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Digitalization of manufacturing processes using gPROMS/gOES

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last updated:Jan 05, 2021

シーメンス株式会社  gPROMS ポートフォリオ
シーメンス株式会社 gPROMS ポートフォリオ
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Visualizing manufacturing processes through advanced process modeling. Numerous achievements in fields such as chemicals, pharmaceuticals, and food production.

Our company offers 'gOES (gPROMS Operational Excellence Solutions)', which digitalizes processes such as chemical manufacturing, pharmaceutical manufacturing, and food production, allowing for simulations. Based on data measured by sensors connected to products, systems, and factory equipment, we construct a "digital twin" that enables real-time understanding of the health and performance of production processes. This contributes to efforts aimed at optimizing operating conditions and more. It is suitable for companies considering the digitalization of manufacturing processes and those looking to understand and improve the state of production processes that are not visible in reality. 【Features】 ■ Can be embedded in control systems (DCS) for online use (soft sensors, digital twins, etc.) ■ Easily create complex chemical reaction models (custom models) ■ Extensive model library and physical property database

    simulator
0909_psenterprise_3b_画像差し替え済.jpg

Digitalization of manufacturing processes using gPROMS/gOES

0909_psenterprise_3b_画像差し替え済.jpg
0909_psenterprise_3b_画像差し替え済.jpg
  • Related Link - https://premium.ipros.jp/psenterprise/product/deta…

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【Introduction Example】 Monitoring the progress of caulking in the thermal decomposition furnace reaction tube and performance degradation due to dirt inside the heat exchanger. Optimization of operations can lead to improved production efficiency and reduced energy consumption. 【Applications Available for Each Purpose】 ■gOLEFINS: Software for accurate measurement prediction and monitoring of ethylene cracking furnaces ■gUTILITIES: Software for utility optimization ■gOILFIELD: Operational optimization of crude oil production systems ■gREFINERY: Operational monitoring of oil refining plants ■gREACTOR: Catalyst reactor model *You can view related materials from "PDF Download." Please feel free to contact us.

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Applications/Examples of results

【gOLEFINS】 * Visual multi-sensor for accurate KPI monitoring * Optimization of acetylene converter operations * Prediction of thermal cracking furnace operating time * Optimization of cracking furnace reverse operation Implementation results: Hanwha (South Korea), SABIC (Saudi Arabia), TOTAL (France) 【gUTILITY】 * Optimization of utility distribution such as electricity, cooling water, steam, and fuel * Operational support to minimize energy consumption and CO2 emissions Implementation results: DSM (Netherlands) 【gREFINERY】 * Operation monitoring of oil refining plants * Pre-maintenance and operational optimization Implementation results: Saudi Aramco (Saudi Arabian national oil company) 【gOILFIELD】 * Optimization of crude oil and gas production facilities Implementation results: A major oil company

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Modeling Tool for Optimal Resource Utilization 'gUTILITY'

Modeling Tool for Optimal Resource Utilization 'gUTILITY'

PRODUCT
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Catalytic reactor reaction modeling support

Catalytic reactor reaction modeling support

OTHER
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AML:FBCR Fixed Bed Catalyst Reactor Advanced Modeling Library

AML:FBCR Fixed Bed Catalyst Reactor Advanced Modeling Library

PRODUCT
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gUTILITY Modeling Tool for Role Optimization

gUTILITY Modeling Tool for Role Optimization

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Company Overview Siemens Process Systems Engineering

Company Overview Siemens Process Systems Engineering

COMPANY
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Simulation and Optimization of Oil Production Systems 'gOILFIELD'

Simulation and Optimization of Oil Production Systems 'gOILFIELD'

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Company information

シーメンス株式会社

シーメンス株式会社 gPROMS ポートフォリオ

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Founded in 1997 by the gPROMS development team at Imperial College London, PSE became part of the Siemens Group in 2019 and has been providing products and services in Japan as Siemens Corporation since 2023. gPROMS features a powerful equation-based computation engine that differs from traditional simulators, allowing for seamless handling of both steady-state and dynamic simulations. This enables the effective scaling up of models adjusted with experimental data from batch processing for the design and operational optimization of continuous processing plants. With gPROMS's excellent capabilities in custom modeling, parameter estimation, and optimization, it is possible to quickly build optimal manufacturing processes, resolve issues, and achieve optimization.

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