Operations Planning And Control (OPAC) - Maintenance & Manufacturing (M&M)

Main research interest (DSC/e related)

OPAC research on maintenance and manufacturing revolves around improvement and integration of manufacturing and maintenance planning, thus facilitating the optimization of a factory as a whole, instead of sub-optimizing business units and processes separately. Integrated planning will lead to higher and more flexible production capacity and more efficient maintenance. The focus is on high-tech industry. Data driven research is centered around the following challenges:

  • Development of data-collection and data-aggregation techniques for production and maintenance models
  • Implementation of advanced prediction and estimation techniques (e.g. failures, wear out, demand)
  • Creation of data-drivenintegrated prediction and optimization models 

Our missionis to produce high quality research results that lead to the development of a data-driven decision-making framework at operational and tactical level to support integrated production planning and predictive maintenance, and to publish these research findings in high impact refereed journals.

Success stories

Introduction of data mining tool at NXP semi-conductor assembly plant to steer daily maintenance operations resulted in an increase in overall equipment efficiency of several percent, which equals an increased output of millions of products per day.

Implemented operational planning support tool at ASML to visualize and align the actual spare parts stocks with the planned stocks at the tactical planning level. Resulted in better service, lower inventory holding costs, and a more efficient planning process.

Project examples

  • Dynamerge NWO, with e.g. Philips, Brandweer Amsterdam, CWI Emergency service logistics, dynamic planning at operational level, network design.
  • MANTIS EU project, 60 partnersPredictive maintenance, maintenance service platform architecture.
  • Philips Data Science Flagship Philips & TU/e Predictive maintenance for healthcare systems.
  • Productive 4.0 117 partners: Data-driven manufacturing.
  • ProSeLo Next TKI Dinalog, with e.g. Marel, Océ, ASML, Vanderlande Predictive maintenance, control towers, new business models.
  • Poultry Processing Marel Stork: Layout design, integrated production planning and scheduling.
  • OPTBIOMAN EU Horizon2020 project:Optimal decision making in bio manufacturing.
  • Campionefield lab Smart Industry, 60 partners:Integrated planning in digital manufacturing.