Formation of project management model parameters based on linearization of functional dependencies

Автор: Gvozdev V.E., Bezhaeva O.Ya., Akhmetova D.R., Safina G.R.

Журнал: Онтология проектирования @ontology-of-designing

Рубрика: Методы и технологии принятия решений

Статья в выпуске: 4 (38) т.10, 2020 года.

Бесплатный доступ

At present, the quality of information support for management is becoming a critical factor in the implementation of the provisions of the Industry 4.0 doctrine, due to which the need to improve the theoretical provisions for managing organizational defects in the implementation of projects for creating hardware and software components of the digital eco-environment becomes especially significant. The paper considers a formal model that creates the basis for the formation of a balanced system of the main characteristics of the project, for the case when satisfaction with the properties of the product on the part of the customer and satisfaction with the progress of the project on the part of the contractor are equally important. The basis for the formation of a balanced system of project characteristics is its consideration as a static multi-connected control object. Empirical functional dependencies correspond to direct and cross connections between the input and output parameters of the object. A feature of constructing empirical models is the use of both actual data on budgets and the duration of previously implemented projects, and subjective expert assessments of project participants. The procedure for forming a balanced system of project characteristics is formalized, which makes it possible to automate it. The proposed approach makes it possible to increase the validity of decisions on the feasibility of implementing the project by the forces of the proposed contractor, taking into account the priority of the budget and the duration of the project for the customer.

Еще

Project management, multi-connected object of management, stakeholders, formal model, expert judgment, measurement data

Короткий адрес: https://sciup.org/170178581

IDR: 170178581   |   DOI: 10.18287/2223-9537-2020-10-4-527-539

Статья научная