3. Accompanying the digitalisation of the process industry and designing potential infrastructural R&D focal points

3.1. Urgent research topics for the digitalisation of the process industry

Digitalisation requires the specific, close cooperation of users from the process industry, their suppliers (i.e., equipment and software manufacturers in automation and plant and apparatus engineering) and research institutes at eye-level.  If these developments are to progress rapidly, this is only achievable in specific projects. Ideally, this is done in joint R&D programs in which demonstrators and prototypes are developed. In addition, jointly validated devices and software with a lasting effect on the digitization infrastructure can also be created here, i.e. a difficult part of product development, the certification, is accomplished jointly and can be implemented particularly quickly.

The digital networking of the horizontal supply chain and the vertical asset life cycle as shown in Figure 1 is the ultimate goal of digitalization in the process industry and holds the greatest potential. The following research and development topics are emerging on the way to this goal:

  • Supply chain, production architecture and platform solutions (horizontal)
  • Process development, asset life cycle (vertical)
  • Digital twin
  • Standardized data structures

In addition to these specific topics, the following cross-cutting issues that influence the success of digitalisation need to be addressed:

  • Learning Processes
  • Artificial intelligence (AI) and IT infrastructure
  • Structural and cultural change in the world of work and work processes


3.1.1.   Supply chain, production architecture and platform solutions

The creation of digital platform solutions in the supply chain between manufacturer, supplier and customer is essential for networking with efficient workflows. The challenges for networking lie in mutual trust and cooperation in the exchange of data. Here, concepts for the secure exchange of data between the process industry and its suppliers through open, standardized, manufacturer-independent interfaces are developed.

3.1.2.    Process development, asset life cycle and digital twin

Work is already underway on the development of "smart and intelligent equipment" and concepts of "modular production" or "continuous engineering". These approaches increase the efficiency and flexibility of the process industry and reduce time-to-market. The digital twin is a central element of digitalization, will gain in importance in the future and is currently under development in many places. Working groups 1 and 3 of TAK Dig have developed and published a position paper on the digital twin [8].

The two working groups have also formed the consortium that developed the project proposal for KEEN within the framework of a call for AI against the background of the requirements of the process industry.

The 58th Tutzing Symposium "Separation Units 4.0 - Separation Technology in the Chemical Industry on the Way to the Digital Future" took place on the topic of Digital Chemical Plant. In October 2019, representatives from academia and industry met at the invitation of the ProcessNet Association "Fluid Dynamics and Separation Technology" to determine the status and further development of the field. In contrast to previous events, the focus was on the individual separation equipment and fluid process engineering itself in a complementary manner. In five topic clusters, each with several workshops, future developments and emerging separation tasks, opportunities, challenges and potentials of fluid separation technology were identified and intensively discussed. In addition, potential and necessary networking and cooperation with other industries and knowledge disciplines were discussed, which forms the basis for further concept developments and for the derivation of necessary activities. A publication on Separation Units 4.0 is also available for this purpose.

3.1.3.    Standardized data structures

Digitization requires comprehensive and efficient access to data from different sources in vertical and horizontal value chains. To enable this access, so-called data models are appropriate, which enable the unambiguous addressability of the data. The DEXPI initiative described below has made a start for the asset life cycle, but data models should now be developed for other areas.

3.1.4.   Cross-cutting issue: artificial intelligence (AI) and IT infrastructure

Trust centers and the use of secure IT infrastructure (possibly also involving federal institutes) play a fundamental role in the design of an IT infrastructure and the use of artificial intelligence.

Research into artificial intelligence concepts for use in the lifecycles of products, processes and systems is pending. Artificial intelligence should contribute to an increase in efficiency and, in particular, also to an increase in plant safety (assistance systems), since it can be used to quickly analyse complex interrelationships and to provide appropriate support to plant operating personnel.

In the field of AI in the process industry, the BMWi, project sponsor DLR in Cologne, granted start-up financing from 15 April 2019 for the TU Dresden, TU Dortmund and FhG-ITMW Kaiserslautern for a full proposal to set up incubator laboratories. Making artificial intelligence understandable in the process industry is the goal of the KEEN start-up project. The project was funded in the competition phase until October 2019. At the end of August 2019, the project has been positively evaluated and will enter the implementation phase as a comprehensive joint project in April 2020.

