Industrial Systems Engineering

Scope

We focus on the development of methods, techniques and tools to support the design and operational management of production systems. The activities concentrate around a number of research topics:

  • Mathematical modeling and optimization of industrial systems
    Development of multi-criteria evaluation and optimization methods to support the design, planning and control of manufacturing systems. The main focus lies on stochastic modelling approaches to obtain robust solutions, taking into account the inherent uncertainty and variability of today’s assembly environments.
  • Validation of flexible automation concepts and operator support systems
    Experimental validation of flexible automation and operator support systems. We focus on the development of standardized models for digitized assembly information based on industrial standards to allow for the (automated) generation of personalized and contextualized work instructions and other support tools.
  • Virtual models to support operational decisions and virtual commissioning
    Development of simulation models to validate design choices and test what-if scenarios. An important research topic is the use of virtual models to perform virtual commissioning of industrial control systems/strategies and automatically generate test scenarios.

Next to this we have activities related to logistics, supply chain management, material handling and warehousing. 

Topics

 

Augmented workers in a manufacturing cell 

operatorinfo.pngThe objective of this project is to develop in-depth understanding w.r.t. methodologies and tools that allow an effective transition from human to human-robot collaborative (HRC) assembly. Our tasks relate to the task distribution and workplace configuratoin. To this end an ontology based on the ISA95 standard has been developed. This ontology allows to collect and provide context aware information to the worker in a manufacturing cell. E.g. information captured from an experienced worker will be stored automatically in this ontology as task instructions. These task instructions will then be provided to the worker, the level of detail will depend on the context e.g. the skill level, the experience, the lot size, .... 

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To Kit or not To Kit (Assembly Line Feeding)

KitOrNot.pngWe developed a decision model to choose between kitting and line stocking at the level of single parts, while taking into account the variable operator walking distances. Different ways of feeding assembly lines, such as kitting and line stocking not only have an impact on in-plant logistics flows but also determine the amount of stock that is available at the line. This, in turn, has an impact on operator walking distances during assembly. We used data from a truck manufacturing company along with artificial data sets. We are currently looking to set up joint research projects to apply the models in the decision process of company cases. 

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Research & test infrastructure

See here our list of infrastructure