This paper considers identifying critical errors problem in a complex project design with a large number of performers. A multi-stage scheme for extracting semantic data from a large number of documents with interdependent sections is offered. At the first stage, the complexity of the primary analysis of data from these sections is estimated. Then this complexity in view of the identified data from adjacent sections is clarified. Based on this, the final breakdown of a large document data set is formed into clusters with alignment of their complexity. The selection and distribution of clusters between experts are in such a way as to ensure the maximum criterion of analysis efficiency in accordance with the existing time and financial resources. The proposed approach has been applied when developing large-scale transport projects.
Enaleev, A. K., & Tsyganov, V. V. (2019). Examination of design for large and complex network projects. In Procedia CIRP (Vol. 84, pp. 11–15). Elsevier B.V. https://doi.org/10.1016/j.procir.2019.04.286