Nickel superalloys occupy a reasonably broad niche in the industry. One of this group’s most common and well-known alloys is Inconel 718. Parts from Inconel 718 are used in aerospace, energy, automotive, and some other vital industries, which creates a demand for research and improvement of the machining conditions of this alloy. This article is devoted to the systematization and generalization of the accumulated experience of machining of Inconel 718 at turning operation. The research methodology is based on the Pareto distribution. In the study, more than 50 articles devoted to turning Inconel 718 were analyzed. The tool materials, methods, and types of coating used in turning Inconel 718 were analyzed. Finite element method modeling of processing processes has been considered. The trends in the selection of cutting parameters and the geometry of the cutting tool and finite element method modeling of processing processes have been considered. Lacunae for promising future research were formulated.

In the study, an automated selection of cutting tools and cutting parameters was performed for the turning of the breech component of the stationary smoke mortar of the AEK-902 “Khmara” aerosol system. The AEK-902 is actively used by the Armed Forces of Ukraine to create a dense smoke screen in order to conceal military equipment from enemy visual, infrared, and thermal detection systems. The breech is a critical mortar component subjected to significant mechanical and thermal loads during operation, which imposes high demands on the quality of its manufacturing, geometric accuracy, and wear resistance. An automated selection of cutting tools and cutting parameters for each turning operation of the breech was carried out using specialized software from two leading global manufacturers of cutting tools: Walter GPS (Walter company) and Sandvik Coromant ToolGuide (Sandvik Coromant company). The selection was made taking into account the type of machining, the geometry of the workpiece, material characteristics, and the requirements for accuracy and surface quality. As a result, a nomenclature of tooling (toolholder and insert types) recommended for each specific turning operation was obtained, as well as productive cutting parameters. For operation 010, the following set of cutting tools is proposed: DSSNL2020K12 turning tool with SNMG120416-PR4335 insert, 462.1-1850-056A1-XM-X2VM drill, DCLNL2525M19 turning tool with CNMG190608-PR4335 insert, A12M-STFCL11 boring tool with TCMT110208-UM4335 insert, A25T-SSKCL12 turning tool with SCMT120412-PR4425 insert. For operation 020, the following tool set is proposed: DCLNL2525M19 turning tool with CNMG190608-PR4335 insert, A16R-SSKCL09 and A25T-SSKCL12 boring tools with SCMT09T308-PR4425 inserts, C2R-CE25-L-J08GB and C2R-CE25-LH07GB grooving tools with corresponding inserts C2I-J2N-0500-0004-TF1225 and C2I-J2N-0400-0004-TF1225, as well as L166.0KF-16-1220-11B threading tool with L166.0L-11MM01-200 1020 insert and 266LKF-20-16 threading tool with 266LL-16MM01A200M 1125 insert.

Nickel superalloys occupy a reasonably broad niche in the industry. One of this group's most common and well-known alloys is Inconel 718. Parts from Inconel 718 are used in aerospace, energy, automotive, and some other vital industries, which creates a demand for research and improvement of the machining conditions of this alloy. This article is devoted to the systematization and generalization of the accumulated experience of machining of Inconel 718 at turning operation. The research methodology is based on the Pareto distribution. In the study, more than 50 articles devoted to turning Inconel 718 were analyzed. The tool materials, methods, and types of coating used in turning Inconel 718 were analyzed. Finite element method modeling of processing processes has been considered. The trends in the selection of cutting parameters and the geometry of the cutting tool and finite element method modeling of processing processes have been considered. Lacuna for promising future research was formulated.

In the study, the decision-making methodology for a web application for automated cutting tool and tooling selection is considered. It is proposed that the constraint satisfaction logic method be used to filter the sets of alternatives in the application database, and the multi-criteria decision-making (MCDM) can be used to rank the alternatives further. For evaluation and ranking based on the proposed criteria, it is suggested that MCDM methods, including the weighted sum method (WSM) and the similarity preference ordering technique (TOPSIS) are used. A calculation using the specified methods for five alternatives (sets of cutting tools for mechanical turning) in the MATLAB environment was carried out. Based on the calculation, it was established that for a small sample, the WSM and TOPSIS methods had a similar result, but due to the difference in calculation approaches when the sample (filtered set of alternatives) increases, the result may differ, which makes it advisable to use these methods in parallel.

Within the study, the increase in processing productivity of the mortar body part of the aerosol system AEK-902 “Tucha”, is studied, which is actively used for camouflage and enhancing combat capability of military equipment and vehicles, serves as an auxiliary means for evacuation, and as a defense method against drones. Using the automated selection method, cutting tools and efficient cutting parameters were chosen for mechanical turning operations, utilizing software, including Sandvik ToolGuide, Walter GPS, and Iscar Tool Advisor. The obtained parameters were compared, the productivity was calculated using the material removal rate (MRR) method, and comparative productivity charts were created. Based on the data, recom-mendations for selecting cutting tools and processing parameters for specific turning operations were developed. The results are based on software recommendations and require further experimental verification in real production conditions. Verifica-tion through practical experiments will allow comparison of calculated parameters to actual processing indicators, refining the parameters and considering possible deviations. This is relevant direction for future research in automated tool selection and optimizing mechanical processing.