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The purpose of this paper is to present an integrated framework for performance evaluation and analysis of human resource (HR) with respect to the factors of health, safety, environment and ergonomics (HSEE) management system, and also the criteria of European federation for quality management (EFQM) as one of the well-known business excellence models.

In this study, an intelligent algorithm based on adaptive neuro-fuzzy inference system (ANFIS) along with fuzzy data envelopment analysis (FDEA) are developed and employed to assess the performance of the company. Furthermore, the impact of the factors on the company’s performance as well as their strengths and weaknesses are identified by conducting a sensitivity analysis on the results. Similarly, a design of experiment is performed to prioritize the factors in the order of importance.

The results show that EFQM model has a far greater impact upon the company’s performance than HSEE management system. According to the obtained results, it can be argued that integration of HSEE and EFQM leads to the performance improvement in the company.

In current study, the required data for executing the proposed framework are collected via valid questionnaires which are filled in by the staff of an aviation industry located in Tehran, Iran.

Managing HR performance results in improving usability, maintainability and reliability and finally in a significant reduction in the commercial aviation accident rate. Also, study of factors affecting HR performance authorities participate in developing systems in order to help operators better manage human error. This paper for the first time presents an intelligent framework based on ANFIS, FDEA and statistical tests for HR performance assessment and analysis with the ability of handling uncertainty and vagueness existing in real world environment.

A growing body of evidence points to the influence of location and allocation decisions on the structure of healthcare networks. The authors introduced a three-level hierarchical facility location model to minimize travel time in the healthcare system under uncertainty.

Most healthcare networks are hierarchical and, as a result, the linkage between their levels makes it difficult to specify the location of the facilities. In this article, the authors present a hybrid approach according to data envelopment analysis and robust programming to design a healthcare network. In the first phase, the efficiency of each potential location is calculated based on the non-radial range-adjusted measure considering desirable and undesirable outputs based on a number of criteria such as the target area's population, proximity to earthquake faults, quality of urban life, urban decrepitude, etc. The locations deemed suitable are then used as candidate locations in the mathematical model. In the second phase, based on the proposed robust optimization model, called light robustness, the location and allocation decisions are adopted.

The developed model is evaluated using an actual-world case study in District 1 of Tehran, Iran and relevant results and different sensitivity analyses were presented as well. When the percentage of referral parameters changes, the value of the robust model's objective function increases.

The contributions of this article are listed as follows: Considering desirable and undesirable criteria to selecting candidate locations, providing a robust programming model for building a service network and applying the developed model to an actual-world case study.

The purpose of this paper is to develop an integrated management system that addresses the shortcoming revealed in the previous approaches of the IMS in literature.

This paper is based on the methodology of literature review analysis, proposition of an approach based on theory by the standards’ cross-references and on practice by the analysis of the real work and the use of the System Modeling Language (SYSML), the computer tool for the engineering system modeling.

An integration approach based on theory and practice in the automotive sector, integrating IATF 16949:2016, ISO 14001:2015, ISO 45001:DIS and some aspects of ISO 26000 is proposed. The proposed approach initiates the use of the SYSML in the IMS development. The model is intended to societies that seek to be sustainable and responsible toward environment and community. The link of the IMS model created with the European Foundation for Quality Management excellence model highlights the fact that the factors of excellence, especially the enablers, are covered by the requirements of the IMS.

This paper is the first approach of IMS that includes ISO 45001 (draft), uses the SYSML and sheds light on the link of excellence and IMS. The paper is the first detailed approach of IMS that addressed car manufacturer.