents in Raipurcity who are potential consumers of EVs. The study employees a convenience sampling technique to select participants, resulting in a sample size of 120. The research examines the relationship between green marketing strategies adopted by EV manufacturers and consumers intention to purchase EVs. It investigates various green marketing dimensions, such as eco-labelling, eco-packaging, and eco-branding, and their impact on consumer’s perceptions of EVs environmental benefits. The research looks at how the way electric car companies advertise their vehicles being good for the environment affects whether people want to buy them. It can also help companies that make and sell electric vehicles in Raipur. If they know what makes people want to buy electric vehicles, they can make plans to encourage more people to buy them. Companies can also use this information to make advertisements that focus on the good things about electric vehicles for the environment, which might make more people want to buy them.

Upward scalable vehicle routing problem of automobile inbound logistics with pickup flexibility

Motivated by the inbound logistics of a famous automobile manufacturing company, we introduce the upward scalable vehicle routing problem (for order pickup) with time windows (USVRPTW), where the pickup from each supplier can be adjusted upward by a certain degree (pickup flexibility) based on the order volume, thus increasing the vehicle utilization and reducing logistics cost. We solve the USVRPTW exactly by a branch-and-price algorithm, where the flexibility affects the pricing problem, leading to the elementary shortest path problem having to consider resource allocation except the resource constraints. The consideration of resource allocation adds many new properties to the shortest path problem, based on which we design a tree search algorithm. We develop a heuristic algorithm based on the bipartite graph to generate initial columns for the column generation (CG) process. The algorithm can also be adopted as an efficient method for solving large-scale problems due to its ability to find near-optimal solutions quickly. We also propose the penalty stabilization method and the drill-down strategy to accelerate CG. Numerical experiments show that our designed branch-and-price algorithm outperforms the commercial solver Gurobi. The efficiency of the tree search algorithm, the heuristic algorithm, and the CG acceleration methods is also verified. Real-data experiments illustrate that the low increase in driving cost can significantly improve vehicle utilization, proving the significance of flexibility. We then provide management insights to reveal that adopting the proposed flexibility mechanism can reduce logistics cost.

A novel resilient and sustainable supplier selection model based on D-AHP and DEMATEL methods

The natural disasters that cause a sudden violent change in the earth and the disruptions made by humans disrupt operations in the supply chain, causing negative influences such as lost productivity, revenue, competitive advantage, and profitability for the company. Therefore, suppliers need to be capable of being resilient to any disruption and providing sustainable supply. Supplier selection is a multi criteria decision making (MCDM) problem that allows suppliers to evaluate different and often conflicting qualitative and quantitative criteria. Both resilient and sustainable supplier selection problems contain many qualitative criteria. Experts make subjective judgments based on qualitative criteria in the decision-making process. The D number is a method used to find an efficient and feasible solution to uncertain information. In this paper, the DAHP method, which integrates the traditional Analytic Hierarchy Process (AHP) method and the D numbers, is used for the resilient and sustainable supplier selection problem. The Decision Making Trial and Evaluation Laboratory (DEMATEL) method is integrated into DAHP to determine criteria and subcriteria weights. The proposed integrated DAHP-DEMATEL model is implemented in an automobile manufacturing company to demonstrate the effectiveness of the method. The Triantaphyllou method is applied to perform sensitivity analysis. The traditional AHP-DEMATEL hybrid method was applied to the same problem, and sensitivity analysis was performed. The sensitivity analysis results of the hybrid method were compared with the results of the applied AHP-DEMATEL method. It can be said that the proposed model is less affected by subjective evaluations and is a robust method.

Reporting in large-scale agile organizations: insights and recommendations from a case study in software development

Application of agile software development methodologies in large-scale organizations is becoming increasingly common. However, working with multiple teams and on multiple products at the same time yields higher coordination and communication efforts compared to single-team settings for which agile methodologies have been designed originally. With the introduction of agile methodologies at scale also comes the need to be able to report progress and performance not only of individual teams but also on higher aggregation of products and portfolios. Due to faster iterations, production of intermediate work results, increased autonomy of teams, and other novel characteristics, agile methodologies are challenging existing reporting approaches in large organizations. Based on 23 interviews with 17 practitioners from a large German car manufacturing company, this case study investigates challenges with reporting in large-scale agile settings. Further, based on insights from the case study, recommendations are derived. We find that combining reporting and agile methodologies in large-scale settings is indeed challenging in practice. Our research contributes to the understanding of these challenges, and points out opportunities for future research to improve reporting in large-scale agile organizations by goal-setting and automation.

