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  • Maintenance of Electric and Hybrid Vehicles

    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 to 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.

  • Conceptual Design of the Low-Cost Environmental Temperature Test Chamber System

    Unmanned robots being remotely controlled or autonomous are spread worldwide and used in different purposes. Inhabited robots are brought very close to users and accessibility to these tools is very high, moreover, at very low costs. Regardless to emphasize the increasing popularity of these robots. However, any robot system being electrically driven and controlled has bottleneck in the amount of the electrical energy stored aboard in the battery packs. In other words, due to limited amount of the electrical energy available special issues related to use energy best way with maximum effectiveness are needed and considered. Additionally, the battery management system is needed to control the processes of the discharge and the charge ensuring technical data and parameters set by the manufacturer. This paper addresses robot applications in regions out of the calculated when special environmental testing is needed to confirm battery pack technical data. Among those of the environmental tests required the temperature test is in the focus of attention. The main idea and purpose of this paper is to set up new concept of the low-cost environmental temperature test chamber, to define its technical parameters and other properties needed for its preliminary design and prototype manufacturing.

  • Optimization and Analysis of Structure about Lifting Device of Logistics Sorting

    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 software 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.

  • Analysing the Conditions of SMEs Regarding Quality Assurance in Hungary and the European Union

    Nowadays, small and medium sized enterprises (SME) have a relatively large task and expectation caused by the appearing of populated large foreign-owned enterprises in our country. In order that they will be able to cooperate with them and be able to join and integrate into the value chain they supply they must meet the high quality of standards. Obtaining then preserving quality certificates is essential for this. It can be fulfilled exclusively with thorough screening and problem identification.

    This situation is exacerbated continuously by globalization in which each sector is involved. It means that they must remain competitive globally. Although in our country most of the small and medium sized enterprises bears the specific characteristics of family businesses innovation may not be avoided if they intend to stay competitive. To fulfil this quality assurance is one of its integral part.

  • The Effect of annealing temperature on corrosion resistance and microstructure of Zr-Sn-Nb-Fe alloy

    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.

  • Artificial Intelligence Possibilities in Vehicle Industry

    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 Techniques (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.

  • Manufacturing Process Optimization and Tool Condition Monitoring in Mechanical Engineering

    The optimization of manufacturing and production processes with various computer software is essential these days. Solutions on the market allow us to optimize and improve our manufacturing and production processes; one of the most popular software is called Tecnomatrix, which is described in this paper. Tool condition monitoring is a vital part of the manufacturing process in the industry. It requires continuous measurement of the wear of the cutting tool edges to improve the surface quality of the work piece and maintain productivity. Multiple methods are available for the determination of the actual condition of the cutting tool. Vibration diagnostics and acoustic methods are included in this paper. These methods are simple, it requires only high sensitive sensors, microphones, and data acquisition unit to gather the vibration signal and make signal improvement. Extended Taylor equation is applied for tool edge wear ratio. Labview and Matlab software are applied for the measurement and the digital signal processing. Machine learning method with artificial neural network is for the detection and prediction of the edge wear to estimate the remaining useful lifetime (RUL) of the tool.

  • Long Container Dwell Time at Seaport Terminals: An Investigation Study from a Consignee Perspective

    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 this 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.

  • Battery Measurement Methods and Artificial Intelligence Applied in Energy Management Systems

    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, and 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.

  • Defect Analysis of Bearings with Vibration Monitoring and Optical Methods

    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.

  • LSI with Support Vector Machine for Text Categorization – a practical example with Python

    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 programming 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.

  • Sustainable Energy in Aviation with Reverse FMEA Analyses

    This research aims to identify and evaluate the key challenges and obstacles hindering the adoption of sustainable energy in the aviation industry. The outcomes and insights derived from this research will be synthesized to provide a comprehensive overview of the opportunities and suggestions for the adoption of sustainable energy in the aviation industry. The objective of this study is to help the aviation industry’s shift toward more sustainable energy sources in order to reduce its environmental footprint and mitigate the effects of climate change. 

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