Ústav výrobních strojů, systémů a robotiky

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Issues of Cybersecurity of The Production System
(MM Publishing, 2022-12-01) Maradová, Karla; Blecha, Petr; Blecha, Radim; Rozehnalová, Jana; Frkal, Vojtěch
Cybersecurity of production systems is a very topical issue in response to the dangers associated with the very high number of cyber-attacks in Europe. The current digital transformation of the industry associated with the digitalisation of manufacturing brings both the positives associated with increased flexibility and productivity of production, and the negatives associated with the risk of data loss, data alteration or blocking of control systems. Cybersecurity issues are also reflected in the revision of EU harmonisation legislation governing the requirements for placing products on the market or in service. It appears that the issue of cyber security needs to be addressed comprehensively across the entire infrastructure of a manufacturing plant. The present paper focuses on the relationship between machinery security and OT/IT security and presents the results of a study aimed at identifying potential sources of threats in an integrated manufacturing system.
CNC Machine Tool Safety From The Aspect Of Hazard Perception By Operating Personnel
(MM publishing, 2022-10-01) Blecha, Petr; Marek, Jiří; Blecha, Radim; Rozehnalová, Jana; Heinrich, Petr; Pacher, Petr
Safety of machinery, including CNC machine tools, must be ensured in all phases of their life cycle. The operation and maintenance phase is the most important as it represents the longest period in the machine ' s technical life linked to occurrence of work injuries. Every designer of a safe machine must consider also any reasonably foreseeable incorrect behaviour of the machine operator. The latest revision proposal of the Machinery Directive 2006/42/ES sets new requirements on solution of CNC machine tools safety. Aside from assessing the impact of cybersecurity on the machinery safety, the manufacturers will now have to take into account also the psychological stress arising from human-machine interaction. From the psychological point of view, the operating personnel of multifunctional CNC machine tools experience high level of stress when machining complicated and complex-shaped workpieces as the material often costs as much as 30% of the price of the machine; therefore, any mistake of the operator resulting in a nonconforming product causes high financial loss. Influence of various stressors on the operating personnel leads to their impaired concentration on the performed tasks, which may be accompanied by insufficient perception of the hazards associated with the machine operation and thus may lead to occurrence of work injuries. The presented paper discusses the factors that may put the operators of multifunctional CNC machine tools under psychological stress and analyses possible application of the virtual reality technology to assess the ability to perceive the hazards linked to such a complex machine on a group of university students representing both operators (beginners) and designers of a multifunctional CNC machine tool.
Numerical Aspects of Multilateration for Volumetric Error Calculation
(MDPI, 2022-09-21) Holub, Michal; Zatočilová, Jitka; Marek, Tomáš; Blecha, Petr; Heinrich, Petr
We discuss two approaches to multilateration with a particular focus on numerical aspects for a given dataset. More precisely, we calculate the volumetric errors of the MCV 754 milling machine from the data measured by a LaserTRACER and provide criteria showing which numerical method is appropriate for the solution of the multilateration problem with respect to a given measurement dataset. In the first case, we consider two cost functions of the optimisation problem; in the second, we use the extremal principle method. We discuss the calculation accuracy depending on the matrix condition number. Our results are compared to the reference results produced by the Trac-Cal software, which is a standard used by most producers for error compensations.
Capability of measurement with a touch probe on CNC machine tools
(Elsevier, 2022-04-12) Blecha, Petr; Holub, Michal; Marek, Tomáš; Jankových, Róbert; Mišún, Filip; Smolík, Jan; Machálka, Martin
Increasing the productivity of high-precision manufacturing requires efficient product inspection, for example, using integrated scanning systems on CNC machine tools (MT). However, measuring the dimensional and shape accuracy of workpieces using a touch probe (TP) on MT is negatively affected by the geometric accuracy setting of the MT, thermal stability of the MT and its surroundings, type of scanning system. The aim of this paper was to examine the possibilities of assessing the capability of touch probe measurements on MT, to define the size of the permissible controlled tolerance of the workpiece and to assess the influence of the geometric accuracy of the machine on the size of the permissible tolerance parameter of the inspected workpiece. In the presented experiments, the calculation of the TP measurement capability is based on a new approach respecting the VDA5 standard extended by the minimum tolerance (TOLmin) conformity assessment procedure according to ISO 14253-1:2017.
Vibrodiagnostics Faults Classification for the Safety Enhancement of Industrial Machinery
(MDPI, 2021-09-30) Zuth, Daniel; Blecha, Petr; Marada, Tomáš; Huzlík, Rostislav; Tůma, Jiří; Maradová, Karla; Frkal, Vojtěch
The current digitization of industrial processes is leading to the development of smart machines and smart applications in the field of engineering technologies. The basis is an advanced sensor system that monitors selected characteristic values of the machine. The obtained data need to be further analysed, correctly interpreted, and visualized by the machine operator. Thus the machine operator can gain a sixth sense for keeping the machine and the production process in a suitable condition. This has a positive effect on reducing the stress load on the operator in the production of expensive components and in monitoring the safe condition of the machine. The key element here is the use of a suitable classification model for data evaluation of the monitored machine parameters. The article deals with the comparison of the success rate of classification models from the MATLAB Classification Learner App. Classification models will compare data from the frequency and time domain, the data source is the same. Both data samples are from real measurements on the CNC vertical machining center (CNC-Computer Numerical Control). Three basic states representing machine tool damage are recognized. The data are then processed and reduced for the use of the MATLAB Classification Learner app, which creates a model for recognizing faults. The article aims to compare the success rate of classification models when the data source is a dataset in time or frequency domain and combination.

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