Towards Semi-Automatic Generation of a Steady State Digital Twin of a Brownfield Process Plant

Researchers have proposed various models for assessing design alternatives for process plant retrofits. Due to the considerable engineering effort involved, no such models exist for the great majority of brownfield process plants, which have been in operation for years or decades. This article proposes a semi-automatic methodology for generating a digital twin of a brownfield plant. The methodology consists of: (1) extracting information from piping and instrumentation diagrams, (2) converting the information to a graph format, (3) applying graph algorithms to preprocess the graph, (4) generating a simulation model from the graph, (5) performing manual expert editing of the generated model, (6) configuring the calculations done by simulation model elements and (7) parameterizing the simulation model according to recent process measurements in order to obtain a digital twin. Since previous work exists for steps (1–2), this article focuses on defining the methodology for (3–5) and demonstrating it on a laboratory process. A discussion is provided for (6–7). The result of the case study was that only few manual edits needed to be made to the automatically generated simulation model. The paper is concluded with an assessment of open issues and topics of further research for this 7-step methodology.

[1]  Understanding and Applying Simulation Fidelity to the Digital Twin , 2018 .

[2]  Daniel G. H. Sorensen,et al.  Brownfield Development of Platforms for Changeable Manufacturing , 2019, Procedia CIRP.

[3]  Guoliang Li,et al.  Impact of ultra-low emission technology retrofit on the mercury emissions and cross-media transfer in coal-fired power plants. , 2020, Journal of hazardous materials.

[4]  A. Friedl,et al.  Renewable hydrogen production: a technical evaluation based on process simulation , 2010 .

[5]  Teodor Malu.an,et al.  SIMULATION OF PROCESSES IN PAPERMAKING BY WinGEMS SOFTWARE , 2013 .

[6]  Aleksey Kychkin,et al.  IoT-based Mine Ventilation Control System Architecture with Digital Twin , 2020, 2020 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM).

[7]  Arshad Ahmad,et al.  Process Simulation for Removing Impurities From Wastewater Using Sour Water 2-Strippers system via Aspen Hysys , 2016 .

[8]  Johannes Kappen,et al.  Use of modelling and simulation in the pulp and paper industry , 2009 .

[9]  Bálint Hartmann,et al.  Multi-objective method for energy purpose redevelopment of brownfield sites , 2014 .

[10]  Alexander Fay,et al.  Automated generation of simulation models for control code tests , 2013 .

[11]  A. Fay,et al.  Object-oriented engineering data exchange as a base for automatic generation of simulation models , 2009, 2009 35th Annual Conference of IEEE Industrial Electronics.

[12]  Valeriy Vyatkin,et al.  Generating an industrial process graph from 3D pipe routing information , 2020, 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA).

[13]  P. Vainikka,et al.  Carbon mass balance in sugarcane biorefineries in Brazil for evaluating carbon capture and utilization opportunities , 2017 .

[14]  Xin Chen,et al.  A Digital Twin-Based Approach for Designing and Multi-Objective Optimization of Hollow Glass Production Line , 2017, IEEE Access.

[15]  Prasanna Kumar Illa,et al.  Practical Guide to Smart Factory Transition Using IoT, Big Data and Edge Analytics , 2018, IEEE Access.

[16]  Changmin Kim,et al.  Skeleton-based 3D reconstruction of as-built pipelines from laser-scan data , 2013 .

[17]  Changmin Kim,et al.  3D reconstruction of as-built industrial instrumentation models from laser-scan data and a 3D CAD database based on prior knowledge , 2015 .

[18]  Somen Nandi,et al.  Techno‐economic analysis of a plant‐based platform for manufacturing antimicrobial proteins for food safety , 2019, Biotechnology progress.

[19]  Syed Saqib Bukhari,et al.  Table Localization and Field Value Extraction in Piping and Instrumentation Diagram Images , 2019, 2019 International Conference on Document Analysis and Recognition Workshops (ICDARW).

[20]  Valeriy Vyatkin,et al.  Automatic Generation of a High-Fidelity Dynamic Thermal-Hydraulic Process Simulation Model From a 3D Plant Model , 2018, IEEE Access.

[21]  Paul Stuart,et al.  Biofuel production in an integrated forest biorefinery: Technology identification under uncertainty , 2010 .

[22]  Christos Koulamas,et al.  Cyber-Physical Systems and Digital Twins in the Industrial Internet of Things , 2019 .

[23]  Tracy J. Benson,et al.  Process simulation and optimization of methanol production coupled to tri-reforming process , 2013 .

[24]  Jukka K. Nurminen,et al.  Object Detection in Design Diagrams with Machine Learning , 2019, CORES.

[25]  Alexander Fay,et al.  Automatic derivation of qualitative plant simulation models from legacy piping and instrumentation diagrams , 2016, Comput. Chem. Eng..

[26]  Gabriela Clemente,et al.  Simulation and optimization of milk pasteurization processes using a general process simulator (ProSimPlus) , 2010, Comput. Chem. Eng..

[27]  Meng Zhang,et al.  Digital Twin Shop-Floor: A New Shop-Floor Paradigm Towards Smart Manufacturing , 2017, IEEE Access.

[28]  S. Vassilyev,et al.  Management of Large-Scale System Development: Modern Trends and Challenges , 2018 .

[29]  Patrice Nortier,et al.  Coupling a Chemical Reaction Engine with a Mass Flow Balance Process Simulation for Scaling Management in Papermaking Process Waters , 2012 .

