When selecting technology options for additive manufacturing, it is important to be guided by a list of basic requirements for manufactured parts, powder material features, and the range of equipment specifications. To develop the most effective solution, pilot testing of the technology will be required to determine the preferred process modes that ensure the required quality, cost, and manufacturing time. Accordingly, for such industries, it is important to develop a model that describes the stages of additive manufacturing. In this regard, this paper is devoted to considering the issues of optimization, planning, and management of additive manufacturing technology based on multiple criteria for selecting the most effective technology that involves optimal loading of production facilities. The proposed model introduces indicators that characterize adaptation and allow arguing the practical benefits of using 3D printing technologies. Comparison of process routes by these indicators allows choosing a specific manufacturing route. Having selected the manufacturing option, it is possible to calculate the most efficient placement of products on platforms, as well as to develop a suitable sequence of execution of the main manufacturing operations in order to minimize costs and time expenditures. It was found that the use of the proposed model allows to reduce the manufacturing time of a batch of products by approximately 2.5%. Thus, the proposed model can be useful in additive manufacturing to reduce downtime of installations and speed up the release of products.

Keywords: production organization, productivity assessment, equipment reconfiguration, machine loading, automation, multi-product production

The work has formulated a justification for the necessity to perform works aimed at solving the tasks of providing technological preparation of composite structures production by means of automation based on the application of modern information and computing systems. The characteristics and key aspects that determine the efficiency of automation at the stage of technological preparation of production are highlighted. Justification of the relationship between the processes determining the process formation and its efficiency is given

Keywords: automation, technological process, technological preparation of production, composite materials, composite designs, neural networks, modeling, process parameters

The basic principles of methodological support for the process of automation of technological preparation of production of products are formulated from the position of identifying the relationship of technological parameters of processing with the target properties of the product. The architecture of the neural network model is proposed and the basic principles of its construction are formulated.

Keywords: automation, technological process, technological preparation of production, neural networks, modeling, technological parameters, target properties