Abstract: This paper presents the solution of multi-objective optimization of the production process of an automated assembly line model, where combination of conventional mathematical methods and methods of artificial intelligence is used. Paper provides the description of methods used in this process, modifications that were realized in the computational process of NSGA - II evolutionary algorithm as well as the solution of the production process optimization respecting all the defined constraints. The first part of the solution, the definition of the set of non-dominated (Pareto optimal) alternatives, is realized by the modified NSGA – II evolutionary algorithm. From the Pareto optimal solutions, choosing the best solution using various mathematical metrics is presented. Approach for the synthesis of the results obtained from various mathematical metrics used to resolve the task is also mentioned with the scope of objectivization of the optimization process.

Keywords: assembly systems; genetic algorithms; optimization methods; mathematical programming; Pareto optimization

Abstract: In this paper a decentralized nonlinear robust control (DNRC) using loop shaping design procedure (LSDP) and gain scheduling (GS) technique is developed for MIMO (multiple-input/multiple-output) systems. The nonlinear system is linearized in several equilibrium points and for each of these latter a decentralized robust controller is calculated, using a proposed LSDP based on RGA (Relative Gain Array) theory, to regulate the system around the equilibrium point. To do this. The use of RGA theory is exploited to define the structure of the weighting controller of the LSDP with the most effective input/output pairing. Then, for each equilibrium point a full-order robust controller is calculated using LSDP, which configuration is simplified exploiting the RGA theory by proposing a selection matrix to deduce a simplified final robust controller. The overall control system is obtained by GS technique from switching between local simplified final robust controllers according to the scheduling parameter’s (SP) value. The proposed algorithm of control is validated on the AERO system of Quanser.

Keywords: Quanser’s AERO; MIMO nonlinear systems; RGA theory; robustness; decentralized control; gain scheduling

Abstract: This research article presents the effects of different abrasives (aluminium oxide, magnesium oxide, zinc oxide, iron oxide, silicon dioxide, titanium dioxide and zirconium dioxide) on tribological performance of non-asbestos brake friction materials. Therefore, friction composites with different abrasives were fabricated and characterized for various mechanical, chemical, and physical properties. The tribological properties of the friction composites were evaluated by running a European testing standard on a Krauss testing machine. It was seen that the different sorts of abrasives substantially affected the tribological performance of the friction composites. The highest values of friction coefficient (0.425), least friction fluctuations (0.252), highest stability coefficient (0.87) as well as the lowest fade (~ 23%) were obtained from the friction composites containing aluminum oxide as an abrasive. The recovery performance of all the friction composites was found to exceed 100% and the actual recovery level depends upon the type of abrasive. Contrary to the friction performance, the wear performance decreased for aluminum oxide and friction composite containing zinc oxide showed higher wear resistance.

Keywords: Polymer composites; Friction materials; Abrasive; Fade; Recovery; Wear

Abstract: The paper deals with the fault diagnosis methodology design for fault detection, localization, estimation and accommodation in a predictive control algorithm. The result of the proposed methodology realization is control and fault diagnosis system, which has a capability of actuators fault tolerance. The fault diagnosis system design is based on the group of unknown input observers. The fault diagnosis system and predictive control algorithm with fault accommodation are implemented in MATLAB. The designed algorithms, which are presented in this paper, are verified by simulations using the simulation model of the Ball on Plate system.

Keywords: fault diagnosis; fault-tolerant system; modeling; predictive control

Abstract: The hot rolled seamless steel pipes and tubes are used successfully in areas such as the petrochemical industry (in oil and gas transport or in the extraction industry). This study includes results of the experimental hot torsion tests conducted to find the plasticity and deformability characteristics of two low alloyed medium carbon steel grades (EA < 2.5%) destined for seamless tubes and pipes manufacturing, used in the petrochemical industry (fluid transport, extraction industry): grade 43MoMn16 and grade 33MoCr11.

Keywords: low alloyed medium carbon steel grades (43MoMn16, 33MoCr11); seamless tubes and pipes; temperature; hot torsion tests; deformability; diagrams

Abstract: The primary goal of this paper is to present a security risk assessment-based methodology for migrating sensitive Smart grid operational technology (OT) services to the computing cloud, either on or off-premise. We created a baseline system architecture diagram for smart grid Industrial Control Systems (ICS) aligned with the IEC-62443 model of security zones. We identified potential threat sources and threats which might affect the confidentiality, integrity, and availability (CIA triad) of OT services. We defined a threat impact and likelihood assessment strategy tailored for use in smart grids. Based on the combined impact and likelihood of threats we present a risk matrix, a tabular risk assessment template, and a baseline cloud migration strategy. We test our methodology on two cloud migration case studies, namely a large distribution system operator (DSO) with a complex OT environment; and a small DSO with limited OT capabilities, budget, and IT staff. As there are no risk assessment-based studies which tackle the problem of migrating smart grid OT services to a cloud computing architecture in a systematic way, our method will be a valuable asset for any smart grid system owner/operator. Which will be able to guide them in choosing an optimal cloud migration strategy, both fitting their specific requirements and maintaining an adequate level of information security.

Keywords: Smart Grid; Cloud computing; control systems; information security; IT/OT systems; risk analysis; SCADA systems

Abstract: The advancement of Internet of Things (IoT) has made it practical to discover, localize and pinpoint smart sensing devices based on the situational context, relevancy, and characteristics to query data intelligently, or conduct actions. Furthermore, the development of large-scale applications must deal with data collection and data sensing from a massive number of ubiquitous components, ultimately converging into 5G mobile networking. Additionally, IoT involves managing the expectations of Big Data sourced from many heterogeneous sources. This paper provides an overview of biomimetic methodologies, which represent a viable solution for large-scale data delivery through the aggregation of information with large-scale IoT technologies.

