Tesla's Manufacturing Process: A Comprehensive Analysis Assignment Sample

Tesla's Manufacturing Process: A Comprehensive Analysis

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Introduction - Tesla's Application of Information Technology in the Automotive Industry

1.0 Introduction-

In this decade information technology has increasingly translucent the financial sector of Tesla company. It is a golden opportunity for the company to implement its technology with Information Technology to grow fast in the car retail industry. In this case study, there are many key points to describe widely like types of software, social and ethical issues of using the technology, network technology, importance of artificial intelligence, and software development of Tesla while using the information technology in the manufacturing process in the automobile industry.

2.0 Literature Review

2.1Different types of Software in general

According to Sheela et al. (2020), a permanent magnet synchronous motor is one of the best methods in the automobiles industries. Magnetic software is useful to analyze and detect the power of the motor. It is eco-friendly and works with 3 kW and 48 V power to operate EV applications. A new stage prototype is designed using the software of MAGNET with the simulator of MATLAB SIMULINK. By using this software, finite element analysis was performed. This is one of the best techniques to use in the automobile industry to protect the environment.

 

2.2 Ethics and Social Issues of using technology in general

According to Vincent, (2018), researchers critically analyzed various controlling factors related to the Tesla automobiles. In this research paper, researchers proposed several ethical implications related to the Tesla automobiles on the basis of the market, choices, and transport-related aspects. On the basis of the research paper, researchers stated several facts related to Tesla such as marketing materials and hardware related to the Tesla. There are also several implications related to the social structure that were very significant aspects here. On the basis of social implication, various aspects such as public safety, artificial intelligence, and financial factors on the basis of automobiles are very significant factors. In the context of the social implications, several car accidents, cases related to drunk driving, and aspects related to not seeing traffic signals were also managed by the Tesla car. System-related artificial intelligence plays a significant role in the aspects related to the social implications. To construct this research paper, there was also an analysis on the basis of the literary resources. In this context, some factors related to the DSR, and analytical assessment on the basis of Tenet 1.05, SECOE, Tenet 6.07, 6.12, 6.08, and many more were very significant here.

2.3 Networking Technology, different types in general

According to Chen, et al. (2019), this research paper observed several aspects related to the autonomous mobile on the basis of the decision-making process and observance. Researchers stated some factors to develop the detection-related aspects to improve the accuracy of the autonomous car and also enhance the safety measures. In this context, researchers have stated the comparison between autonomous cars and self-driven cars. Researchers introduced some fundamental problems such as the types and amount of information we need to share with this car. There were several aspects like clouds based on LIDAR, several operative systems, SPOD, and infrastructure related to the SPOD also very significant here to construct this research paper. Researchers incorporated SPOD with LiDAR and observed some undetected objectives related to this aspect.

2.4 The Artificial Intelligence and its importance in general

According to Khan, et al. 2022, researchers considered a solution on the basis of several challenges through learning and adaptation processes. In this research paper, several aspects based on met-learning, and cognitive loops are very significant. They considered some implementations related to the cognitive loop regarding mechanisms on the basis of each segment of the learning and adaption process. In this context, the control loops must be implemented by artificial intelligence and several factors. In this literary source, they referred to some technologies related to the building blocks to get design goals regarding communication, AI, and computation.

2.5 Software Development Life Cycle

The study conducted by Singh et al. (2021) demonstrates that the fabrication of metal matrices based on the casting method is one of the most efficient techniques used in the automobile sector. This technique is based on auto components. It provides high strength, high failure life, and high resistance rate. It can replace part of steel in the manufacturing process.

3.0 Analysis and Discussion

3.1 Software and its types used in the manufacturing

Elon Musk is the world’s most famous person for his technical knowledge of science which has revealed his idea. The manufacturing of Tesla has focused on Musk’s vision. The main motive of Tesla is to innovate the electric vehicle and clean energy company. The electric cars of Tesla are the Model X, Model Y, Model 3, and Model S. In the process of manufacturing Elon Musk has discussed what type of product will be manufactured and is accordingly important to proceed with the manufacturing process (Tenhundfeld, et al., 2019). In his first vision Musk has applied the concept of “Alien Dreadnought” to innovate and manufacture the product.it is the automated setting of the factory but this concept has failed in the practice while the Model S production is ongoing lastly the production will be assisted by the human to clean up the mess. Recently Tesla has succeeded in their business by revitalizing the method that they used “Alien Dreadnought”. The software version of Tesla is “0.5 of the Alien Dreadnought” (Le, 2021). A common strategy of Tesla is basically used for the manufacturing purpose of “Integrated ERP software” to achieve the target growth of the company. This software tracks their daily mechanical activities check the product quality and looks after some additional features of the company’s manufacturing process.

