MTPPy: Open-Source AI-friendly Modular Automation

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung


  • Valentin Khaydarov - , Arbeitsgruppe Systemverfahrenstechnik, Technische Universität Dresden (Autor:in)
  • Laura Neuendorf - , Technische Universität (TU) Dortmund (Autor:in)
  • Tobias Kock - , Equipment Design, Technische Universität (TU) Dortmund (Autor:in)
  • Norbert Kockmann - , Technische Universität (TU) Dortmund (Autor:in)
  • Leon Urbas - , Process Control Systems/Process System Engineering (Autor:in)


Modular Automation offers promising technologies for the process and chemical industry. It meets the requirements for greater flexibility and a shorter development cycle for production facilities by dividing the process into smaller standardized units. Key element of Modular Automation is the Module Type Package (MTP). It represents a standardized and manufacturer-independent description of the automation interface for self-contained production units, or Process Equipment Assemblies (PEA), and endows the plug-and-produce capability of PEAs. Software solutions to program MTP compatible PEAs are mostly provided by the Programmable Logic Controller (PLC) manufacturers. They are proprietary and bound to certain hardware and even programming languages. Therefore, their suitability for implementation of soft sensors based on data-driven advanced analytics is strongly limited. In this article we present an opensource Python package, MTPPy, designed for rapid prototyping of MTP-capable soft sensors with a focus on AI-based research applications. MTPPy is aimed at the accelerated deployment of soft sensors in the modular plants; thus, closing the gap between the data-driven model development and integration into the production.


Titel2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)
Herausgeber (Verlag)IEEE Computational Intelligence Society (CIS)
ISBN (elektronisch)9781665499965
ISBN (Print)978-1-6654-9997-2
PublikationsstatusVeröffentlicht - 9 Sep. 2022


Titel2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)
Dauer6 - 9 September 2022
OrtStuttgart, Germany

Externe IDs

Scopus 85141375788
Mendeley c6a5d7b6-3e0f-34ad-8119-75caaa942c79



  • Chemical industry, Soft sensors, Raman scattering, Programmable logic devices, Rapid prototyping, Production facilities, Hardware, Advanced Analytics, Artificial Intelligence, Chemical Industry, Modular Plant, Module type package, PEA Engineering, PEA-as-Code, Process Industry, Soft sensor, VDI/VDE/NAMUR 2658