Salman Nazir

Advanced Applications in Process Control and Training Needs of Field and Control Room Operators

OCCUPATIONAL APPLICATIONS Operators play a vital role in production and safety in industrial processes. Since the introduction of advanced control techniques, such as model predictive control and real-time optimization, operators’ acquisition of adequate mental models to develop complex cause-and-effect relationship explaining plant behavior has been increasingly challenged. Additionally, distinct challenges have arisen with respect to crew coordination between control room and field operators to orchestrate a coordinated flow of actions to assess situations or choose a course of action. Based on an analysis of training needs, it is argued that traditional training practice, such as the use of operator training simulators, could be advanced by using current training environments, such as virtual reality training simulators. This would allow using modern training technology and its advancements in parallel to the advancements of control techniques to support production and safety at its best. TECHNICAL ABSTRACT Background: Extensive integration of various modern methods in the process industry has changed the tasks of industrial operators. The integration of advanced technology and control algorithms lead to new challenges faced by control room and field operators, from both technical and crew-coordination complexity perspectives. From a technical perspective, couplings, dynamic effects, non-transparency, conflicting goals, comprehension of model predictive control, and real-time optimization challenge the development of an accurate mental model. From a crew-coordination complexity perspective, control room operators and field operators face the challenge to orchestrate their individual actions into a coordination flow of actions to assess a situation and solve problems. Purpose: The purpose of this article is to highlight the cognitive and teamwork requirements of operators and to note the limitations of current training practices compared to the training objectives that need to be achieved individually and as a team. Methods: Evidence is presented from instance-based learning theory and theories addressing the acquisition of mental models, instances, and skills for crew-coordination complexity; this is used to suggest that current training practices match only a subset of the challenging training objectives that are essential to use technology efficiently and safely. Results: Findings from the cognitive training need analysis are linked to training objectives and training methods based on the learning theories presented. Additionally, arguments for using different training environments (operator training simulators, virtual reality training simulators) to achieve the training objectives in an optimal way are presented. Conclusions: It is concluded that advancements in the applications of process control techniques call for a new mindset in the training of operators. Advanced training methods and environments can be one way of helping the operator to improve performance reduce errors and enhance safety.

Testing and analyzing different training methods for industrial operators: an experimental approach

1. Abstract Process industry is known for its complexity and sensitivity with critical procedures saturated with demanding human-machine interfaces that may induce human errors thus resulting in abnormal situations. Abnormal situations may lead to near misses and even to severe accidents, which can result in loss of production and even in casualties and fatalities. This paper aims at abridging the gap between the highly demanding human machine interfaces and the training methods employed in the process industry by experimentally analyzing the effectiveness of distinct training methods in a virtually simulated abnormal situation. The performance of operators is measured by means of suitable Key Performance Indicators (KPIs) applied to the specific case study. In particular, we analyze experimentally two distinct training methods based respectively on a Power Point presentation and a 3D virtual environment. The positive outcomes of this approach consist in increasing the reliability, cost effectiveness, environmental friendliness, and safety of the process. This work is the result of the interaction between chemical engineers and experimental psychologists, which may open new horizons to scientific research.

How a plant simulator can improve industrial safety

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.

Automation in Process Industry: Cure or Curse? How can Training Improve Operator’s Performance

Abstract Automation in the process industry has seen its implication and implementation since 1960’s. However, during last decades the “trend” of integrating advanced and sophisticated process control techniques like process optimization, soft sensors, MPC, RTO has significantly increased. The reasons that can be attributed to the increase in automation are mainly the implementation cost respect to expected revenues and the wide range of alternatives and suppliers. Unfortunately, the inclusion of automation coupled to either new plants/processes or process retrofitting and revamping neglected often the operator’s characteristics that can be summarized with the human factor term. This paper provides an insight to the extensive use of automation and the associated challenges that an industrial operator faces because of information overload, human machine interface, and automation complexity. The forgotten part, i.e. the human (operator) element, is emphasized with respect to the operations in control room and in the field. The impact of complexity of automation on the nature of operator error is discussed for both normal operating conditions and abnormal situations. A case study reflecting automation failure combined with human error(s) is presented. Finally, a Hierarchal Training Syllabus (HTS) is proposed by using a so called Plant Simulator. The features and relevant benefits of HTS are also outlined.