3.2 Ethics and social issues in the manufacturing process

In the manufacturing process of Tesla, it has faced many problems socially. Many fraud allegations are faced by the company socially like misuse of tax money, the environmental practice of Tesla, safety issues, customer service issues, the environment of workplace issues, condition issues of the working employees, and the company has failed to accept the agreement of license. The SolarCity group has filed a lawsuit alleging against the stakeholders of Tesla and the shareholders have claimed that Musk was aware of the insolvency prior that the SolarCity have which is the main time to buy out. The critics have claimed that Tesla has fake safety for the autopilot driver assistance system. The safety of the autopilot vehicles of Tesla is not secure (Holstein,et al., 2018). The National Transportation has penalized Tesla for they have failed to secure the safety of the driver. Tesla has been fired from the factory of Giga New York for filtering out the tax of nearly one Billion Dollars in the taxpayer money which overruns the cost, delayed the construction of the company, and inflated job promises with a lack of effort. The owner of the vehicle has filed a complaint about the time of repair of a “nightmarish” has taken up to 6 months for it due to lack of the services center the parts are not found anywhere. The working employee of Tesla has discussed their dissatisfaction with the company’s treatment of them publically. Because the ambulance has visited many times due to the health issues of workers like dizziness, abnormal breathing, chest pains, and many more so Tesla has employed more than ten thousand employees at the end of that time. Tesla also faced workplace harassment like racial discrimination.

3.3 Types of Networking Technologies that used in the manufacturing process

Tesla uses advanced technology to develop their manufacturing in the networking business. They use innovative ideas to increase their uniqueness in the manufacturing sector. They have used advanced technology to produce multiple products like vehicles, solar roofs, and some other essential gadgets. They have changed the way of thinking in the automobile sector. They hire skilled technologists who are efficient in their work. The products manufactured by Tesla have high demand because they have assured the customers to provide safety. They update their products with new features. Adding new features help to grab the new customers including the existing customers. They can produce the same energy using smaller cells. The cars produced by Tesla are in a variety of ranges (Habib, et al., 2020). Using advanced technology helps the company to reduce the cost of production. Although they have pay a huge amount to hire skilled developers. They face many adverse situations while handling the issues related to networking technology but they use advanced skills to overcome the problems. They use AI technology to identify any defects in their products. They have trial sessions for each product. These trial sessions are required before launching any kind of product on the market. They use a transformer to detect any objects. This helps to prevent the number of accidents. Advanced languages are used to make the networking ber. Now they are going to launch some cars which have the ability of self-driving. But the process of making those cars involves proper utilization of software. The sensors are also designed to provide some additional facilities to the consumers. Tesla has the proper knowledge about the demand and the problems faced by the consumers using manufacturing products from them. But they take the feedback from the consumers and try to fulfill their expectations. They have innovated some neutral networks which have the ability to exclude the features from the videos. This technology helps to understand the surroundings through cameras. There are some other features developed by Tesla using networking. The cars can easily get to know about the routes. These technologies work like a human brain.

3.4 The importance of Artificial Intelligence in the manufacturing process

There are many networking technologies that have been included in the manufacturing process of the Tesla Autopilot vehicles. They have implemented artificial technology to plan, support, use the inference hardware, and achieve the general solution of self-driving. The company has built an Artificial Intelligence chip to run its Full Self-Driving (FSD) software. They also invented the Dojo chips to supply the power to the system to build the AI training. Tesla has designed the Dojo system with the firmware of silicon which has interfaces with the high-level software to control it. Tesla has applied edge-cutting exploration to prepare the neutral networks deeply on the problems from the attention to get control of the programming (Cooke, 2020). To build the autopilot neutral networks Tesla has involved around forty-eight networks and seventy thousand GPU hours to prepare it. The company has developed its core of algorithms which have driven the car and represent it with a high devotion to planning the trajectories for the world in that space. The company has built its autopilot software from the lowest level of the stack which has integrated tightly with its custom hardware and implemented the super reliable boot loaders which are supported by the over-the-air updates. Tesla has built an open loop, a closing loop, and hardware in the loop to accelerate the pace that has innovated to track the performance to prevent the regression.

