Skip to main content
SpringerLink
Log in

Operator training simulators in virtual reality environment for process operators: a review

  • S.I. : Virtual Reality, Augmented Reality and Commerce
  • Published:
Virtual Reality Aims and scope Submit manuscript

Abstract

Given the factors such as safety, profitability, and environmental concerns at stake, operator training is an everlasting and vital process in the process industry. An inevitable need for skilled operators in the chemical industry leads to search for novel and effective training methodologies. Consequently, dynamic simulation techniques have been considered as a tool to educate and train inexperienced personnel as expected by the industry. Traditional training methodologies are hardly sufficient to instruct the operators for seldom-occurring perilous situations. Conventional operator training simulators (OTS) are generally effective, but they lack to give operators the actual feel of the scenarios. Training effectiveness can be enhanced by providing operators with a sense of realism. Therefore, integration of OTS with virtual reality (VR-OTS) certainly comes out to be an alternative. VR-OTS can replicate emergency conditions, accidents, and investigate safety protocols. In this work, we discuss the need for virtual reality (VR) in OTS, merits of VR-OTS, and the role of training assessment methods. Contributions of OTS Authors’ in process industry from year 2000 to mid-2017 are reviewed and discussed extensively. The review shows that VR-OTS provides tangible benefits over its conventional counterparts in terms of improved safety of plant, increased productivity, and environmental protection. Finally, this paper outlines future scopes that the current researcher may consider to focus for the increased and improved VR-OTS usage.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Aggarwal R, Black SA, Hance JR, Darzi A, Cheshire NJ (2006) Virtual reality simulation training can improve inexperienced surgeons’ endovascular skills. Eur J Vasc Endovasc 31:588–593

    Article  Google Scholar 

  • Ahmad Z, Patle DS, Rangaiah GP (2016) Operator training simulator for biodiesel synthesis from waste cooking oil. Process Saf Environ 99:55–68

    Article  Google Scholar 

  • Antonovsky A, Pollock C, Straker L (2014) Identification of the human factors contributing to maintenance failures in a petroleum operation. Hum Factors 56:306–321

    Article  Google Scholar 

  • Ayral T, Jonge PD (2016) Operator training simulators for brownfield process units offer many benefits. Hydrocarbon Process 92:45–47

    Google Scholar 

  • Bell JT, Fogler HS (1996) The status and prospects of virtual reality in chemical engineering. Ann Arbor 1001:48109-2136

    Google Scholar 

  • Bell JT, Fogler HS (2004) The application of virtual reality to (chemical engineering) education. In: Proceedings of the IEEE virtual reality 2004, Chicago, IL, USA, 27–31 March 2004, pp 217–218

  • Berg LP, Vance JM (2017) Industry use of virtual reality in product design and manufacturing: a survey. Virtual Real 21:1–17

    Article  Google Scholar 

  • Brambilla S, Manca D (2009) Dynamic process and accident simulations as tools to prevent industrial accidents. Chem Prod Process Model 4:1–15

    Google Scholar 

  • Brambilla S, Manca D (2011) Recommended features of an industrial accident simulator for the training of operators. J Loss Prevent Proc 24:344–355

    Article  Google Scholar 

  • Cheng-jun C, Feng-shi L, Niu L (2010) Research on chemical process simulation system using distributed virtual reality. In: Third international conference on information and computing, Wuxi, Jiang Su, pp 133–136. https://doi.org/10.1109/icic.2010.127

  • Cibulka J, Komulainen TMK, Mirtaheri PM, Nazir S, Manca D (2016) Virtual reality simulators in the process industry. A review of existing systems and the way towards ETS. In: O’Conner L (ed) 2016 9th EUROSIM congress on modelling and simulation Oulu, Finland, 12–16 September 2016. IEEE, pp 458–464

  • Colombo S, Manca D, Brambilla S, Totaro R, Galvagni R (2011) Towards the automatic measurement of human performance in virtual environments for industrial safety. In: ASME 2011 world conference on innovative virtual reality (WINVR 2011), pp 1–10

  • Colombo S, Manca D, Nazir S (2013) Virtual reality as effective tool for training and decision-making: preliminary results of experiments performed with a plant simulator. In: Proceedings of SPE European HSE conference and exhibition health, safety, environment and social responsibility, pp 405–411

