OBRABOTKAMETALLOV technology Vol. 26 No. 3 2024 Currently, the initiative shown by enterprises is aimed at the synthesis of science, technology, innovation using digitalization and automation of design and production processes [10, 11], etc. At the same time, the emphasis of this initiative is on improving the functioning Continuous Acquisition and Life cycle Support (CALS), in particular, on improving Electronic Technical Documentation (ETD), digital twin technology [12, 13] and Quality Management Systems (QMS) [14, 15]. Product Lifecycle Management (PLM) systems are used to manage ETD, provide Integrated Logistics Support (ILS) [16] data and provide access to it at any stage (Fig. 1). Fig. 1. Information support for the PLC stages At the design stage, Computer-Aided Design (CAD) systems and Component Supplier Management (SCM) systems are used. Product Data Management systems (PDM) are used to solve the problems of joint functioning of CAD/CAE components (CAE – Computer Aided Engineering) [17]. In digital production systems, technological preparation of production (TPP) is carried out in the CAD system of TPP, including automated TPP-CAPP (Computer Aided Process Planning) and the development of control programs for Technological Equipment (TE) with CNC-CAM (Computer Aided Manufacturing). Program control is performed through a CNC system based on specialized computers integrated into the maintenance facility. Information obtained during production can be sent to the Enterprise Resource Planning system (ERP). To perform the functions of collecting and processing data on the state of maintenance and Technological Processes (TP), a system of software and hardware complex for Supervisory Control and Data Acquisition (SCADA) is introduced into the Automated Control System (ACS) [18], interacting with the Manufacturing Execution System (MES). According to GOST 57700.37–202, a DT is a system consisting of a digital model of a product and twoway communication with the product and (or) its components. The work of the authors Lu et al. [7] describes a conceptual model of DT consisting of three elements: physical space, digital space and two-way dynamic communication between it; an information model that collects and integrates selected information from existing databases; a methodology describing decision support within the life cycle. To ensure the stability of TP and other production elements that directly affect the quality of the product [19–21], when introducing DT into the life cycle stages, it is necessary to pay attention to improving the complex processing and transmission of accumulated streaming data received from a real product and describing its behavior – the Digital Shadow (DS) [22, 23]. DS helps to concentrate data sets from different subsystems for the purpose of processing and filtering it for use in DT. For example, during machining by cutting, an excessively large array of different data on process parameters enters the digital space from the product, some of which are not directly related to DT.
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