Recent technological advances in the development of alternative energy sources, including biofuels, for transportation and energy requirements have demonstrated the need for highly skilled engineers and operators in the biotechnological industries. Although operator training simulators (OTS) used in the traditional chemical process industries may be used to train biorefinery operators and engineers, several distinct aspects of bioprocess operations make their direct application limited. The development and deployment of OTSs for use in biotechnological processes is therefore beginning to gain increasing attention. This review paper examines the present status of OTS development and use in biorefineries, including future considerations on how an OTS may be used to improve operator competence, maximise biorefinery operational efficiencies and protect people and the environment. The general premise of an OTS is that model‐based operator training simulators can be used to verifiably enhance the training of industrial operators to run complex biorefineries. Only a few examples of the design and application of OTSs in large‐scale biorefineries have so far been reported. A discussion of the mathematical models used for OTS development is briefly presented, as well as available OTS design frameworks and vendors, including their benefits and drawbacks. The review concludes by looking at possible future directions of OTS development and use in biorefineries and their contribution in facilitating the transition to a bio‐based economy. © 2018 Society of Chemical Industry
Operator training simulators (OTS) are widely used in several industries including chemical processing, oil and gas, medicine, aircraft and nuclear facilities. However, developing a biorefinery OTS is a complex engineering design activity that requires a structured technique. This paper presents a structured methodology that applies design frameworks from other disciplines and a user-centred approach for biorefinery OTS design. These include the definition of end user requirements (operator training needs), and the analysis of these requirements using Quality Function Deployment (QFD). Furthermore, an algorithm for bioprocess optimisation and automatic adjustment of operating parameters is developed for integration into the OTS. This algorithm is based on the Nelder-Mead simplex method for multi-dimensional function minimisation. Identified user requirements were categorized into primary, secondary and tertiary training needs, with increasing levels of detail from primary to tertiary needs. The relationships between identified operator training needs and OTS technical and functional specifications were investigated, and a priority rating assigned to the most important OTS specifications. Identified OTS specifications were evaluated for robustness to ensure that important features were not omitted from the final design.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.