The use of simulators in maritime education and training is an essential component for developing seafarer competencies. Emerging immersive technologies, such as virtual reality (VR), augmented reality (AR) and mixed reality (MR) have created new and differing possibilities for maritime simulations and simulators. The increasing advancements and technical readiness of these systems have paved the way for a new generation and category of simulators and simulation-based experiences for professional education, training, and operations, which are relatively cheaper, more immersive, compact, and accessible in comparison to traditional configurations. Although the concept of utilizing VR, AR, and MR head-mounted display technologies for professional training and operations is not new, their recent developments and proliferation now allow for practical implementation and real-world application. Particularly, the adoption and integration of these technologies into the education, training, and operations of maritime industries provide new possibilities and paradigms to support operators and operations both on land and at sea. The purpose of this paper is to discuss the concepts of VR, AR, and MR applications specifically for maritime education, training and operations, including the potential benefits, drawbacks, and limitations of these systems.

An empirical model has been developed for the successful prediction of the melt index (MI) during grade change operations in a high density polyethylene plant. To efficiently capture the nonlinearity and grade-changing characteristics of the polymerization process, the plant operation data is treated with the recursive partial least square (RPLS) scheme combined with model output bias updating. In this work two different schemes have been proposed. The first scheme makes use of an arbitrary threshold value which selects one of the two updating methods according to the process requirement so as to minimize the root mean square error (RMSE). In the second scheme, the number of RPLS updating runs is minimized to make the soft sensor time efficient, while reducing, maintaining or normally increasing the RMSE obtained from first scheme up to some extent. These schemes are compared with other techniques to exhibit their superiority.

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Keeping the systems and processes safe is of paramount importance for all industries around the world. Process industry is a socio-complex system constituted of dynamic chemical processes, sophisticated computer algorithms, modern human machine interfaces, and teams of operators working at different locations. The decisions of the operators directly or indirectly influence the safety and production of chemical processes. The article presents and discusses a solution for immersive training of industrial operators that allows experiencing the multifaceted scenarios of (real) plant operations. This tool, called Plant Simulator (PS), combines a process simulator and an accident simulator to simulate dynamically both normal and abnormal/accident scenarios. These simulators are the engines that work behind the curtains of an Immersive Virtual Environment and make possible the realism of the simulated operations in the plant. The article explains the features of PS and discusses two case studies that show the potential improvements achievable in processes safety. 9 fatalities and 122 casualties; demolished life in 100-km Marcal river. Neptune Technologies and Bioresources. Sherbrooke, Quebec, Canada (2012); a huge blast followed by smaller ones.2 fatalities and 17 casualties.

Objective In this review, we investigate the relationship between agent transparency, Situation Awareness, mental workload, and operator performance for safety critical domains. Background The advancement of highly sophisticated automation across safety critical domains poses a challenge for effective human oversight. Automation transparency is a design principle that could support humans by making the automation’s inner workings observable (i.e., “seeing-into”). However, experimental support for this has not been systematically documented to date. Method Based on the PRISMA method, a broad and systematic search of the literature was performed focusing on identifying empirical research investigating the effect of transparency on central Human Factors variables. Results Our final sample consisted of 17 experimental studies that investigated transparency in a controlled setting. The studies typically employed three human-automation interaction types: responding to agent-generated proposals, supervisory control of agents, and monitoring only. There is an overall trend in the data pointing towards a beneficial effect of transparency. However, the data reveals variations in Situation Awareness, mental workload, and operator performance for specific tasks, agent-types, and level of integration of transparency information in primary task displays. Conclusion Our data suggests a promising effect of automation transparency on Situation Awareness and operator performance, without the cost of added mental workload, for instances where humans respond to agent-generated proposals and where humans have a supervisory role. Application Strategies to improve human performance when interacting with intelligent agents should focus on allowing humans to see into its information processing stages, considering the integration of information in existing Human Machine Interface solutions.

The maritime industry is increasingly becoming dependent on dynamic positioning (DP) systems for automated vessel station keeping. This study aimed to reveal characteristics of DP operators' situation awareness (SA) and decision-making during critical incidents. Information from a total of 24 critical incidents was collected from 13 experienced DP using the critical decision method. The results indicate that in 10 incidents, the DP operators were unable to identify the base events (e.g. did not form level 1 SA) but were able to identify the problem (e.g. understand the situation; e.g. form level 2 SA). These findings indicate that the establishment of high-level SA may happen even without low-level SA. This study contributes to an improved understanding of the development of SA and the recovery of critical incidents during complex maritime operations.

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