  • Colombo S, Nazir S, Manca D (2014) Immersive virtual reality for training and decision making: preliminary results of experiments performed with a plant simulator. SPE Econ Manag 6:165–172

    Article  Google Scholar 

  • Cox RK, Smith JF, Dimitratos Y (2006) Can simulation technology enable a paradigm shift in process control? Modeling for the rest of us. Comput Chem Eng 30:1542–1552

    Article  Google Scholar 

  • Cozens P, Waters J, Neale R (2002) A virtual reality approach to personal safety and the design of built environment facilities. In: Proceedings of the 18th ARCOM annual conference. Association of Researchers in Construction Management, pp 461–473

  • Dalgarno B, Lee MJ (2010) What are the learning affordances of 3-D virtual environments? Brit J Educ Technol 41:10–32

    Article  Google Scholar 

  • Fiske T, Hill D (2010) 3D simulation brings immersive dimension to operator training, ARC INSIGHT. https://arcadvisorygroup-public.sharepoint.com/myarc/myreports/. Accessed 14 April 2017

  • Formosa NJ, Morrison BW, Hill G, Stone D (2018) Testing the efficacy of a virtual reality-based simulation in enhancing users’ knowledge, attitudes, and empathy relating to psychosis. Aust J Psychol 70:57–65

    Article  Google Scholar 

  • Steptoe W, Oyekoya O, Murgia A, Wolff R, Rae J, Guimaraes E, et al. (2009) Eye tracking for avatar eye gaze control during object-focused multiparty interaction in immersive collaborative virtual environments. In: IEEE virtual reality conference, Lafayette, LA, 2009, pp 83–90. https://doi.org/10.1109/vr.2009.4811003

  • Haller M, Holm R, Volkert J, Wagner RA (1999) VR based safety training in a petroleum refinery. In: The 20th annual conference of the European association of CG, Eurographics, Milano, Italy

  • Hill KJ, Howarth PA (2000) Habituation to the side effects of immersion in a virtual environment. Displays 21(1):25–30

    Article  Google Scholar 

  • Howarth PA, Costello PJ (1997) The occurrence of virtual simulation sickness symptoms when an HMD was used as a personal viewing system. Displays 18(2):107–116

    Article  Google Scholar 

  • Kanawattanachai P, Yoo Y (2007) The impact of knowledge coordination on virtual team performance over time. MIS Q 31:783–808

    Article  Google Scholar 

  • Kang S, Kang S (2018) The study on the application of virtual reality in adapted physical education. Clust Comput. https://doi.org/10.1007/s10586-018-2254-4

    Google Scholar 

  • Kluge A (2014) The acquisition of knowledge and skills for taskwork and teamwork to control complex technical systems: a cognitive and macroergonomics perspective. Springer, Germany

    Book  Google Scholar 

  • Kluge A, Sauer J, Schüler K, Burkolter D (2009) Designing training for process control simulators: a review of empirical findings and current practices. Theor Issues Ergon Sci 10:489–509

    Article  Google Scholar 

  • Kozlak M, Nawrat A, Kurzeja A (2014) Virtual reality simulation technology for military and industry skill improvement and training programs. Szybkobieżne Pojazdy Gąsienicowe 2:5–12

    Google Scholar 

  • Lee S, Jeong I, Il M (2000) Development of evaluation algorithms for operator training system. Comput Chem Eng 24:1517–1522

    Article  Google Scholar 

  • Li Z, Qiu H, Yue Y (2002) Development of a learning-training simulator with virtual functions for lathe operations. Virtual Real 6:96–104

    Article  Google Scholar 

  • Lily Q, Gang Z, Yong P, Tingfu M, Ming G (2008) Three-dimensional virtual chemical laboratory based on virtual reality modelling language. In: IEEE international symposium on IT in medicine and education. Xiamen, pp 491–496

  • Luo N, Wang X, Van F, Qian F (2015) Integrated simulation platform of chemical processes based on virtual reality and dynamic model. Comput Aided Chem Eng 37:581–586

