Autonomous driving is no longer just an idea of technology vision instead a real technical trend all over the world. The continuing development to a further level of autonomy requires more on mobile robots safety while bringing more challenges to human-vehicle interaction. A robot autonomous vehicle (AV) as a research platform operates an experimental study on human-AV-interaction (HAVI) and performs a novel method for mobile robot safety assurance. Not only autonomous driving technology itself but human cognition also performs an essential role in how to ensure better autonomous mobile robot safety. A Wizard-of-Oz experiment in the university combing a survey-based study indicates public attitudes towards driverless robot vehicles. HAVI experiment have been carried through light patterns designed for experiment. This paper presents an attempt to investigate humans’ acceptance and emotions as well as a validation to bring the mobile robot vehicle to a high-level autonomy.

During of hypereutectic Al-Si alloys, tool wear increases owing to the presence of silicon particles. Therefore, polycrystalline diamond tools are typically used, but they are very expensive. The purpose of this study is to examine the tool wear characteristics during the end milling of hypereutectic Al-Si alloy (A390–T6) by using comparatively inexpensive diamond-like carbon coated cemented carbide tools. Al-Si alloy was end-milled by changing the cutting speed. Our results revealed that the width of flank wear land increased monotonously with increasing of the cutting force regardless of the cutting speed. In addition, the experimental equation of the width of flank wear land was derived as a function of cutting speed and time, and it was clarified that width of flank wear land could be approximated.

The successful selection process of industrial robots (IRs) for today's Cyber-Physical Systems is an important topic and there are different possibilities to solve the task. The primary task is to estimate the existing IR selection systems according to the suitability analysis and to highlight the main positive features and problematic areas. The objective of the reverse task is to carry out the sensitivity analysis of the existing robot-based manufacturing systems. The matching of these two approaches helps decision makers to develop the main principles of IR selection in today`s multidimensional and fast-changing economic world.

The paper present theoretical and experimental studies of the energy dissipation performance of a composite structure composed in a multilayer nano-composite damping coating applied on a tungsten carbide shim and placed beneath the cutting insert. The coated shim placed closed to the cutting zone is subjected to high compressive and shear stresses as well as high temperature. Therefore, apart from high damping capacity it requires high stiffness and high thermal resistance. The coated shim dissipates the high frequency oscillations produced at the tool-chip and tool-workpiece interfaces during the chip forming process. The use of coated shims demonstrates that the tool life is considerably extended, while the machined surface integrity is improved. The Reuss model of the composite structure composed of a phase with a stiff, low loss factor and a phase with high loss factor is used to calculate the optimal coating thickness that gives high loss factor combined with high stiffness. The synthesis process of the coating material using HiPIMS process is discussed. The physical characteristics of the coating and the machining performance are presented in the experimental section.

The article presents FEM model of an angular contact ball bearing used in spindle systems with active preload control. A two-dimensional replacement model for a single rolling element was developed. Its elastic characteristics were determined and the stress distribution was presented for the FEM 2D model. Based on the elastic characteristics for a single rolling element, a complete 3D bearing was modelled. The substitute model of a bearing developed in this way was used to model the spindle system. The elasticity curve of this spindle was determined. The last stage of the work involved the experimental verification of the FEM model using a custom-built test bench, in which piezoelectric elements were used to preload the bearings.

This paper highlights the performance of precision hard turning with CBN cutting tools from energy point- of-view with additional tool wear effect. For this purpose several wear tests were performed during which the tool nose wear VBC and the corresponding changes of component forces Fc, Ff and Fp were continuously measured. Based on the measured forces and geometrical characteristic of the uncut layer, specific cutting and ploughing energy were determined for several combinations of cutting parameters. Consequently, changes of energy consumption resulting from tool wear evolution for variable feed rate, depth of cut and tool nose radius were presented.

The prediction of component properties from the Additive manufacturing (AM) process poses a challenge. Therefore, this paper presents the development of a novel machine data (G-Code) based procedure as well as its programming implementation of a process simulation in ANSYS Mechanical for the fused layer modelling (FLM) process. For this purpose, an investigation of additively produced components with varying parameters made of polylactic acid (PLA) is carried out and simulated by means of the developed method. Application of the developed method makes it possible to predict the thermally induced distortion of PLA-Parts based on the machine data from the FLM process before production.

During the years common understanding of the possibilities and perspectives of Virtual Reality (VR) usage has been changed. It is thought that VR is mainly used in entertainment purposes, but it is being used already for many years in different industries, and now with easier access to the hardware it became a helpful and accessible tool that could be used and developed in any field of human activities. In manufacturing, immersive technologies are mainly used nowadays for the visualisation of processes and products combining those visuals into the factory Digital Twin (DT) which is possible to view from the inside look. This feature is already being used in several manufacturing simulation tools, which enable to view onto industrial line / robotic cells via Virtual Reality glasses. However, the potential of using simulations with VR in manufacturing is not fully uncovered. The main aim of this, industrial robotics targeted research is to enable besides simulation also universal control algorithms through Virtual Reality experience, produced by game engine Unity3D, which can be easily modified for a wide range of industrial equipment. The primary outcome of this work is the development of the synchro-nisation model of real and virtual industrial robots and experimental testing the developed model in Virtual Reality and shop floor labs

This review paper highlights the hybrid manufacturing processes which integrate the additive and subtractive processes performing on one hybrid platform consisting of the LMD (laser metal deposition) unit and CNC machine tools. In particular, some important rules and advantages as well as technological potentials of the integration of different AM technique and finishing CNC machining operations are discussed and overviewed. Some representative examples such as formation of difficult features around the part periphery, deposition of functional layers and coatings and repair of high-value parts in aerospace industry are provided. Some conclusions and future trends in the implementation of hybrid processes are outlined.

The paper discusses Single Minute Exchange of Die (SMED) and machine learning methods, such as neural networks and a decision tree. SMED is one of lean production methods for reducing waste in the manufacturing process, which helps to reorganize a conversion of the manufacturing process from current to the next product. SMED needs set-up activity analyses, which include activity classification, working time measurement and work improvement. The analyses presented in the article are focused on selecting the time measurement method useful from the SMED perspective. Time measurement methods and their comparison are presented in the paper. Machine learning methods are used to suggest the method of time measurement which should be applied in a particular case of workstation reorganization. A training set is developed and an example of classification is presented. Time and motion study is one of important methods of estimating machine changeover time. In the field of time study, researchers present the obtained results by using (linear) multi-linear regression models (MLR), and (non-linear) multi-layer perceptrons (MLP). The presented approach is particularly important for the enterprises which offer make-to-order products. Development of the SMED method can influence manufacturing cost reduction of customized products. In variety oriented manufacturing, SMED supports flexibility and adaptability of the manufacturing system.