Addressing the issue of the human factor in producing and developing cars is crucial. Since the quality of a vehicle defines the safety of its owner, it is essential to ensure the absence of errors during the development and production processes. For this purpose, an in-depth overview and analysis of the issues that enhance the impact of the human factor in designing and producing cars need to be researched. The goal of the study is to define the extent to which the human factor in production and development affects the number of car accidents, as well as explore the range of issues that contribute to the enhancement of the human factor. The results of the research can be used to improve car safety and reduce the number of road accidents.
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Introduction and Problem Statement
Working in the automotive industry implies dealing with a range of challenges, the possibility of an error due to the human factor being one of them (Wagner et al. 1001). As a mode of transportation, cars require rather impressive skills because of the speed that they can develop and the dire consequences of failing to manage the driving process (Noroozi et al. 135). Therefore, it is imperative to reduce the threat to a minimum, which requires preventing mistakes at the production stage. Thus, the human factor in car development and production must be studied thoroughly.
However, when considering the effects that human factors produce in the context of the automotive industry, one must also keep in mind that some of the conventional ideas about human factors and road accidents will have to be challenged (Albzeirat et al. 2). For example, instead of the traditional question of who is to blame for a car crash or a similar catastrophe caused by a human factor at the production stage, one will have to scrutinize the factors that lead to human error (Dhillon 2). As a result, a more productive study of the problem and the identification of its solution can be a possibility.
Therefore, the lack of understanding of how the phenomenon of the human factor must be treated can be seen as the primary problem. Defining the human factor and the extent to which it affects the propensity toward car accidents will have to be used as a tool for improving the situation as opposed to reinforcing punishment and blaming. The identified approach is expected to lead to a vast drop in the number of accidents, as well as a steep rise in the security levels.
In order to explore the subject matter, it was decided to carry out a mixed-research-based analysis of the issue. Particularly, the identification of key human factors that can affect the process of car production and development was viewed as a necessity. The specified stage needs to be qualitative in its nature since the phenomenon of the human factor and the way in which it manifests in the automotive industry will have to be explored. Furthermore, the connection between the human factor and the number of errors made in the context of the car industry, particularly at the stage of their design and production, will have to be calculated. The specified step will require a t-test analysis to determine the presence of a tangible impact of the human factor on the quality of cars and, thus, the possibility of a road accident.
The procedure will require gathering information from car-producing companies for the location of the human factors that may possibly lead to the introduction of inherent flaws into the design of cars and, thus, increase the threat of a road accident. The types of human factors that can affect the quality of the end product and entail a car crash will be identified. Furthermore, statistical data necessary for a quantitative assessment of the impact that the specified factors have on the rise in the number of road accidents will have to be collected. The specified information will be obtained from the databases created by the United States Department of Transportation. After classifying car crashes according to the factor that caused them and locating the number of ones that were induced by faulty mechanisms, one will be able to correlate the specified occurrences with the human factors that may have caused the identified occurrences at the production stage.
The procedure will be carried out with the help of the Student’s t-test. Thus, the opportunities for locating the connection between the specified variables will become a possibility. The number of car crashes will be viewed as a dependent variable in the specified scenario, whereas the human factor that may have possibly induced it will be regarded as an independent one (Ivanova et al. 1176). A study of the connection between the identified variables will allow determining the impact that a vast range of human factors have on the probability of a car accident after a vehicle is produced.
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As a result, the extent to which various human factors affect the possibility of an accident will be identified. However, when considering the significance of the study, one must mention that the vast array of human factors that will be discovered in the process can be viewed as the most important contribution to the study of the subject matter. An overview of the existing studies shows that there is no clear taxonomy of human factors, especially pertaining to the realm of the automotive industry (Sobhani et al. 132). Therefore, an in-depth analysis of the situation is required.
It is expected that the analysis aimed at detecting a positive correlation between the human factor and the propensity toward car accidents will deliver positive outcomes. Furthermore, the overview of the human factors that can be located in the environment of car production is believed to lead to discovering a vast number of issues that affect the efficacy of the production process. Particularly, the identification of a wide range of factors that contribute to a drop in the overall quality of production can be viewed as the most important outcome.
To be more specific, it is believed that internal and external influences will be identified when exploring the phenomenon of the human factor. The external ones will be linked to the workplace environment and the challenges that staff members face in it, whereas the external ones will be connected directly to the outside influences that have a direct impact on the well-being of staff members and the overall productivity thereof. The identified analysis includes an assessment of the factors that may contribute to stress among car industry employees, as well as the issues that may lead to the development of a careless attitude toward the process of manufacturing and testing the quality of products. It could be assumed that overly high reliance on technology and the following lack of personal supervision of the processes involving car manufacturing, location of defects, evaluation of test results, etc., serve as the foundation for the enhancement of the human factor effect (Aoyama et al. 1084).
In addition, there are reasons to believe that the analysis will point to the necessity of focusing on innovative solutions in manufacturing, production, and quality management. The identification of the crucial effects on the staff’s performance that determine the enhancement of the human factor is bound to produce the results that can be used to improve the quality of cars in the future. Moreover, the outcomes of the analysis are believed to contribute to a better understanding of how the human factor affects the quality of the product and the chance of malfunctioning that may lead to a further road accident. The results of the study, therefore, can be used to enhance safety levels for users by affecting the quality of car manufacturing and design processes. By locating the elements of the environment that lead to a rise in the number of human errors, one will be able to increase safety rates significantly by reducing the number of defective products. Thus, it is believed that the study may serve as the platform for introducing a series of improvements into the car manufacturing industry and a steep rise in the levels of safety among customers. Therefore, the research should be regarded as an important step in developing a proper understanding of how the human factor defines the overall quality of the end product, as well as how the specified factor can be controlled to enhance the safety of buyers and reduce the threats of road accidents.
Addressing the issue of quality is linked directly to exploring the effects that the human factor has on staff’s performance rates. The specified task is especially important in the automotive industry, where the quality of cars determined the levels of safety for buyers. Therefore, determining the effects that the human factor has on the number of defective items produced and, thus, the rise in the levels of car accidents will allow enhancing the safety of customers exponentially.
Albzeirat, Malek Khalaf, et al. “A Novel Mathematical Logic for Improvement Using Lean Manufacturing Practices.” Journal of Advanced Manufacturing Systems, vol. 1, no. 1, 2015, pp. 1-12.
Aoyama, Tomomi, et al. “How Management Goes Wrong?–The Human Factor Lessons Learned from a Cyber Incident Handling Exercise.” Procedia Manufacturing, vol. 3, 2015, pp. 1082-1087.
Dhillon, Bhavad N. Human Reliability, Error, and Human Factors in Power Generation. Springer, 2014.
Ivanova, Alena, et al. “Manufacturing Capability of the Robotic Complex Machining Edge Details.” International Journal of Engineering and Technology, vol. 7, no. 5, 2015, pp. 1774-1780.
Noroozi, Alireza, et al. “Determination of Human Error Probabilities in Maintenance Procedures of a Pump.” Process Safety and Environmental Protection, vol. 92, no. 2, 2014, pp. 131-141.
Sobhani, Ahmad, et al. “An Innovative Modeling Method to Evaluate Human Factor Effects on the Performance of Manufacturing Systems.” 2015 IEEE International Conference on IEEE, edited by Fabio Pini, Industrial Engineering and Engineering Management (IEEM), 2015, pp. 130-134.
Wagner, Regina, et al. “Exploration of the Product Phase-Out Process in Manufacturing Firms: A Human Factor Perspective.” Business Process Management Journal, vol. 23, no. 5, 2017, pp. 1000-1017.