Provides tools for data-based diagnosis and elimination of faults in on-board vehicle computers. Furthermore, the intricacy of the vehicle calls for recruiting personnel with more advanced technical knowledge, typically paid more. Demand for these experts surpasses the availability of workers. The lesser number of young technicians replacing senior competent
experts older age aggravates this issue since it calls for greater salaries to draw in these replacements.Autonomous cars are still vehicles, each component of which, mechanical or electric, has a limited life cycle notwithstanding technical developments. Consequently, an autonomous car's mileage determines its more or less wear and tear. Technical issues
increase in risk with increasing degree of difficulty. There is a major mistake risk until the fleet of autonomous cars grows adequate to gather comprehensive statistical data on all types of failures. ,This might lead to unstable car systems as well as a great demand for competent vehicle service experts. Real-time operating condition monitoring as well as decision-making
On driving operating and maintenance depending
on expected conditions are part of Vehicle Health Management (VHM). The paper (Jaw L. and Wang W. 2004) offers a universal, flexible integration and testing concept for checking / evaluating control, together with workability management capabilities, which provide the required environment for evaluating effectiveness, including the accuracy of decision-making,
algorithms and models for managing workability status in real time and in closed cycle. Since it influences repair and maintenance times, identifying flaws in automobile systems is absolutely important. One often used technique is a fault tree diagram. However, considering the structure of the implicit system, the authors of (James A.T., Gandhi O.P. & Deshmukh S.G.
2018) suggested a method with explicitly included built-in structure by means of digraph modeling, which employs the system approach of graph theory. The suggested method includes guidelines for determining the malfunction fundamental causes. The created digraph technology produced a fault tree fit for computer operation. Consequently, this approach can
Be automated to identify car problems
The approach coter will assist in building a knowledge base regarding failures, their causes, and their fixes. For M & R engineers, then, this method is very helpful. Modern vehicles today provide a challenging task since different causes of breakdowns produce similar symptoms in very sophisticated vehicles. Based on failure's maintenance manuals to manufacturer
standard and personnel expertise, current fault diagnosis systems are often insufficient and result in tremendous effort and incorrect remedies. Thus, the article (Meckel S. et al., 2019) presents techniques for extracting knowledge from unstructured and informal materials on online forums with the aim of synthesizing diagnostic graphs from the created knowledge
base, which are software part for use in vehicle maintenance offering more efficient and targeted diagnostics actions and real-time service. Using cars annual monitoring under several operating situations, the paper (Borucka A. 2019) shows a wear analysis of brake system components. The aim was to investigate the relevance of the chosen elements
Influence on the brake wear degree as well as
to offer potential approaches applicable in this field. This will not only offer a better safety degree but also more effective task planning and the required inclusion of the related charges in the corporate budget. An suitable schedule for vehicle maintenance is necessary to guarantee always high service quality, operability and safe operation of the transportation system. As stated in (Kamlu S. & Laxmi V. 2019), maintenance which depending on
condition identifies the vehicle. According to the 2018 Sharma S. study, mother satisfaction is high; quality has improved and prices have been lowered. Based on operational reliability data knowledge, the article (Vintr S. Z. and Holub R. 2003) addresses the optimizing the maintenance concept technique, which enables to lower the vehicle life cycle costs (LCC). The key interactions between LCC of the main vehicle subsystems and the frequency of their
scheduled (preventive) repairs are theoretically optimized by the authors under a model. The authors show that, with a straightforward measure of administrative change in maintenance periodous medium-speed engines, it is rather easy to locate reserves in the vehicle maintenance concept and generate considerable savings in the vehicle LCC using the presented model. Furthermore covered in this work are an analytical research of engine
Conclution
lubrication system operating a study of the engine oil pressure effect on friction losses, and torque investigation at several oil pressure levels. Reliable source for identifying and fixing a lubricating system in a standard passenger vehicle was diagnostic data gathered from many engines. Before failure occurs, condition using either wired or wireless data forecasts and implements suitable maintenance measures, such repairs and replacements. This work
presents a condition-based maintenance (CBM) method proposed to construct a fuzzy model for individual cars by considering several uncertainties including load, mileage, and topography. Thanks to their Markovian structure, hidden markov models (HMM) can include all accessible prior knowledge in a Bayesian formulation and offer the construction of computationally intensive signal processing algorithms Reducing the cost of engines
maintenance and overhaul, which are the most expensive vehicle systems helps the diesel engines M and R system mostly aim to improve the operation efficiency. The paper investigates the trends of the oil volume influence in the diesel crankcase on the intensity of changes in the engine technical state and the oil ageing throughout operation. mprocessorize
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