Posts Tagged ‘bioprocessing’


The emergence of new production philosophies, initiated by the FDA’s PAT initiative and in particular the German government’s future project Industry 4.0, has led to a reorientation of sensor technology, which will be trend-setting for biotechnology processes with their special requirements – especially continuous and/or integrated production – in the coming years. Under the maxim of process observability and controllability,a clear trend towards smart sensors with a clear focus on sensor intelligence, decentralization, multi-sensor systems and miniaturization has become apparent.

How to avoid drowning in the data flood

Driven by the state initiative of the future project Industry 4.0, the real and virtual world merge into the Internet of Things. Through intelligent methods of process monitoring and decision making, production processes, companies and complete value chains are to be controlled and optimized almost in real time. In the context of a holistic and sustainable implementation of the vision of the intelligent company, it is particularly important for the field of biotechnology with its high demands on product quality and safety as well as the sometimes highly complex production processes and structures to obtain reliable data for production control. More and more modular, intelligent and networked components must make this data available and via integrated analytical tools take over the simult

aneous evaluation of this flood of data. In this context, smart sensors are sensors that perform complex signal processing tasks in addition to the actual measurement task, can be parameterized and diagnosed and can provide additional information about themselves and the process environment.

Especially for the applicability to biotechnological processes, the following elements of extended sensor intelligence are of essential importance, as they will provide users with greater process reliability as well as cost and time savings:

  • Self-diagnosis, self-identification and reporting of one’s own status
  • Possibility of executing decentralised logic functions (If-Then) and processing complete process functions (only result is reported to PLC) for increasing process reliability and reducing the volume of data to be transmitted
  • Independent validity check of the measured values and adequate information summary
  • Selection and evaluation of process profiles, characteristics and parameters and transfer to status and status messages such as „in control“ or „out of control”
  • direct interaction with assigned actors via decentralised control units
  • Trend determination and prediction of process flows

The extension of sensor intelligence is particularly important for its applicability to biotechnological processes. The possibility of self-diagnosis, self-identification and reporting of the own status should take place in the sensor, so that an independent validity check of the measured values can be transferred to the control system. As a result, the routine testing work in the laboratory can be reduced. Checks are only carried out when necessary and the personnel capacities released as a result can be re-allocated in the company to add value.

Requirements for sensors in biotechnology

The prerequisite for this is an adequate information summary of the available data and suitable data preprocessing with the execution of decentralized logic functions. In this way, the smart sensor can independently record process events and evaluate the determined events using a corresponding functionality (e.g. correlation analyses of abiotic and biotic data).  The actual control is transferred for further processing in the control cycle. The independent process analysis, parameter evaluation and decision making of the individual sensor or in combination, for example as a multi-agent framework, offers enormous potential in terms of optimising and increasing the efficiency of bioprocesses. In particular, the complex topic of population heterogeneity and the use of complex substrate matrices open up a broad spectrum to explore the possibilities and limitations of the smart sensors with regard to innovative population concepts and models.

This text is an excerpt of the position paper “Smarte Sensoren für die Biotechnologie”, DECHEMA 2017. If you want to learn more about the concept, applications and technologies for smart sensors, join the conference „Smart Sensors – mechanistic and data driven modelling“ on 1-2 October 2018, Frankfurt.


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