The usage of the system by large enterprises has some features; first of all it concerns the installation of the system to the enterprise network to keep the advantages of cloud system. As a rule we can provide permanent licenses and one-year support. The key features of the system usage by large enterprises are:
1. Solved problems relate to the managing technology for the processes of small-series production of machine-building and / or instrument-making enterprises controlled by orders. Such enterprises are characterized by high variability of external orders flow and of production environment conditions. It determines the complexity of operative management for production and enterprise.
2. The originality of the proposed technology is a creation of a digital twin that accurately indicates the real state of production and ensures both operative management of production and the definition of strategy and tactics for competitive growth. At the same time, new functions are the self-learning of the digital twin, the high adaptability of the production system to the flow of plan tasks, both for the production preparation stage and for the production stage, at workplaces in real time along the whole manufacturing route – from the purchase of components to the warehouse of the finished goods.
3. The expected positive effect of a new control technology with a digital twin displays in improvement of timely execution of the received production orders (to 100%) and in multiple
reduction of production cycles time (3-10 times), which provides higher competitive position for the enterprise. In addition, the new technology allows to calculate quickly and to determine expertly the effect of technological composition and of resources utilization rate on lead time for current and new production orders, to take this into account for commercial negotiations and for discussion of plans for new products development.
4. A new technology of digital twin control is based on adaptive scheduling algorithms, cyber physical systems for gathering and exchanging of operation information about the production state based on industrial Internet of things, as well as algorithms of artificial intelligence for system self-learning. At the same time, the processing of large data amounts and of actual production figures is used for statistical management of quality of referenced data, labor resources, technological equipment configuration and manufacturing
product range. It can be used also for expert reports about the possible interdependences of production and business indicators.