Digital Production, Logistics, Maintenance, Repair and Overhaul (MRO)

(Digitale Produktion, Logistik und MRO)



The research center for „Digital Production, Logistics, Maintenance, Repair and Overhaul (MRO) shall make visible and strategically focus the distributed research activities of the Hamburg University of Technology regarding the area of “Industrie 4.0” to make better use of existing competencies as well as extend the expertise. A necessary first thematic focusing of the extensive “Industrie 4.0” (I4.0) approach results from the consideration of the production environment of the metropolitan region Hamburg (cf. figure). In northern Germany, the dominating industries are aircraft construction and MRO (maintenance, repair and overhaul), shipbuilding, logistics, wind power, mechanical engineering and medical technology. These industries are characterized by small batch sizes or job production, distinct lightweight construction by design or material with a low level of automation, commonly large dimensions of the products with workshop oriented organization principles as well as the long service life of products that in many cases involves higher efforts for MRO than the original production.

Especially the last aspect calls for an expansion of the so far production oriented approach of I4.0 to all phases of product life. The matching “classic” approach to digitalization, “Product Lifecycle Management” (PLM), has to be extended using the following approaches:

  • Control of highly distributed processes with low levels of automation and small batch sizes or job production during and across life phases (control)
  • Use of current and/or historical life phase data for predictive optimization of subsequent phases (prediction, e.g. predictive maintenance)
  • Use of current and/or historical life phase data for feedback optimization of preceding phases for small series, evolution of product families or by one-off upgrading/retrofit (feedback)

Thus, the primary objective of the research center is the “development of methods for the efficient management of regenerative product life phases by prediction and feedback for one-off products”.