4.0 Conclusions

Tesla is an automobile industry and there is no doubt which is invented by Elon Musk. the company’s main motive is to invent the autopilot car which is automatically drive when the driver does not want to drive by implementing the information technology in the automobile sector. On the basis of the research paper, researchers stated several facts related to Tesla such as marketing materials and hardware related to the Tesla. Tesla has faced many issues in their manufacturing periods so now Elon Musk has changed that technology by the AI technology. They use AI technology to identify any defects in their products. They have trial sessions for each product. These trial sessions are required before launching any kind of product on the market. The company has built its autopilot software from the lowest level of the stack which has integrated tightly with its custom hardware and implemented the super reliable boot loaders which are supported by the over-the-air updates.

Reference list

Journals

Chen, Q., Tang, S., Yang, Q. and Fu, S., 2019, July. Cooper: Cooperative perception for connected

Cooke, P., 2020. Gigafactory logistics in space and time: Tesla’s fourth gigafactory and its rivals. Sustainability, 12(5), p.2044.

Distributed Computing Systems (ICDCS) (pp. 514-524). IEEE.Sestino, A., Peluso, A.M., Amatulli, C. and

engineering industry: the case study of Tesla, inc. Serbian Journal of Management, 14(2), pp.361-371.

Gayathri, S. and Kumari, D.A., Electric Vehicles-An Introduction of the Tesla for Strategy and

Gong, Z., Li, X. and Shi, X., 2022, April. Dynamic Changes in Exchange Rate Movements and Tesla

Guido, G., 2022. Let me drive you! The effect of change seeking and behavioral control in the Artificial

Habib, T., Kristiansen, J.N., Rana, M.B. and Ritala, P., 2020. Revisiting the role of modular innovation in technological radicalness and architectural change of products: The case of Tesla X and Roomba. Technovation, 98, p.102163.

Holstein, T., Dodig-Crnkovic, G. and Pelliccione, P., 2018. Ethical and social aspects of self-driving cars. arXiv preprint arXiv:1802.04103.

Intelligence-based self-driving cars. Technology in Society, p.102017.

Jen?ová, S., Vasanicova, P. and Litavcová, E., 2019. Financial indicators of the company from electrical

Khan, M.A., Sayed, H.E., Malik, S., Zia, T., Khan, J., Alkaabi, N. and Ignatious, H., 2022. Level-5

Le, L. and Ho, Q., 2021. Factors affecting the valuation of electric vehicle company in 2020: case Tesla Inc.

Leadership. International Journal of Recent Technology and Engineering, 8.

Sheela, A., Suresh, M., Shankar, V.G., Panchal, H., Priya, V., Atshaya, M., Sadasivuni, K.K. and Dharaskar, S., 2020. FEA based analysis and design of PMSM for electric vehicle applications using magnet software. International Journal of Ambient Energy, pp.1-6.

Singh, H., Brar, G.S., Kumar, H. and Aggarwal, V., 2021. A review on metal matrix composite for automobile applications. Materials Today: Proceedings, 43, pp.320-325.

Smerichevskyi, S., Kryvoviaziuk, I. and Raicheva, L., 2018. Economic consequences of financial stability

Stock Yields. In 2022 7th International Conference on Social Sciences and Economic Development

study. Sustainability, 13(9), p.4872.

Tenhundfeld, N.L., De Visser, E.J., Haring, K.S., Ries, A.J., Finomore, V.S. and Tossell, C.C., 2019. Calibrating trust in automation through familiarity with the autoparking feature of a Tesla Model X. Journal of cognitive engineering and decision making, 13(4), pp.279-294.

Vincent, K., 2018. Ethical Implications: The ACM/IEEE-CS Software Engineering Code applied to Tesla's" violation of world automotive corporations. Baltic Journal of Economic Studies, 4(2), pp.229-234.

Wong, E.Y.C., Ho, D.C.K., So, S., Tsang, C.W. and Chan, E.M.H., 2021. Life cycle assessment of electric