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The article discusses the approach to collecting and aggregating data from sensors located on heterogeneous technological equipment using the principles of the industrial Internet of things. The main analytical data processing platforms are considered, the advantages of using ready-made and own solutions are shown. A practical example of the collection of parameters from a planer-milling machine with their subsequent analytical processing, which revealed the need for unscheduled technological maintenance of the spindle assembly, is presented.

The basic aspects of preparing a cutting tool for applying wear-resistant coatings to it, in particular, the use of brush technology to round its cutting edges, are investigated. A structural model for constructing a specialized brush machine control system has been developed and the basic aspects of its development have been determined.

The work deals with the features of construction of human-computer interaction to manage the complex process equipment. The mechanism for creating additional portable terminals for monitoring and controlling complex machine tools is presented. A practical example of using the mechanism for creating additional terminal solutions for monitoring and controlling the Quaser MV184P milling machining center is given.

Many industrial manufacturing and enterprises are currently undergoing a digital transformation phase. The digital transformation of a manufacturing is a complex and multilateral process that affects almost all levels of production. For some, this is a necessary step that will reduce production costs, for others it is an opportunity to rethink the business processes of building a full-fledged digital production with the implementation of the concepts of Industry 4.0. This transition is mainly based on the principles of data collection, storage and processing, followed by analysis and the possibility of impact on production. But also an important factor is the approach to planning the activities of the enterprises. At the same time, the combination of flexible management methodologies with the possibility of obtaining data on the state of production will allow bringing existing business processes to a new level.