[30]  Nikolaos Papakonstantinou,et al.  Integrating 2D and 3D Digital Plant Information Towards Automatic Generation of Digital Twins , 2020, 2020 IEEE 29th International Symposium on Industrial Electronics (ISIE).

[31]  Ben-Guang Rong,et al.  Process simulation and economical evaluation of enzymatic biodiesel production plant. , 2010, Bioresource technology.

[32]  Johan S. Carlson,et al.  Maximizing Smart Factory Systems by Incrementally Updating Point Clouds , 2015, IEEE Computer Graphics and Applications.

[33]  Bohong Wang,et al.  Heat exchanger network retrofit by a shifted retrofit thermodynamic grid diagram-based model and a two-stage approach , 2020 .

[34]  Magne Hillestad,et al.  Dynamic Modeling of the Solvent Regeneration Part of a CO2 Capture Plant , 2013 .

[35]  V.V. Makarov,et al.  The Design Concept of Digital Twin , 2019, 2019 Twelfth International Conference "Management of large-scale system development" (MLSD).

[36]  Lei Shu,et al.  Smart Factory of Industry 4.0: Key Technologies, Application Case, and Challenges , 2018, IEEE Access.

[37]  Massimiliano Barolo,et al.  Using process simulators for steady-state and dynamic plant analysis: An industrial case study , 2004 .

[38]  Ana Paula F. D. Barbosa-Póvoa,et al.  Sustainable batch process retrofit design under uncertainty - An integrated methodology , 2017, Comput. Chem. Eng..

[39]  Christos Koulamas,et al.  Cyber-Physical Systems and Digital Twins in the Industrial Internet of Things [Cyber-Physical Systems] , 2018, Computer.

[40]  Zhiyong Su,et al.  Topology based 2D engineering drawing and 3D model matching for process plant , 2017, Graph. Model..

[41]  Mark Matzopoulos Dynamic Process Modeling: Combining Models and Experimental Data to Solve Industrial Problems , 2014 .

[42]  Jin-Kuk Kim,et al.  Screening of site-wide retrofit options for the minimization of CO2 emissions in process industries , 2015 .

[43]  Xavier Turon,et al.  Simulation and optimisation of a high grade coated paper mill , 2005 .

[44]  C. D’Alpaos,et al.  From biogas to biomethane: A process simulation-based techno-economic comparison of different upgrading technologies in the Italian context , 2019, Renewable Energy.

[45]  Valeriy Vyatkin,et al.  Applying graph matching techniques to enhance reuse of plant design information , 2019, Comput. Ind..

[46]  Thore Berntsson,et al.  The potential for steam savings and implementation of different biorefinery concepts in Scandinavian integrated TMP and paper mills , 2011 .

[47]  Miguel J. Bagajewicz,et al.  Profit-based grassroots design and retrofit of water networks in process plants , 2009, Comput. Chem. Eng..

[48]  Nikolaos Papakonstantinou,et al.  Design to automation continuum for industrial processes: ISO 15926 – IEC 61131 versus an industrial case , 2019, 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA).

[49]  Markus A. Reuter,et al.  Study of process water recirculation in a flotation plant by means of process simulation , 2020 .

[50]  Zhibo Pang,et al.  Reconfigurable Smart Factory for Drug Packing in Healthcare Industry 4.0 , 2019, IEEE Transactions on Industrial Informatics.

[51]  Arndt Lueder,et al.  The Flow and Reuse of Data: Capabilities of AutomationML in the Production System Life Cycle , 2018, IEEE Industrial Electronics Magazine.

[52]  Sylvie Nivelon,et al.  Speciation and supersaturation model in papermaking streams , 2011 .

[53]  Marcelo Cardoso,et al.  Chemical process simulation for minimizing energy consumption in pulp mills , 2009 .

[54]  Julio Garrido Campos,et al.  Automatic generation of digital twin industrial system from a high level specification , 2019, Procedia Manufacturing.

[55]  Kauko Leiviskä Simulation in Pulp and Paper Industry , 1996 .

[56]  Valeriy Vyatkin,et al.  An Integrated Implementation Methodology of a Lifecycle-Wide Tracking Simulation Architecture , 2018, IEEE Access.

[57]  Petteri Kangas,et al.  Evaluation of future pulp mill concepts – Reference model of a modern Nordic kraft pulp mill , 2014 .

[58]  Nenad Stojanovic,et al.  Data-driven Digital Twin approach for process optimization: an industry use case , 2018, 2018 IEEE International Conference on Big Data (Big Data).

[59]  Hon Loong Lam,et al.  Process simulation and techno economic analysis of renewable diesel production via catalytic decarboxylation of rubber seed oil - A case study in Malaysia. , 2017, Journal of environmental management.

[60]  Martin John Atkins,et al.  WinGEMS modelling and pinch analysis of a paper machine for utility reduction , 2010 .

[61]  Marc Priggemeyer,et al.  Experimentable Digital Twins—Streamlining Simulation-Based Systems Engineering for Industry 4.0 , 2018, IEEE Transactions on Industrial Informatics.

[62]  Matthew J. Realff,et al.  Design and simulation of an organosolv process for bioethanol production , 2013 .

[63]  Valeriy Vyatkin,et al.  Automatic Generation of a Simulation-Based Digital Twin of an Industrial Process Plant , 2018, IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society.

[64]  Mark Matzopoulos Dynamic Process Modeling: Combining Models and Experimental Data to Solve Industrial Problems , 2011 .