Use of digital twins in automotive industry: Russian and foreign experience

Aim. To determine the breadth of application of digital twins in the automotive industry in Russia and abroad, and to compare the level of implementation of innovative technology in production.Tasks. To consider the general issues of digitalization of the automotive industry and the tools by which it is carried out, including such a tool as a digital twin; to characterize the problem issues that need to be solved in the production of cars with digital twins; based on the analysis of examples of digital twins in the automotive industry in Russia and foreign countries to show the level of technology development and advantages of its use.Methods. The objectives were solved by using empirical research methods, in particular based on the study of various sources of information, including the scientific works of researchers, as well as the analysis of the data obtained with subsequent conclusions.Results. Along with many other effective tools of digitalization, the digital twin helps enterprises from the automotive industry to reach a new technological level of development, optimizing production processes and increasing the competitiveness of manufactured products and companies. There are several facets of digital twin technology that enable critical tasks at every stage of vehicle design, production and testing, while reducing time and material costs. The technology is gradually beginning to be used in leading car manufacturing companies, both in Russia and abroad. Especially effective is the use of digital twins in the production of electric cars.Conclusions. Digital twins serve as an effective tool for the digitalization of the automotive industry, allowing to reduce costs and time spent on product development and production, as well as on various vehicle tests. In addition, due to the use of technology, manufacturers have the opportunity to identify new ways to improve products, expand the model range, and improve safety and comfort for customers. Due to these advantages, the technology is actively being introduced in the production of foreign and domestic cars. However, in the absence of all necessary resources in Russia, the production of cars using digital twins is not as active as in other countries.

Implementation of Web-based E-learning System in Automobile Industry Using Agile Model

Training is one of the most important human resource development activities in growing industries, especially the manufacturing industry. Preparing learning materials and tracking trainees' performance during a training session are the challenges faced by a local automobile manufacturing company. This project aims to develop a web-based E-learning management system for training purposes at a local automobile company. This online system will complement the traditional method for trainers in preparing learning materials and tracking trainees’ performance. In addition, this system supports in-class activities for trainees to learn and understand, explore, and exchange ideas outside the classroom, while trainers can manage and upload course materials. In order to evaluate the user acceptance towards the system, several tests were conducted. It is envisaged that the proposed system will provide a more convenient way for a local automobile company to train their trainees.

THE RELATIONSHIP BETWEEN PRODUCT ARCHITECTURE AND INNOVATION: A STUDY THROUGH DESIGN OF MOTORCYCLES

AbstractHow does the quantity and quality of innovation in an organization vary with the architecture of the product that the organization produces is a recurring theme in literature. This paper attempts to answer this question in quantitative terms and establishes an empirical relationship. While establishing this relationship, this paper also finds objective and quantitative expressions both for the product architecture and innovation in such a way that both the qualitative and quantitative aspects of innovation are accounted for. In this process three new formulations, which can be calculated using the data available in public domain, have been established for architectural modularity, architectural complexity and innovativeness of an idea respectively.These formulations have been verified by collecting innovation data in an automobile manufacturing company and analyzing it from the perspective of architecture and innovation. Finally, the relatioships between architectural parameters and innovativeness have been explored. Implications include the type of architecture more amenable to innovation, the impact of innovation on architectural complexity and a methodological contribution to operationalizing innovation.

Analysis of Financial Strategy and Operation Strategy of BYD, Changan Automobile, and Great Wall Motor

With the increasing emphasis on environmental protection energy in global development, new energy vehicles have attracted the attention of automobile manufacturers. At present, the market has a great development prospect and there is no obvious oligopoly. Therefore, taking China's domestic automobile market as the target, this paper selects three representative automobile enterprises with different development priorities to conduct financial analysis, industry analysis, and SWOT analysis on the three companies. Based on the data of these three companies, the overall domestic automobile market in China is roughly evaluated, and the future development of China's new energy automobile market is speculated. This study found that the influence of new energy automobile enterprises in the automobile manufacturing industry has gradually increased, but it still cannot affect the position of traditional automobile manufacturing companies. At present, there is no oligopoly in China's domestic new energy market. Even BYD, which already has the first-mover advantage, does not fully grasp the majority of the domestic market, and it is still possible to be surpassed by later companies (such as Changan Automobile and Great Wall Automobile).