In a competition for the best ideas, the project developed a concept for the establishment of a platform to promote the application of artificial intelligence methods in the process industry by the end of July. Three full-day creative workshops in Frankfurt at the DECHEMA building served to determine the need for action and generate solution approaches in five pillars:

  • AI-based modelling
  • AI-based engineering & optimization
  • AI life cycle models
  • AI fully automated
  • AI Training

From this, three areas have been formed for modelling, engineering and fully automated plant, which are being tackled in different work packages.

3.1.5.    Horizontal issues: Learning processes; structural and cultural change in the world of work and working processes

Digitalisation will bring about profound changes in the world of work and in work processes. This will initially involve new technologies, but also, to a large extent, methodological and structural changes. New learning concepts as well as further training opportunities for industry, science and public authorities must be created. Furthermore, the implementation of change management concepts is necessary. Working on these topics requires the integration of non-technical disciplines (e.g. industrial psychology). TAK Dig has established a working group for this topic area, sees itself as a mediator and would like to bring together the various specialist areas.

3.2.    Existing R&D programmes for the digitalisation of the process industry

There are mainly programs for the automation of the manufacturing industry as well as for increasing efficiency and modularization in chemical process technology. No current program addresses the comprehensive digitalization of the process industry, as suggested in 3.

3.2.1. Increasing efficiency and modularisation in chemical process technology

Project duration: 03/2015-08/2018

Funding: BMWi

In the medium term, the Chemical Process Engineering research field is to link the areas of sensors and artificial intelligence even more closely with efficiency and modularisation concepts. In this respect, new funding directions can also be linked there.

1st funding phase: ENPRO 1.0: From 2014 to 2017, four collaborative projects and one accompanying project were carried out in the ENPRO initiative:

  • Continuous processes for polymer specialities with the aid of novel apparatus concepts (KoPPonA)
  • Smart-Mini Plant for the development of efficient continuous separation processes (SMekT)
  • Modular equipment for energy-efficient production (modularization)
  • Improved energy efficiency and process acceleration through data integration from process development to production (data integration)

2nd funding phase: ENPRO 2.0: The first projects from the 2nd funding phase of the ENPRO initiative have been running since November 2017.

  • Efficient orchestration of modular systems (ORCA, start: 01.11.2017)
    In the EPRO 2.0 ORCA project, plant operators, module manufacturers, automation engineers, system integrators, authorities and universities are working together to derive process engineering, safety engineering and automation technology integrating concepts for modular, intelligent and flexible production plants.
  • Cross-scale methodology for planning and developing resource-efficient processes (SkaMPi, start: 01.11.2017)
    The aim of the SkaMPi project (cross-scale methodology for planning and developing resource-efficient processes) is to break through inherent barriers and to supplement the existing methodology in such a way that the selection of the optimal apparatus technologies can be carried out at an early stage for a new product or an envisaged product portfolio. In doing so, an optimal resource-efficient process connection is taken into account.
  • Separation processes with efficient and intelligent equipment (TeiA, start: 01.01.2018)
    Currently, pharmaceutical, fine and specialty chemicals are still produced and purified in batch processes, whereas a changeover to continuously operated and modularly designed plants can be a promising approach for energy and time savings. For this purpose, various crystallization and extraction apparatuses are being investigated within the TeiA project. Their operating windows are characterized and tested for different material systems. In addition, novel sensors will be developed, integrated into the apparatuses and used for an improved process understanding.
  • Modules in the life cycle of a process plant - applications for integrated models (ModuLA, start: 01.09.2018)
    In the ModuLA project, the specification of a continuous and consistent information model, i.e. a digital twin, for modules and systems is being developed. The information model covers the entire life cycle from laboratory, planning and construction to operation, maintenance and deconstruction. The results of the project provide a basis for linking modules with each other in terms of information technology and making relevant life cycle information of modules and plants available more easily than at present.

3.2.2.   Scalable integration concept for data aggregation, analysis and processing of large data volumes in the process industry (SIDAP, http://www.sidap.de)

Project duration: 03/2015-08/2018

Funding: BMWi "Smart Data

Partners: Bayer AG, IBM Deutschland GmbH, Chair of Automation and Information Technology TU Munich, Evonik Industries AG, Gefasoft AG;

Associated partners: Covestro AG, Krohne Messtechnik, NAMUR, Samson AG, Sick AG, ZVEI; cooperation partners: Interessengemeinschaft Regelwerke Technik (IGR) e.V.

