Document Type
Conference Paper
Publication Date
Winter 10-29-2021
Pages
403-408
Conference Name
2021 Virtual International Annual Conference of the American Society for Engineering Management: Engineering Management and the New Normal, 27th-30th October 2021
Abstract
Driven by a growing requirement during the 21st century for the integration of rigorous statistical analyses in engineering research, there has been a movement within the statistics and quality communities to evolve a unified statistical engineering body of knowledge (Hoerl & Snee, 2010). Systems Statistical Engineering research seeks to integrate causal Bayesian hierarchical modeling (Pearl, 2009) and cybernetic control theory within Beer's Viable System Model (S Beer, 1972; Stafford Beer, 1979, 1985) and the Complex Systems Governance framework (Keating, 2014; Keating & Katina, 2015, 2016) to produce multivariate systemic models for robust dynamic systems mission performance. (Cotter & Quigley, 2018) set forth the Bayesian systemic hierarchical constraint propagation theoretical basis for modeling the amplification and attenuation effects of environmental constraints propagated into systemic variability and variety. In their theoretical development, they simplified the analysis to only deterministic constraints, which models only the effect of statistical risks of failure. Imprecision and uncertainty in the assessment of environmental constraints will induce additional variance components in systemic variability and variety. To make causal Bayesian hierarchical modeling more capable of capturing and representing the imprecise and uncertain nature of environments, we must incorporate rough or fuzzy functions and boundaries to model imprecision and grey boundaries to model uncertainty in constraint propagation at each system level to measure the overall impact on the organization variability and variety. This paper sets forth a proposed research method to incorporate rough, fuzzy, and Grey set theories into Systems Statistical Engineering causal Bayesian hierarchical constraints modeling.
Original Publication Citation
Fakhravar, Hengameh and Tahami, Hesamoddin. Systems Statistical Engineering – Hierarchical Fuzzy Constraint Propagation. 2021 Virtual International Annual Conference of the American Society for Engineering Management: Engineering Management and the New Normal, 27th-30th October 2021.
Repository Citation
Fakhravar, Hengameh and Tahami, Hesamoddin, "Systems Statistical Engineering – Hierarchical Fuzzy Constraint Propagation" (2021). Engineering Management & Systems Engineering Faculty Publications. 85.
https://digitalcommons.odu.edu/emse_fac_pubs/85
Included in
Industrial Engineering Commons, Other Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Engineering Commons
Comments
Copyright 2021 as indicated. Reprinted with permission of the American Society for Engineering Management. International Annual Conference. All rights reserved.