Keywords: 5G communications; big data; Internet of Things; machine-to-machine systems; massive-scale systems; middleware; ubiquitous systems; wireless sensor and actuator networks

Abstract: Based particularly on data technologies, information is rapidly evolving in engineering. In mechanical engineering, maintenance is benefiting the most from data innovations, the reduction of maintenance costs, and the improvement of system availability. Modern reliability engineering targets uncertainty with advanced statistics and data science. This paper explores maintenance descriptive analytical techniques to determine whether variations between porosity percentage in batches from two similar machines are due to randomness, suggesting technical issues on machinery. The finding is backed by statistical analysis, hypothesis testing, and data mining. Python 3 was used following best practices of data science and data visualization as the main toolset to explore the working data, execute the proposed statistical analysis, and make conclusions. The findings were promising reinforcing the importance of advanced statistics for reliability studies. As a conclusion, we failed to reject the null hypothesis suggesting that there was no apparent difference between sample means. With a confidence of 95%, the difference is explained by natural variations and randomness inherent to the fabrication process.

Keywords: reliability engineering; python programming; statistical analysis; maintenance optimization

Abstract: With the increased use of robots with different performance characteristics in areas such as search and rescue, patrolling and surveillance, the control of multiple robots with unequal capabilities have gained a lot of interest among robotics researchers. Also, the uncertainty of the sensors utilized on the robots for localization has made the problem of imprecise localization attractive. This paper aims to present the development and implementation of a multi-agent collaboration algorithm under localization uncertainty using Hopfield neural networks, guaranteed power Voronoi diagrams (GPVD or GPD), and coverage control. The agents are considered non-holonomic wheeled mobile robots under the assumption that their locations are not known precisely, but they are known to be in uncertain circles. The workspace is partitioned with a Guaranteed Power Voronoi Diagram (GPVD or GPD) algorithm which takes imprecise localization into account. Also, it is assumed that the actuation capabilities of the robots are different from each other and the agents do not know those performances beforehand. The performance parameters of the robots are learned by using the collaboration algorithm with Hopfield Neural Network (HNN) and then passed to the GPD algorithm. The GPD algorithm together with the HNN provides workspace partitioning for the robots so that the agents with poor actuation performances take smaller regions from the workspace while the agents with strong performances take greater regions. Thus, a collaborative coverage task is achieved which enables the robots to deploy themselves to an optimal configuration minimizing the total coverage cost. The simulation results in MATLAB show the efficiency of the algorithm. The experimental results with the Robot Operating System (ROS) are given. The results obtained are satisfactory since the algorithm has faster convergence and has the capability to assign the regions from the workspace considering the imprecise localization resulting from sensor characteristics. Finally, the algorithm is compared to the base collaboration method, important performance improvements had been observed.

Keywords: Workspace allocation; Coverage control; Guaranteed Power Voronoi Diagrams; Hopfield Neural Network

Abstract: We propose a novel method for binary-based decision diagrams (DD) which uses a residual variable. A new type of DD – Residual Variable in decision diagram (RViDD) allows to work without the use of the lowest and the most numerous level of nodes but at the same time preserves all the fundamental characteristics of DD. Thanks to these properties, it allows the use of all existing algorithms for optimization with only slight or no modification. In this paper we present the required characteristics for providing compatibility between DD using different decompositions and RViDD as well as the exchange of residual variable without the necessity of constructing a new RViDD. Proposed method was experimentally validated on benchmark circuits with various types of experiments. We use exhaustive (all input variable combination) comparative between reduced and ordered DD and RViDD with the average improvement up to 17.55%. Since optimization of DD is a NP-complete problem, we also include the usage of evolutionary algorithm for RViDD in comparison to more effective algorithms.

Keywords: BDD; KFDD; decision diagrams; residual variable

Abstract: Aircraft applications require high reliability, high availability, and high power density, while aiming to decrease weight, complexity, fuel consumption, operational costs, and environmental impacts. Modern electric driving systems can meet these demands and provide significant technical and economic enhancements over traditional mechanical, hydraulic, or pneumatic systems. Due to the high reliability of Switched Reluctance Motors (SRMs), it can be used for aircraft electromechanical actuators to replace the conventional actuators. This paper presents Model Predictive Control (MPC) for the actuators system to drive flight control surfaces in modern civil aircraft. In this study, the actuators system with nonlinear SRM is modeled, simulated, and controlled using a predictive control technique. The predictive control algorithm is applied for a three-phase controlled rectifier to provides a fixed DC voltage for actuators supply bus, and for SRM's symmetrical power converter to drive the surface of the actuator. The performance of the proposed system is tested using a simulation model in PSIM software, and the controller is programmed using C language. Obtained results confirm the effectiveness of the suggested system to drive aircraft electromechanical actuators satisfactorily for either tracking demanded motor speed or desired actuator deflection angle.

Keywords: Switched Reluctance Motor; Model Predictive Control; Current Control; More Electric Aircraft; Aircraft Electrical Actuators

Abstract: Emotional intelligence is at the heart of our research. Our aim was to examine the differences that exist between generations, based on the views of their representatives. In the theoretical portion we dealt with defining emotional intelligence and presenting it from the leaders’ aspect. Finally, each generation is introduced. In our paper we set up 2 hypotheses, which are cross-tabulated and / or analyzed with the help of related statistical methods. In the end, both our hypotheses proved to be true. This article contains 2 figures and 2 tables. Our paper ends with a section on conclusions, in which we summarize our research, results and outline our findings.

Keywords: emotional intelligence; generations; workplace