Critical incidents during dynamic positioning: operators’ situation awareness and decision-making in maritime operations

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.

Virtual and Augmented Reality as Viable Tools to Train Industrial Operators

Abstract The sensitivity and significance of operator training increased profoundly with the increase in automation of industrial plants. The paper proposes and discusses the use of Virtual Reality and Augmented Virtual Reality to train industrial operators. A detailed and immersive 3D model of the plant allows the operators understanding the details of equipment and operating conditions. Both the dynamic behavior and the control strategies of the process can be reproduced with a 3D immersive virtual environment by implementing and coupling a dynamic process simulator and a dynamic real-time accident simulator. The AVR feature enhances the VR by adding further information and analysis that result in better understanding of operators that work either in control room or in the field. The proposed training methodology allows achieving significant improvements in reliability, cost effectiveness, environmental friendliness, and process safety.

Distributed Situation Awareness in pilotage operations: Implications and Challenges

Pilotage is considered as the most critical leg of navigation and a complex operation in maritime domain. In this paper, we argue that Distributed Situation Awareness (DSA) is an important construct in pilotage as the information required to carry out operations is distributed between agents and artefacts. We identify the central themes from the theory of DSA which are useful in describing modern day complex socio‐ technical systems. Further, based on the central themes, we propose guidelines for evaluating bridge teams involved in pilotage operations. http://www.transnav.eu the International Journal on Marine Navigation and Safety of Sea Transportation Volume 11

Towards Holistic Decision Support Systems: Including Human and Organizational Performances in the Loop

Abstract A fundamental challenge and opportunity for risk and operational managers to improve significantly their activity is to adopt a holistic approach to decision-making by grounding their decisions on the effective knowledge, experience and capabilities of operators and their organization. The paper explains why accounting for human and organizational factors is fundamental to strengthen decisions and why doing it in an experimental fashion is the way forward. Further, it is explained that leveraging on human and organizational factors, instead of appealing mainly to the technological ones, opens opportunities to improving decisions and save resources. The manuscript presents an example stemming from a use case developed with one major company of the Oil & Gas sector.

Computer Supported Collaborative Learning as an Intervention for Maritime Education and Training

Maritime domain is one of the most high-risk industry and it predominantly employs simulator training as a means to train the prospective operators. Maritime instructors need to train students who will become future sharp end operators and interact in highly safety critical environment. One of the goals of maritime education is therefore to create relevant learning activities among the trainees which will help them not only to learn the highly contextualized/situated knowledge of work settings but who are able to work together in team demonstrating qualities such as critical thinking and leadership. Educational frameworks that take into account the unique nature of maritime domain are therefore needed to be identified. Sociocultural perspectives suggests that learning is situated in communities of practice. In order to study how people learn in practice, it is necessary to study how individuals interact with other members and the different mediational tools that are at their disposal for engagement in specific activities. In this exploratory study, we analyze the maritime simulator training through the lens of sociocultural perspective and propose computer supported collaborative learning as an intervention for maritime education and training. We describe the salient characteristics of collaborative learning and its relevance for maritime education and computer supported training. An observation study was carried out at a maritime simulator training facility. The aim is to better understand/explore the complexities of maritime simulator training and reflect on how the collaborative learning approach can be better used to support the connections of simulated learning activities and its relevance in real life maritime operations.

Towards Automated Performance Assessment for Maritime Navigation

This paper presents the outcome of a pre‐project that resulted in an initial version (prototype) of an automated assessment algorithm for a specific maritime operation. The prototype is based on identified control requirements that human operators must meet to conduct safe navigation. Current assessment methods of navigation in simulators involve subject matter experts, whose evaluations unfortunately have some limitations related to reproducibility and consistency. Automated assessment algorithms may address these limitations. For a prototype, our algorithm had a large correlation with evaluations performed by subject matter experts in assessment of navigation routes. The results indicate that further research in automated assessment of maritime navigation has merit. The algorithm can be a stepping stone in developing a consistent, unbiased, and transparent assessment module for evaluating maritime navigation performance. http://www.transnav.eu the International Journal on Marine Navigation and Safety of Sea Transportation Volume 11