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This paper reports a study into the role of individual (S, P, N, C, Si, Mn, Ni, Cr) and combined (Q1=S, Q2=S+P, Q3=S+P+N, Q4=S+P+N+C, Q5=S+P+N+C+Si, Q6=S+P+N+C+Si+Mn, Q7=S+P+N+C+Si+Mn+Ni, Q8=Q=S+P+N+C+Si+ Mn+Ni+Cr) elements in five steel AISI 304 smelting cycles. The correlation between the rate of corrosion K in chloride-containing media and the specific magnetic susceptibility c0 of austenite (matrix), the low content Рdof d-ferrite, and the percentage of elements has been established. Taking into consideration the order of arrangement and influence of other present components, a set of the different-shaped graphic models of K dependences on c0, Рd, and percentage of elements was found. However, the sum of the eight calculated individual and combined elements (Q8) of the models coincides with the sum of the same elements (Q=Q8) of steel smelting samples that were subjected to experimental measurements of c0 and Рd. The curves of the reported models were compared with experimental dependences of K on c0, Рd. The positive and negative role of individual and combined elements in the process of pitting resistance of steel smelting cycles has been identified. Given this, it is assumed that the effect exerted on K by individual and combined elements in the intervals before and after their critical content may be ambiguous. Hence, one value K can correspond to several values of the contents of elements, c0, Рd. A proof of that is the coincidence between the calculated models K of corrosion on the same total content of Q8 for steel samples determined experimentally. The positive (negative) and ambiguous role of elements in the process of corrosion and the possibility of predicting corrosion tolerance of austenitic steels are assumed. The experimental dependence K on c0 and Рd has been established; the greater c0 and Рd, the lower the corrosion rate K. The studied steels contained d-ferrite in the low limits of 0.01...0.1 %.

Mathematical models that describe the dependences of the critical temperatures of pitting formation of AISI 304, 08Kh18N10, AISI 321, 12Kh18N10T steels in model circulating waters with pH 4…8 and chloride concentrations from 350 to 600 mg/l on their chemical composition and structure have been developed. They are based on linear squares regressions and a feed-forward neural network for reduced feature numbers. Using the developed mathematical models, it was found that the critical pitting temperatures of these steels increase with an increase in the pH of the circulating water, the number of oxides up to 3.95 μm in size, the average distance between titanium nitrides, the Cr content and a decrease in the concentration of chlorides in the circulating waters, the average distance between oxides and average austenite grain diameter. At the same time, it was found that the geometric dimensions of the steel structure most intensively affect their pitting resistance in circulating waters, and the effect of their chemical composition is minimal and is determined by the amount of Cr, which contributes to an increase in the pitting resistance of steels, probably increasing the solubility of nitrogen in the austenite solid solution. It is proposed to use the developed mathematical models to select the optimal heats of these steels for the production of heat exchangers and predict their pitting resistance during their operation in circulating waters.

The subject of the study is the process of Information and Measuring System (IMS) designing as a component of the Cyber-Physical System (CPS) in the paradigm of Industry 4.0 (I4.0). The aim of the study is to develop methodological support for the design of IMS and Automatic Control Systems (ACS) as components of production CPS (CPPS), in particular, for Digital Factory. Objectives: to determine the conceptual model of IMS; choose the IoT model for structural synthesis, select the appropriate regulatory (sets of standards and implementation models) and hardware; perform R&D of IMS based on NB-IoT sensors; formalize the procedure for integrating components into the CPPS, develop the Asset Administration Shell. The methods used are: heuristic synthesis methods, experimental planning theory. The following results were obtained. The key role of optimally designed IMS level 4.0 in increased decision-making accuracy in CPPS management and control processes is demonstrated. The quality of control is improved both by quickly obtaining accurate information for updating models in cyber add-ons, and at the physical level, in ACS. The universal model of IMS implementation in CPPS was proposed. The stages of choosing the concept, structure, hardware and communication protocols of the IIoT ecosystem IMS + ACS have been performed. The methodology was tested during the development of the NB-IoT Tech remote monitoring system, which has a decentralized structure for collection data on resources consumed. The integration of the ecosystem as a component of CPPS at the appropriate levels of the architectural model RAMI 4.0 has been performed. Regulatory support has been formed and the functional aspect of the Asset Administrative Shell for CPPS integration has been developed. Conclusions. Scientific novelty: it is proposed to design the IMS as a component of the AAS of the cyber-physical system, according to the implementation methodology of its subsystems at the corresponding levels of RAMI4.0 and the selected IoT model. The new approach, called "soft digitalization", combines the approaches of Industry 3.0 and 4.0, it is designed for the sustainable development of automated systems to the level of cyber-physical systems and is relevant for the recovery of the economy of Ukraine. Practical significance of the results: the IoT-Tech system based on Smart sensors has been developed and tested. This information and measurement system is non-volatile and adapted to measure any parameters in automated systems of various levels of digitization.