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Operator training simulators in the chemical industry: review, issues, and future directions

  • Dipesh S. Patle received his Master of Engineering from BITS Pilani, India. Previously, he worked as lecturer and as senior research fellow at BITS Pilani and IIT Kharagpur, respectively for a couple of years. Currently, he is pursuing his PhD at USM Malaysia. His research interests include process modeling, simulation, optimization, dynamics and control, and OTS development. He has several publications to his credit.

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    Zainal Ahmad received his Diploma in Chemical Engineering from the University Technology Malaysia in 1996, a BEng (Hons) degree in Chemical Engineering from the University of Surrey, UK, in 1998, an MSc in Applied Process Control (with Distinction) in 2001, and a PhD in Chemical and Process Engineering in 2005, both from Newcastle University, UK. He has been an Associate Professor at the University Sains Malaysia since 2005. His research interests include artificial neural networks, process modeling, model-based process control, and neural network applications in chemical processes. He has guided several Master and PhD students. He has several awards and several international journal/conference publications to his credit.

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    Gade P. Rangaiah is with the Department of Chemical & Biomolecular Engineering at the NUS, Singapore. He obtained his Bachelor’s, Master’s, and Doctoral degrees in Chemical Engineering from Andhra University, IIT Kanpur, and Monash University, respectively. He worked in Engineers India Limited for 2 years before his doctoral study. Prof. Rangaiah received the Annual Teaching Excellence Award from NUS for four consecutive years. His research interests are in modeling, optimization and control of chemical, petrochemical and related processes. He has supervised 12 research fellows/engineers and 40 graduate theses including 20 doctoral theses. Prof. Rangaiah has edited 4 books, has contributed many chapters to these and other books, and has published 150 journal and 120 conference papers in the field of Process Systems Engineering.

Veröffentlicht/Copyright: 10. Februar 2014
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Abstract

An inevitable need for the skilled operators to increase the safety and productivity is not new to the chemical industry. Consequently, the training of operators is considered as a very important activity in the chemical industry. Conventional training methodologies are ineffective in training the operators for seldom-occurring perilous situations. The operator training simulator (OTS) is an alternative to train operators without actually endangering the plant and personnel. This contribution covers and discusses the need for OTS, applications of OTS in the chemical industry, issues related to OTS, salient features of a good OTS, commercial software packages used to build OTS, and training configurations. In this article, applications of OTS in the chemical industry reported in the open literature from 1990 to mid-2013 are also reviewed briefly. The review shows that OTS has been successfully used in many chemical industries. Finally, this article concludes by outlining the future directions. Overall, it provides a deeper understanding of many issues about the OTS to interested researchers, vendors, modeling engineers, and application engineers aiming to stimulate further developments in this area leading to improved OTS and their increased usage in the chemical industry.


Corresponding author: Zainal Ahmad, School of Chemical Engineering, Engineering Campus, Universiti Sains Malaysia, Nibong Tebal, 14300 Penang, Malaysia, e-mail:

About the authors

Dipesh S. Patle

Dipesh S. Patle received his Master of Engineering from BITS Pilani, India. Previously, he worked as lecturer and as senior research fellow at BITS Pilani and IIT Kharagpur, respectively for a couple of years. Currently, he is pursuing his PhD at USM Malaysia. His research interests include process modeling, simulation, optimization, dynamics and control, and OTS development. He has several publications to his credit.

Zainal Ahmad

Zainal Ahmad received his Diploma in Chemical Engineering from the University Technology Malaysia in 1996, a BEng (Hons) degree in Chemical Engineering from the University of Surrey, UK, in 1998, an MSc in Applied Process Control (with Distinction) in 2001, and a PhD in Chemical and Process Engineering in 2005, both from Newcastle University, UK. He has been an Associate Professor at the University Sains Malaysia since 2005. His research interests include artificial neural networks, process modeling, model-based process control, and neural network applications in chemical processes. He has guided several Master and PhD students. He has several awards and several international journal/conference publications to his credit.

Gade P. Rangaiah

Gade P. Rangaiah is with the Department of Chemical & Biomolecular Engineering at the NUS, Singapore. He obtained his Bachelor’s, Master’s, and Doctoral degrees in Chemical Engineering from Andhra University, IIT Kanpur, and Monash University, respectively. He worked in Engineers India Limited for 2 years before his doctoral study. Prof. Rangaiah received the Annual Teaching Excellence Award from NUS for four consecutive years. His research interests are in modeling, optimization and control of chemical, petrochemical and related processes. He has supervised 12 research fellows/engineers and 40 graduate theses including 20 doctoral theses. Prof. Rangaiah has edited 4 books, has contributed many chapters to these and other books, and has published 150 journal and 120 conference papers in the field of Process Systems Engineering.

Acknowledgments

The authors gratefully acknowledge Universiti Sains Malaysia for financial support received through the project (RU grant 1001/PJKIMIA/814155).

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Received: 2013-8-7
Accepted: 2014-1-2
Published Online: 2014-2-10
Published in Print: 2014-4-1

©2014 by Walter de Gruyter Berlin/Boston

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