In this study, an integrated approach is presented for analyzing the impact of resilience engineering and ergonomics factors in aerospace supply chain using data envelopment analysis (DEA). The proposed approach selects the preferred supplier by considering traditional supply chain factors as well as resilience engineering and ergonomics factors. Also, the relevant performance efficiency of each decision making unit is calculated. The case study of this paper is the supply chain of real commercial airlines. Thus, the aerospace standards as well as resilience and ergonomics factors are considered to be modeled by the mathematical programming approach. 22 suppliers are evaluated by analyzing inputs and outputs through data envelopment analysis, and each supplier is considered as a decision making unit (DMU). In this study, the most effective factors are identified as “reliability”, “Human resource management”, “supplier’s delay” and “availability”. Also, “lead time” shows the highest potential for improvement. This study helps decision makers identify the weaknesses of their supply chain management to establish a performance improvement plan in aerospace industry.

Construction sites are accident-prone locations and therefore safety management plays an im-portant role in these workplaces. This study presents an adaptive algorithm for performance as-sessment of project management with respect to resilience engineering and job security in a large construction site. The required data are collected using questionnaires in a large construction site. The presented algorithm is composed of radial basis function (RBF), artificial neural networks multi-layer perceptron (ANN-MLP), and statistical tests. The results indicate that preparedness, fault-tolerance, and flexibility are the most effective factors on overall efficiency. Moreover, job security and resilience engineering have similar statistical impacts on overall system efficiency. The results are verified and validated by the proposed algorithm.