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Maintenance of Electric and Hybrid Vehicles
Megjelent december 10, 2020

An electric car is a vehicle powered by one or more electric engines, utilizing energy stored within batteries that are rechargeable. The first register of a usable electrical vehicle dates from 1880s. A hybrid vehicle incorporates two or more different power types, including, e.g., gasoline engines and electric motor. The goal in this work is present the overall overview of the structure of the electric, hybrid and electric-hybrid vehicles, advantages and disadvantages of these types, the main points to focus when maintaining these and the challenges involved in its production and maintenance.

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Defect analysis of bearings with vibration monitoring and optical methods
Megjelent február 13, 2018

Diagnosis of bearings with advanced methods gained remarkable roles in the previous years. This article focuses on the manufacturing defects and methods to reveal and classify them. During manufacturing several faults could emerge because of the grinding operation, tool wear and chatter vibration. Inproper handling of the bearing parts because ...of the collosion to each other and the storing box that causes deformation. To reveal these problems several methods are applied in industry. For deeper surface analysis nitric acid can be used to initate the finished surface of the roller then natrium-carbonate that nautralize the elements. Vibration analysis in its standard Fourier form is not a new achivement but other mathematical tools could be applied to condition monitoring such as wavelet transform. It is an efficient tool for analyzing the vibration signal of the bearings because it can detect the sudden changes and transient impulses in the signal caused by faults on the bearing elements. In this article five different wavelets, Daubechies, Gaussian, Coiflet, Mexican hat, Meyer are compared according to the Energy to Shannon Entropy ratio criteria to reveal their efficiency for fault detection.

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LSI with Support Vector Machine for Text Categorization – a practical example with Python
Megjelent november 19, 2021

Artificial intelligence is becoming a powerful tool of modernity science, there is even a science consensus about how our society is turning to a data-driven society. Machine learning is a branch of Artificial intelligence that has the ability to learn from data and understand its behavers. Python programmin...g language aiming the challenges of this new era is becoming one of the most popular languages for general programming and scientific computing. Keeping all this new era circumstances in mind, this article has as a goal to show one example of how to use one supervised machine learning method, Support Vector Machine, and to predict movie’s genre according to its description using the programming language of the moment, python. Firstly, Omdb official API was used to gather data about movies, then tuned Support Vector Machine model for Latent semantic indexing capable of predicting movies genres according to its plot was coded. The performance of the model occurred to be satisfactory considering the small dataset used and the occurrence of movies with hybrid genres. Testing the model with larger dataset and using multi-label classification models were purposed to improve the model.

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Optimization and Analysis of Structure about Lifting Device of Logistics Sorting
Megjelent december 12, 2019

The lifting device of a logistics sorting machine needs high frequency upward and downward reciprocating motion therefore the cutting fork arms and matching parts of the shaft are often worn out. In this paper the problem of the shear fork types applied for the lifting mechanism is studied at first. Then the advanced numerical simulation ANSYS adopted for the lifting mechanism of the shear fork type, and the means of virtual simulation is introduced. Hence the possible location of faults and fault modes are analysed. Then improving measures about the lifting mechanism of the logistics sorting machine are suggested.

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A KKV-k helyzetének vizsgálata az Európai Unióban és hazánkban minőségbiztosítási szempontból
Megjelent április 8, 2022


Hazánkban napjainkban a kis- és középvállalkozásokra igen nagy feladat és elvárás hárul az elnépesedett külföldi tulajdonú nagyvállalatok jelenléte miatt. Ahhoz, hogy velük együtt tudjanak működni, be tudjanak kapcsolódni, s ezáltal integrálódni az általuk diktált értékláncba, minőségi követelményeknek kell megfelelniük. Ehhez elengedhetetlen a minőségi tanúsítványok megszerzése és megtartása, mely kizárólag alapos átvilágítás és problémafeltárás mellett lehetséges.

Ezt a kialakult helyzetet még tovább fokozza a valamennyi szektort érintő globalizáció, azaz, hogy globálisan is képesek legyenek versenyképesek maradni. Bár hazánkban a legtöbb KKV a családi vállalkozások sajátosságait viseli magán, az innovációt nem kerülhetik el, ha versenyben akarnak maradni. Ehhez pedig szervesen hozzátartozik a minőségbiztosítás.

