IoT for Process Management

Under the theme »IoT-based Process Management«, the Fraunhofer IIS works on projects for the use of IoT data (Internet of Things) for analysis and control of spatially distributed processes in production and logistics. Methods of process mapping, which are based on IoT systems, enable a comprehensive view on procedures of physical processes and provide the data basis for process mining methods as process analysis, -control and -optimization.

IoT devices as data source for Process Mining

Automated, real-time data collection during the process execution is provided by IoT technologies, resulting in large amounts of sensor data. A model-based or AI-based generation of events extracts the process-relevant information. Afterwards, process-mining techniques are used to analyze the processes, identify deviations or optimization potentials within the operational processes.  After the deduction of recommendations for action, a feedback in the process is following. Automated production planning based on objective data is enabled. IoT devices such as smart tags, RTLS or wearables offer more efficient task processing and new interaction options for process control.


Research at Fraunhofer IIS covers both the application as well as the technological development of the following topics:

Usage of IoT devices as a data source in physical processes

Process step and event detection through model-based or AI-based processes

Process Mining

Feedback in the process by IoT devices

Decentralized process control by IoT devices


Process Step Recording of Small-Scale Ceramic Production by IoT Devices

SME's usual small-scale manual production processes consist of many spatially distributed process steps and place high demands on material flow control. In the INWIPRO project, the production progress is monitored in real time by smart tags. Thereby a consistent production plan can be controlled flexibly and efficiently. The smart tags accompany the production parts through the entire, several-week production. Current position, environment and, above all, process status information are collected. This allows an optimized production planning, which adapts processes to changed conditions such as machine.

Reference Projects


Digitization of Production Processes


In the INWIPRO project, production progress is monitored in real time with the aid of smart objects in the form of electronic goods accompanying carriers, thus enabling flexible and efficient control of continuous production planning. The goods accompanying carriers will be equipped with s-net® networking technology to ensure consistent localisation and the recording of processing statuses.


Road to Digital Production


The requirements for efficient production processes are constantly increasing in global competition. Digitization and data analysis are intended to increase efficiency, flexibility and quality. In the "R2D - Road to Digital Production" project, the digitization of industrial production processes is being driven forward through the development of a Cyber-Physical Production System (CPPS).


AI-based Processmanagement


Demands of transparent and optimized material flow - and processing procedures rise constantly, but affected processes are often not fully digitalisied. The research project AI4Pro wants to optimize spatially distributed processing steps and develope AI based methodes for physical production processes.


Verification of in-house Material Flow Processes


In the ProCheck project producing companies get the chance of using Process Mining for their physical material flow processes. This is due to the fact, that market requirements especially regarding transparency and optimization of processes, are constantly increasing. Not digitalised logistic processes of producing SME can be analysied automatically and subsequent be optimized. This increases the efficiency of those processes.


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