Investigating Spatiotemporal Variability of Water, Energy, and Carbon Flows: A Probabilistic Fuzzy Synthetic Evaluation Framework for Higher Education Institutions

Higher education institutions (HEIs) consume significant energy and water and contribute to greenhouse gas (GHG) emissions. HEIs are under pressure internally and externally to improve their overall performance on reducing GHG emissions within their boundaries. It is necessary to identify critical areas of high GHG emissions within a campus to help find solutions to improve the overall sustainability performance of the campus. An integrated probabilistic-fuzzy framework is developed to help universities address the uncertainty associated with the reporting of water, energy, and carbon (WEC) flows within a campus. The probabilistic assessment using Monte Carlo Simulations effectively addressed the aleatory uncertainties, due to the randomness in the variations of the recorded WEC usages, while the fuzzy synthetic evaluation addressed the epistemic uncertainties, due to vagueness in the linguistic variables associated with WEC benchmarks. The developed framework is applied to operational, academic, and residential buildings at the University of British Columbia (Okanagan Campus). Three scenarios are analyzed, allocating the partial preference to water, or energy, or carbon. Furthermore, nine temporal seasons are generated to assess the variability, due to occupancy and climate changes. Finally, the aggregation is completed for the assessed buildings. The study reveals that climatic and type of buildings significantly affect the overall performance of a university. This study will help the sustainability centers and divisions in HEIs assess the spatiotemporal variability of WEC flows and effectively address the uncertainties to cover a wide range of human judgment.

A fuzzy synthetic evaluation of vulnerabilities affecting supply chain resilience of industrialized construction in Hong Kong

PurposeDemands for Industrialized Construction (IC) have intensified with growing construction industry imperatives to (A) boost performance; (B) reduce reliance on “in-situ and on-site” operations; and (C) strengthen supply chain resilience (SCR) not just for survival but also to fulfill obligations to clients in the coronavirus disease 2019–induced (COVID-19–induced) “new normal”. In addressing these imperatives, this paper targets more effective leveraging of latent efficiencies of off-site-manufacture, based on findings from a Hong Kong (HK)–based study on assessing and improving SCR in IC in a high-density city.Design/methodology/approachStarting with the identification of critical supply chain vulnerabilities (CSCVs), this study developed a multilevel–multicriteria mathematical model to evaluate the vulnerability levels of IC supply chains (SCs) in HK based on an in-depth questionnaire survey followed by experts' inputs and analyzing them using fuzzy synthetic evaluation (FSE).FindingsThe overall vulnerability index indicates that IC in HK is substantially vulnerable to disruptions, while production-based vulnerabilities have the highest impact. Top management attention is needed to address these CSCVs in IC in HK.Originality/valueTo the authors' knowledge, this is the first structured evaluation model that measures the vulnerability level of IC, providing useful insights to industry stakeholders for well-informed decision-making in achieving resilient, sustainable and performance-enhanced SCs.

A quality analysis method for three-dimensional model in aircraft structural parts design

To analyze the quality of three-dimensional (3D) model for aircraft structural parts designed by model-based definition (MBD) technology, an approach combining analytic hierarchy process (AHP), hesitant fuzzy linguistic term set (HFLTS), and fuzzy synthetic evaluation is proposed. According to all levels of quality standards and part specification-tree elements, a quality assessment index system is constructed from four sub-models of parts 3D model: design model, process model, tooling model, and test model. In addition, the weight of each index is calculated using the AHP. Then the assessment model is established by using a configurable index system model, HFLTS, fuzzy synthetic evaluation, and assigning uniformly and quantitatively the index system through quality grade division rules of indexes and triangular fuzzy numbers. Finally, a case application is used to illustrate the proposed method. The application of this method can make the quality analysis of parts 3D model more effective, accurate, and efficient. This paper can not only help enterprises identify higher-weight and error-prone design factors, but also guide designers in modeling.