Please use this identifier to cite or link to this item:
http://elar.urfu.ru/handle/10995/102523
Title: | Improve business process efficiency by value engineering |
Authors: | Mineeva, T. A. Kuznetcova, N. A. Norkina, O. S. Popova, E. V. |
Issue Date: | 2020 |
Publisher: | IOP Publishing Ltd |
Citation: | Improve business process efficiency by value engineering / T. A. Mineeva, N. A. Kuznetcova, O. S. Norkina, et al. — DOI 10.1088/1757-899X/971/5/052015 // IOP Conference Series: Materials Science and Engineering. — 2020. — Vol. 971. — Iss. 5. — 052015. |
Abstract: | This article is devoted to the problems of business processes optimization by value engineering (FCA) method. The business processes analysis is particularly relevant in modern conditions. The purpose the investigation is to adapt the value engineering to the business process. The FCA is a universal and highly efficient method of parameters optimization and other structural, technological, organizational, economic characteristics of a product, work or services. The hypothesis of the applying a value engineering to a business process possibility is considered. The article discusses FCA tools as an example of a metal rolling business delivery process. A business process model is being constructed as an object structural element model. The functions decomposition is carried out. Functions are classified into basic and auxiliary on the basis of the level. In the article the significance and functional costs are determined. A functional-cost diagram is constructed to identify the functions with the most deviations needing improvement. The FCA stages are accompanied by graphical illustrations, tables that illustrate the logic of applying the method to the business process. As a result, an optimal business-process concept with the lowest cost is being developed. © Published under licence by IOP Publishing Ltd. |
URI: | http://elar.urfu.ru/handle/10995/102523 |
Access: | info:eu-repo/semantics/openAccess |
SCOPUS ID: | 85098068082 |
WOS ID: | 000646359100318 |
PURE ID: | 975a38aa-4ba9-4b28-b2cd-27780083be69 20412196 |
ISSN: | 17578981 |
DOI: | 10.1088/1757-899X/971/5/052015 |
Appears in Collections: | Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC |
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2-s2.0-85098068082.pdf | 520,72 kB | Adobe PDF | View/Open |
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