A hybrid approach to enhancing the performance of manufacturing organizations by optimal sequencing of value stream mapping tools

PurposeLean manufacturing (LM) is prevalent in the manufacturing industry; thus, focusing on fast and accurate lean tool implementation is the new paradigm in manufacturing. Value stream mapping (VSM) is one of the many LM tools. It is understood that combining LM implementation with VSM tools can generate better outcomes. This paper aims to develop an expert system for optimal sequencing of VSM tools for lean implementation.Design/methodology/approachA proposed artificial neural network (ANN) model is based on the analytic network process (ANP) devised for this study. It will facilitate the selection of VSM tools in an optimal sequence.FindingsConsidering different types of wastes and their level of occurrence, organizations need a set of specific tools that will be effective in the elimination of these wastes. The developed ANP model computes a level of interrelation between wastes and VSM tools. The ANN is designed and trained by data obtained from numerous case studies, so it can predict the accurate sequence of VSM tools for any new case data set.Originality/valueThe design and use of the ANN model provide an integrated result of both empirical and practical cases, which is more accurate because all viable aspects are then considered. The proposed modeling approach is validated through implementation in an automobile manufacturing company. It has resulted in benefits, namely, reduction in bias, time required, effort required and complexity of the decision process. More importantly, according to all performance criteria and subcriteria, the main goal of this research was satisfied by increasing the accuracy of selecting the appropriate VSM tools and their optimal sequence for lean implementation.

Business Analysis of Toyota Based on Enterprise Value Multiple and PEST Analysis

Toyota is a long-established automobile manufacturing company with both a broad market and abundant economic activities. This paper conducts a business analysis of the Toyota company by analyzing the accounting statements and financial data of Toyota company for sales, profitability, and stock value. Overall, Toyota has an advantageous position in terms of sales compared to other competitor companies and also in terms of profitability by analyzing the marginal net profit, it is concluded that Toyota's profitability is in the middle to upper level compared to other competitors. In the stock value analysis, by comparing the enterprise value multiple and the price-to-earnings ratio analysis, it is concluded that Toyota has the highest price-to-earnings ratio compared to other competitors, thus concluding that Toyota has a high stock return and a rich investment value. This research paper provides relevant business analysis for major companies in the automotive manufacturing industry for the last two years, reflecting the business conditions of different companies and the future prospects of Toyota.

Development of test methods for electromechanical sensors of vehicles used for operation in regions with a hot climate

Currently, there are various methods of testing vehicles and its components used by different car manufacturing companies. Also, these methods are given in the UNECE regulatory documents in the field of transport, but these documents do not take into account the separate operating conditions of cars in different regions. In this regard, the paper presents the road and climatic conditions of Central Asia characterized by peculiar characteristics. Based on the climatic features of the operation in a hot region, technical requirements have been developed for electromechanical sensors of cars for operation in hot climatic conditions, which should ensure the reliability of these components when the car runs at least 250,000 km. The method of testing electromechanical sensors of cars has been presented. It is established that in order to ensure the normal operability of sensors operating in hot climates, it is necessary to conduct tests at a nominal ambient temperature 45 ± 5 °C. The test procedure is built based on this parameter. All developed test methods are consistent with current standards in the field of electromagnetic, electromechanical and other electrical parameters of the automotive industry. Schematic diagrams of stands for testing have been given. The paper reflects the methodology of accelerated reliability tests, in which the temperature is set as the accelerating factor. The tests fully reflect the operational characteristics of the movement of cars in a sharply continental climate with a hot slope of ambient temperature with sharp temperature changes. After each test, it is determined that the nominal parameters of the sensors are checked for compliance with the established requirements. Conclusions reflecting the results of the work carried out have been made.

The differential impacts of top management support and transformational supervisory leadership on employees’ digital performance

ABSTRACT How do leaders across different hierarchies motivate employees’ job performance in the new digital age? In order to answer this under-investigated question, we first conceptualise digital performance as employees’ job performance that is attained through using the new generation of digital technologies and then propose a research model that integrates and differentiates the influential mechanisms of the dual leadership factors – top management support and transformational supervisory leadership – regarding employees’ digital-enabled task performance and innovative performance. Specifically, we tested the research model with two different samples, including 230 sales personnel from a large automobile manufacturing company and 206 employees from multiple joint ventures across different industries. We find that top management support exhibits a stronger influence on digital-enabled task performance than on innovative performance through the mediation of data-driven culture, while transformational supervisory leadership nurtures a stronger effect on digital-enabled innovative performance than on task performance through the mediation of digital self-efficacy. Our study consolidates and extends the technology use literature on management support and advances IS leadership theory to the digital context. Our findings also offer practical insights into the effective use of the new generation of digital technologies in organisations.