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The Effect of annealing temperature on corrosion resistance and microstructure of Zr-Sn-Nb-Fe alloy
Megjelent december 12, 2019

The Ti-2Al-2.5Zr titanium alloy plate in beta phase water quench at different times of the reentry after annealing is implemented while primary phase number and size distribution of samples are obtained. This research is carried out on corrosion behavior in 3.5% [mass fraction] NaCl solution. Experimental study showed that after the beta phase ...water quenching Ti-2Al-2.5Zr titanium alloyed after 500 oC annealing when partial recrystallization happened. There seems to be lots of tiny dispersion in the alloy that was annealed with its samples of six-party [HCP] structure of Ti, Zr, Al phase 2 with the dimension below 100 nm. Reaching 500 oC when the rate of annealing at a primary phase of the sample at 550 oC is low 90% of the primary phase is less than 100 nm. The changing of the rule of present decreasing also triggers little difference overall. Precipitation in the process of annealing Zr [Nb,Fe,Cr] 2is less that proves to be good for corrosion resistance.

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Artificial Intelligence Possibilities in Vehicle Industry
Megjelent december 12, 2019

There have been several attempts during the last decades to extend the ranges of application of artificial intelligence. The aim of the development for AI is to replace human intelligence and experience. The ultimate aim for machines and vehicles is to run much more efficiently and with higher reliability than ever before. The Artificial Techni...ques (AI) used a wide range of expert systems to optimize problems. Hybrid intelligent management systems have become increasingly influential in artificial intelligence during the last decades. As a result, maintenance and fleet management systems have undergone significant development. By choosing adequate maintenance or operating strategy and taking user behaviour into consideration, these systems can not only increase the reliability and efficiency of vehicles but can also result in financial savings. The paper tries to discusses the applications of AI techniques in predictive maintenance and vehicle industry.

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Long Container Dwell Time at Seaport Terminals: An Investigation Study from a Consignee Perspective
Megjelent április 8, 2022

Abstract. Many companies are concerned about the problem of increasing average dwell time for their import containers at the port of the final destination and therefore incurring additional shipping costs in form of demurrage charges for the port administration and detention charges for the shipping line. Previous studies have addressed thi...s topic by analyzing terminal operations and evaluated its effects on port productivity and competitiveness; however few studies have explicitly explored long container dwell time causes from a consignee perspective. This research aims to identify the causes of long dwell time for the import containers at port storage yards for one of the leading FMCG companies in Jordan. To that end, the data of import containers whose stay at the terminal exceeded the free storage days in the period between 2019 and 2020 were collected by referring to the set of shipping documents and reviewing the correspondences between the consignee and other parties in the supply chain. Based on the timelines that have been analyzed for each case of delay to the collection of shipping documents in consideration with the payment terms, as well as the clearance and delivery timelines, ten causes for the long container dwell time have been identified and classified into three main categories according to the types of flow in the supply chain; five causes related to information flow, two causes related to cash flow, and three causes related to physical flow. The impact of these causes has been evaluated using the demurrage and detention charges as a measure indicator and the findings of this research have also revealed that the causes related to cash flow have a greater impact than the other types of causes.

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Battery Measurement Methods and Artificial Intelligence Applied in Energy Management Systems
Megjelent március 3, 2019

Diagnostics of batteries using advanced methods have gained remarkable roles in the past few years. This study focuses on the type of measurements, tests and methods to reveal and classify them. During manufacturing and operation several faults could emerge in batteries including non-optimal operation conditions, operators without experience, a...nd finally, random changes in batteries under physical and nonphysical conditions. Improper handling of batteries and battery cells man cause operation failures or, in the worst case, accidents. To reveal these problems several methods are applied in industry and in scientific laboratories. For a comprehensive analysis of battery management, artificial intelligence and Industry 4.0 methods can be used very effectively. Big Data analysis in its standard form is not a new achievement, but other mathematical tools could be applied to control monitoring such as Fuzzy Logic or Support Vector Machine (SVM). They are efficient tools to analyse the deviation of batteries condition because it can detect sudden changes, parameter deviations and anomalies, and the user’s behaviour and habits. This article gives a description about the most important battery testing methods and the connection between Big Data and Operation Management with Artificial Intelligent (AI) methods.

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