Mechatronics, System Engineering and Robotics

In addition to the analysis of the transformer's assessment in view of the impact on the topology of the transmission, generation and distribution system, the recognition of the status of parameters and performance is a necessity to increase the efficiency of operational work, but the techniques/methods to perform the monitoring are essential. In this context, advanced monitoring techniques as well as smart devices that allow access to continuous analysis and diagnosis of parameters that are considered important for this purpose should be considered. One important condition of monitoring and diagnosis are the temperatures of the power transformers. In this paper are depicted the analysis through trends and alarms of the temperatures by comparing the range of the limits by on-line and off-line techniques. Furthermore, the operational work and the status of monitored parts by year, load and alarms are presented. Prepared monitoring and diagnostic reports, and appropriate corrective measures are taken depending on the status of the power transformer based on their temperatures trend.

Continuous market demand shows a fast transition of Additive Manufacturing (AM) from prototype to regular production. The different complex parts are easier to manage using 3D scanners and applying Reverse Engineering (RE) to convert them into digital data that can be reproduced again. Through this paper we intend to explain the relationship between RE and AM with decision making methodology by applying AHP hierarchy, including: goals, criteria, sub-criteria and alternatives. Case study presented confirm the efficiency of the proposed methodology for decision making in production technology.

This paper presents two possibilities of martensitic (fine grain and coarse grain) microstructure preparation. These microstructures are present as sub-zones in the heat-affected zone of welded joints, but due to the narrow region of HAZ in a real weld, only a few tests are possible to perform such as micro-hardness. Welding simulator and laboratory furnace were used as methods for the preparation of the specimens. The material used in this study was a Nickel Molybdenum alloy steel (18CrNiMo7-6). Investigation of the mechanical properties of sub-zones of the HAZ of this particular alloy steel, were done by applying proper thermal cycles. Hardness and diameter of grain size were measured, tensile strength is calculated and Charpy instrumented test of both microstructures were performed in room temperature. The difference in Impact toughness was remarkable due to the difference in microstructure, energy for initiation and propagation were calculated by comparing (F-t and E-t) diagrams for both microstructures. The study revealed that the preparation of specimens with microstructure as at welded condition is possible, and it could lead to prepare samples for investigation of other mechanical properties such as fatigue crack growth and fracture toughness test.

Image classification application has recently been covering a high number of research fields. In the other hand as the performance of the mobile devices is being updated day by day, the implementation of image recognition algorithms in them, is not only being trendy but very helpful in everyday tasks. With the automatic monument recognition, visiting a city is easy and fun. This application recognizes the captured monument, gives useful information and describes that particular landmark.

In this paper there are used four historical monuments of the city of Prizren, Kosovo and the aim is to classify these four famous monuments.

The images where taken specially for the research from the different angles of the city and the dataset for the classification process has been created.

One of the most convenient algorithms of Deep Learning is used for the classification of these four types of monuments. Using Matlab, a convolutional neural network architecture is adopted for the training of the created model.

After the model is fully trained, it is validated and tested to calculate the accuracy of the model.

In this paper, we design and implement a low-cost energy monitoring sensor that can be used in many applications, such as in electricity billing, energy management in smart grid and also at home automation. The design is based on a low-cost HLW8012 chip and ESP32 microcontroller. Measurement of electric power using HLW8012 with Kalman Filter is a new technique proposed in this paper. The experimental results showed that this sensor with this new algorithm can monitor energy and successfully measure data like voltage, current, active power and reactive power.

In secondary raw materials and industrial recycling sectors there is the need of solving quality control issues. The development and deployment of an effective, fast and robust sensing architecture able to detect, characterize and sort solid waste products is of primary importance. Near InfraRed (NIR) based HyperSpectral Imaging (HSI) techniques to detect materials to recycle and/or solid waste products to process represents an interesting solution to address quality control issues in these sectors. In this paper, are presented two different case studies on the utilization of NIR-HSI to detect contaminants in household plastic packaging waste and recognize materials occurring in processed monitors and flat screen waste.

The proposed approach consists of a cascade detection based on Partial Least Squares – Discriminant Analysis (PLS-DA) classifiers applied on hyprspectral images acquired in NIR range (1000-1700 nm).