    Article  Google Scholar 

  • Manca D (2017) Technical considerations on operator training simulator (OTS). http://pselab.chem.polimi.it/wp-content/uploads/2017/06/Les-07-Operator-Training-Simulator.pdf. Accessed 14 June 2017

  • Manca D, Nazir S, Colombo S (2012a) Performance indicators for training assessment of control-room operators. Chem Eng Trans 26:285–290

    Google Scholar 

  • Manca D, Nazir S, Lucernoni F, Colombo S (2012b) Performance indicators for the assessment of industrial operators. Symp Comput Aided Process Eng 17:20

    Google Scholar 

  • Manca D, Brambilla S, Colombo S (2013a) Bridging between virtual reality and accident simulation for training of process-industry operators. Adv Eng Softw 55:1–9

    Article  Google Scholar 

  • Manca D, Colombo S, Nazir S (2013b) A plant simulator to enhance the process safety of industrial operators. In: European HSE conference and exhibition, society of petroleum engineers, London, UK

  • Manca D, Nazir S, Colombo S, Kluge A (2014) Procedure for automated assessment of industrial operators. Chem Eng Trans 36:391–396

    Google Scholar 

  • Manca D, Nazir S, Komulainen TM, Øvergård KI (2016) How extreme environments can impact the training of industrial operators. Chem Eng Trans 53:193–198

    Google Scholar 

  • Manesh HF, Schaefer D, Hashemipour M (2011) Information requirements analysis for holonic manufacturing systems in a virtual environment. Adv Mater Res Switz 53:385–398

    Google Scholar 

  • Mannan S (2017) The 100 Largest losses. http://www.oliverwyman.com/content/dam/marsh/Documents/PDF/UK-en/100%20Largest%20Losses%2023rd%20Edition-03-2014.pdf. Accessed 1 June 2017

  • Monferini A, Konstandinidou M, Nivolianitou Z, Weber S, Kontogiannis T, Kafka P, Kay AM, Leva MC, Demichela M (2010) Human & organizational factors impact on risk level in an NG treatment and storage plant. In: European safety and reliability conference 2010. ESREL, pp 1820–1827

  • Muravyev A, Berutti M (2007) Operator training system for hydrocracking unit: real world questions and answers. In: AIChE annual meeting, Texas, conference proceedings

  • Naderpour M, Nazir S, Lu J (2015) The role of situation awareness in accidents of large-scale technological systems. Process Saf Environ 97:13–24

    Article  Google Scholar 

  • Nazir S, Manca D (2015) How a plant simulator can improve industrial safety. Process Saf Prog 34:237–243

    Article  Google Scholar 

  • Nazir S, Colombo S, Gallace A, Bordegoni M, Manca D (2012a) Performance comparison of different training methods for industrial operators. In: de Waard D, Brookhuis K, Dehais F, Weikert C, Röttger S, Manzey D, Biede S, Reuzeau F, Terrier P (eds) Human factors: a view from an integrative perspective. Proceedings HFES Europe chapter conference Toulouse, pp 235–242

  • Nazir S, Totaro R, Brambilla S, Colombo S, Manca D (2012b) Virtual and augmented reality as viable tools to train industrial operators. Comput Aided Chem Eng 30:1397–1401

    Article  Google Scholar 

  • Nazir S, Colombo S, Manca D (2012b) The role of situation awareness for the operators of process industry. Chem Engineer Trans 26:303–308

    Google Scholar 

  • Nazir S, Colombo S, Manca D (2013a) Testing and analyzing different training methods for industrial operators: an experimental approach. Comput Aided Chem Eng 32:667–672

    Article  Google Scholar 

  • Nazir S, Colombo S, Manca D (2013b) Minimizing the risk in the process industry by using a plant simulator: a novel approach. Aidic Conf Ser 11:271–280

    Google Scholar 

  • Nazir S, Kluge A, Manca D (2014) Can immersive virtual environments make the difference in training industrial operators. In: Proceedings of the human factors and ergonomics society, pp 251–265

  • Nazir S, Øvergård KI, Yang Z (2015a) Towards effective training for process and maritime industries. Procedia Manuf 3:1519–1526

