Open AccessProcess model as a basis for intellectual control in real time by the processes of the production enterprise
Author(s) -
Olha Novikova,
A. Kotsyubinsky,
Nadezhda Yudina,
С. А. Лившиц,
T. Dunaeva
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/618/1/012009
Subject(s) - enterprise integration , computer science , enterprise information system , enterprise life cycle , enterprise systems engineering , process management , integrated enterprise modeling , enterprise software , business process , enterprise data management , knowledge management , enterprise architecture , process (computing) , enterprise modelling , enterprise planning system , business , work in process , engineering , operations management , architecture , art , visual arts , operating system
Modern enterprises are working in a complex and volatile business environment. In order to adapt to this situation, enterprises are trying to realize horizontal and vertical integration of the enterprise processes (managerial and production processes) leading to the creation of a real-time enterprise. In such an enterprise, integral data is used with different time horizons, starting from the millisecond, generated by automatic devices, and ending with daily, generated business applications. However, these integral data are rarely used for operational management of time by enterprise processes of the enterprise. To overcome this limitation, a process model for identifying and assimilating knowledge is proposed that encompasses four steps: (i) analyzing and (re-designing the enterprise’s controlled processes, (ii) developing a data model and enterprise data flow diagrams for automatic devices and business applications, (iii) identification of knowledge based on the discovery of knowledge in working with databases, (iv) continuous monitoring and management of enterprise processes, using complex event processing.