Nowadays is very important to control systems. Crane systems are tremendously utilised in numerous heavy load transportation industries, and therefore, the control of crane systems is a well-established research field. The system is described by mechanical equations, equations of motion and transfer function. The case of open loop is also analyzed and simulated parameters of PID controller to stability Crane system. The PID controller and the modeling of the system is executed in Matlab-Simulink.

The trend of constructing and converting an ordinary home into a smart home has been on a steady rise in recent years, all thanks to new technologies now being implemented such as Internet Of Things (IoT) and smart devices that have the ability to collect important data in order to optimize consumption and reduce the cost of electricity. Smart homes are considered expensive, but there is a possibility for a homeowner to implement some of the smart technologies without making huge expenses and investments. One way to do this is to use smart sockets, which make it possible for an ordinary home to function as a smart one. The purpose of this topic is to explain the impact of applying smart outlets to ordinary homes as well as the steps that are needed to be taken to develop such a product. Starting from understanding hardware product development strategies to applying them in our case in important processes like the electronic part development, programming, development of a simple mobile application for user interaction and finally a description of the mechanical parts designed in 3D.

By changing the way of production with the same resources engineers and managers always trying to increase outcomes. Lean is a method that is focused on reducing waste, it is used to manufacturing industries to reduce waste and, in the meantime, the quality is higher. Application of lean manufacturing into enterprises may bring many benefits and advantages such as time reduction to the customers, efficient usage of processes, less utilization of inventory, improvement of knowledge management, cost savings, and rework reduction. This paper has attempted to understand how lean manufacturing is being used in the Kosovo Manufacturing Industry and benefits implementation of lean manufacturing techniques and their facilities.

Optical based characterization techniques and related analytical methodologies, originally utilized in the mineral sector, can be profitably applied to solid waste streams products as resulting from different recycling processes. This approach, when supported by digital tools allows to perform a full characterization of compositional and textural attributes of the different particulate solids constituting the waste flow streams. To reach this goal specific physical-chemical attributes must be collected, analyzed and processed in order to define, according to market requirements, specific classes of quality to assume as reference to define optimal processing strategies. Computer-assisted optical characterization, coupled with hyperspectral sensing devices and embedding recognition/classification logics, can contribute to reach these goals, dramatically reducing analytical time and costs. In this work an example of this “transfer approach”, from minerals to waste, is presented, analyzed and discussed, with reference to a porphyry copper ore sample and a WEEE product.

Diversity and inclusion are the vital to the long-term success of any business. In Industry 4.0 and 5.0 there is a requirement that engineering firms have the best talent to foster innovation, entrepreneurship and growth. The best talent means offering engineering education to all members of society, including minority groups. Traditionally automation is not an engineering sector that attracts a diverse cohort. This paper looks at why science, technology engineering and math (STEM) in general, and automation in particular, flourishes when opened up to a more diverse and inclusive community and it offers insight as to how to attract this more diverse and inclusive society.

As we know the artificial intelligence, and specifically artificial neural networks, have improved rapidly in the last decade which leads to the application of these systems in commercial fields like in buying online products, medical applications, financial applications, etc. But we know also that ANN usually are complex systems that need a lot of computing power in order to function properly which limits their application in number of fields, including here embedded systems because of their limited hardware and software properties. In this paper our goal is to implement a fully functional ANN in ATmega328p microcontroller, which will be programmed and trained in microcontroller. Our study case is solar tracker, where we aim to create a functional tracker which works based on ANN and with very limited hardware resources. With this implementation we aim to prove that ANN can function in practical systems without need of high computing power but just with simple low cost embedded system.

The possibility of increasing production capacity by re-designing the actual layout and material flow at the Elsam factory is explained in this article. Planning of the actual layout needs some improvements because it does not meet customer demand. The actual layout is found to be disorganized on material flow which leads to a decrease in production capacity. Three different layouts are considered and analyzed. A comparison between the proposed and actual layout is shown to find out the influence on production capacity. According to the data taken from simulation software FlexSim, significant improvement is foreseen. This study reveals that redesigning the layout ensures an increase of production capacity and decrease the possibilities of accidents during transportation between consecutive workstations by decreasing the traveling distance.