    Article  Google Scholar 

  • Nazir S, Sorensen LJ, Øvergård KI, Manca D (2015b) Impact of training methods on distributed situation awareness of industrial operators. Saf Sci 73:136–145

    Article  Google Scholar 

  • Park J, Jung W, Ha J, Shin Y (2004) Analysis of operators’ performance under emergencies using a training simulator of the nuclear power plant. Reliab Eng Syst Saf 83:179–186

    Article  Google Scholar 

  • Passos C, Nazir S, Mol AC, Carvalho PV (2016) Collaborative virtual environment for training teams in emergency situations. Chem Eng Trans 53:217–222

    Google Scholar 

  • Patle DS, Ahmad Z, Rangaiah GP (2014) Operator training simulators in the chemical industry: review, issues, and future directions. Rev Chem Eng 30:199–216

    Article  Google Scholar 

  • Reinach S, Viale A (2006) Application of a human error framework to conduct train accident/incident investigations. Accid Anal Prev 38:396–406

    Article  Google Scholar 

  • Rose FD, Brooks BM, Rizzo AA (2005) Virtual reality in brain damage rehabilitation: review. Cyberpsychol Behav 8:241–262

    Article  Google Scholar 

  • Salmon PM, Stanton NA, Walker GH, Jenkins D, Ladva D, Rafferty L, Young M (2009) Measuring situation awareness in complex systems: comparison of measures study. Int J Ind Ergonom 39:490–500

    Article  Google Scholar 

  • Shang X, Chung P, Fry J, Vezzadini L, Colombo M (2009) How a process simulator and a rule-based system contribute to virtual reality applications for process safety. Comput Aided Chem Eng 26:435–439

    Article  Google Scholar 

  • Siminovich C, Joao S (2014) Dynamic operator training simulators for sulphuric acid, phosphoric acid, and DAP production units. Procedia Eng 83:215–224

    Article  Google Scholar 

  • Toro R, Ortiz JM, Zamora C (2013) An integrated simulation-based solution for operator effectiveness. IFAC Proc Vol 46:65–69

    Article  Google Scholar 

  • Vidulich MA, Tsang PS (2006) Mental workload and situation awareness. In: Salvendy G (ed) Handbook of human factors and ergonomics, 3rd edn. Wliey, New Jersey, pp 243–268

    Google Scholar 

  • Wasfy TM, Noor AK (2001) Visualization of CFD results in immersive virtual environments. Adv Eng Softw 32:717–730

    Article  MATH  Google Scholar 

  • Yang SH, Yang L, He CH (2001) Improve safety of industrial processes using dynamic operator training simulators. Process Saf Environ 79:329–338

    Article  Google Scholar 

  • Zhiyun Z, Baoyu C, Xinjun G, Chenguang C (2003) The development of a novel type chemical process operator-training simulator. Comput Aided Chem Eng 15:1447–1452

    Article  Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge the fellowship awarded to the author, Dipesh S Patle, from Erasmus Mundus Intact for Postdoctoral research.

Author information

Author notes

  1. Dipesh S. Patle

    Present address: Chemical Engineering Department, Motilal Nehru National Institute of Technology Allahabad, Allahabad, India

  2. Dipesh S. Patle: Work carried out as a post doctoral researcher at Politecnico di Milano, Italy.

Authors and Affiliations

  1. Department of Chemical Engineering, School of Civil and Chemical Engineering, Vellore Institute of Technology, Vellore, Tamilnadu, 632014, India

    Dipesh S. Patle & Swapnil Sharma

  2. PSE-Lab - Process Systems Engineering Laboratory, CMIC Chemical Engineering Department, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133, Milan, Italy

    Dipesh S. Patle & Davide Manca

  3. Training and Assessment Research Group (TARG), University College of Southeast Norway, Postboks 4, 3199, Borre, Norway

    Salman Nazir

Authors
  1. Dipesh S. Patle
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Davide Manca
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Salman Nazir
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Swapnil Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dipesh S. Patle.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Patle, D.S., Manca, D., Nazir, S. et al. Operator training simulators in virtual reality environment for process operators: a review. Virtual Reality 23, 293–311 (2019). https://doi.org/10.1007/s10055-018-0354-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10055-018-0354-3

Keywords

Search

Navigation