This research evaluates IRCA registered auditors' perspectives of the added value of ISO 9001:2015 to the organizations that adopt it and are certified accordingly, bringing a more independent perspective than previous studies based on quality managers or consultants' views. Supported by a worldwide survey among IRCA registered auditors and the adoption of a Covariance based-Structural Equation Modelling (CB-SEM) approach the results point out that the auditors' judgment regarding the ISO 9001:2015 value is influenced by their perceptions (regarding the document) and experience (auditing). The research results highlight the importance of selecting auditors with the appropriate ISO 9001:2015 knowledge and experience to assess ISO 9001:2015 Quality Management Systems (QMSs) within the certification process, therefore, contributing to the business and processes performance improvement and sustainable outcomes.

Human-Robot Collaboration (HRC) systems are often implemented seeking for reducing risk of Work-related Musculoskeletal Disorders (WMSD) development and increasing productivity. The challenge is to successfully implement an industrial HRC to manage those factors, considering that non-linear behaviors of complex systems can produce counterintuitive effects. Therefore, the aim of this study was to design a decision-making framework considering the key ergonomic methods and using a computational model for simulations. It considered the main systemic influences when implementing a collaborative robot (cobot) into a production system and simulated scenarios of productivity and WMSD risk. In order to verify whether the computational model for simulating scenarios would be useful in the framework, a case study in a manual assembly workstation was conducted. The results show that both cycle time and WMSD risk depend on the Level of Collaboration (LoC). The proposed framework helps deciding which cobot to implement in a context of industrial assembly process. System dynamics were used to understand the actual behavior of all factors and to predict scenarios. Finally, the framework presented a clear roadmap for the future development of an industrial HRC system, drastically reducing risk management in decision-making.

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