SIDAP developed a data-driven as well as service-oriented integration architecture, which makes already existing structural information and data streams in engineering and process control systems accessible for interactive analyses by authorized users in an abstracted, integrated and access-protected form, taking into account their different semantics. This enables device manufacturers to analyze device malfunctions on the basis of usage data of their devices in production plants and maintenance, to identify faults preventively and to intervene in time to provide plant operators with optimal support in the future. For the plant operator, optimum use of the devices and thus the most trouble-free operation possible is ensured. The final report is available here [10].

3.2.3.    Data Exchange in the Process Industry (DEXPI)

Project information: Working group of the ProcessNet (http://dexpi.org/)

Owners/operators: Air Liquide, BASF, Bayer, Covestro, Equinor, Evonik, Merck 

Technical consulting: AixCAPE, pnb plants & bytes

Software manufacturers: Aucotec, Autodesk, AVEVA, Bilfinger, eVision, Hexagon, PTC, Semantum, Siemens, X-Visual

Research facilities: Kyungpook National University, RWTH Aachen University AVT.SVT, Tecgraf/PUC-Rio, TU Berlin, VTT Finland

Insufficient interoperability between CAE tools makes it difficult to plan, build and operate process plants across organizational boundaries, e.g. between different companies or even business units within the same company. Therefore, the DEXPI working group aims to develop a manufacturer-neutral exchange format for engineering data and documents and to implement it in interfaces of existing CAE tools. Currently, the focus is on the exchange of P&I diagrams including graphical layout and engineering data.


3.2.4.    smartLAB (Biotechnology)

Project duration: 2014-2019

Funding: State of Lower Saxony (MW and MWK)

Partners: Sartorius, Mettler-Toledo, Eppendorf, Schmidt & Haensch, Noack Laboratories, labfolder, IGo3D, Presens, Köttermann, Realworld One, Fraunhofer IPA, Institute for Journalism and Communication HMTMH, Institute for Technical Chemistry LUH, Deutsche Messe

The smartLAB initiative has been in existence since 2014 and has set itself the goal of evaluating technologies for digitisation in the laboratory sector in a holistic approach, developing corresponding functional and digitalized laboratory environments and ultimately presenting its results in a showroom, so that this important topic for the development of laboratory infrastructure is clearly presented, opportunities for the various players are identified and further developed and an intensive discussion on this topic is initiated.

Every two years, the smartLAB therefore presents its current results at a highlight stand at the LABVOLUTION trade fair, the last time in May 2019. smartLAB not only shows the latest technologies in the laboratory sector, but also demonstrates exemplary, fully digitally supported workflows live, in order to make digitalization a tangible experience for visitors.

Important aspects of the smartLAB are the basic networking of laboratory equipment with a LIMS, flexible and modular laboratory infrastructure, integration of innovative technologies also from the consumer sector (e.g. smartphones, 3D printing, augmented and virtual reality, etc.), interaction media for human-machine interaction (e.g. LabGlasses, touch beamers, speech assistance systems, etc.) and the standardization of interfaces, device drivers and communication protocols.

3.2.5.    Digitisation in industrial biotechnology (DigInBio)

Project duration: 2018-2020

Funding: BMBF

Partners: Chair of Biochemical Engineering TU Munich, Institute of Technical Chemistry LU Hannover, IBG-1: Biotechnology Research Centre Jülich, labfolder GmbH;

Supporters: Sartorius, TECAN, Eppendorf, 2mag, m2p-labs, Eppendorf Bioprocess Center, Presens, iTiZZiMO, Clariant, Qiagen, Evonik, Mettler Toledo, BRAIN, VCI, IG BCE, Deutsche Messe. 

The joint project "DigInBio" will demonstrate to industry and young academics the future possibilities of digitalization, automation and miniaturization for biotechnology. By setting up demonstration laboratories, the potential of digitalization in this field will become visible and how it can be shaped in concrete terms.

The main focus is the development of digital workflows starting with the selection of suitable production organisms up to the processing of the product. Important aspects here are the acceleration of experimental work through automation and digitalization as well as the modularization of the processes combined with intelligent data management via a LIMS. Communication between system components and laboratory equipment plays a major role in the digital accessibility of experimental data and is a central challenge.

Next page


  1. Introduction
  2. The concept of digitalisation in the process industry
  3. Accompanying the digitalisation of the process industry and designing potential infrastructural R&D focal points
  4. Current associations and working groups shaping the digitization of the process industry
  5. Important events to shape the digitalization of the process industry
  6. References



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