This website accompanies a systematic mapping study on Model-Based Systems Engineering for Industry 4.0.
Industry 4.0 is a term coined 2011 at Hannover fair as the fourth industrial revolution that arises from interconecting all parts of the manufacturing value-added chain. It also has become the title of a high tech strategy project of the German Federal Ministry of Education and Research and can be defined as
“the next phase in the digitization of the manufacturing sector, driven by four disruptions: […] data volumes, computational power, and connectivity; the emergence of analytics and business-intelligence capabilities; new forms of human-machine interaction […]; and improvements in transferring digital instructions to the physical world, such as advanced robotics and 3-D printing.” (McKinsey)
“connected, intelligent products that communicate with users, new digital business models that harness collected data to offer additional services and as-a-service products, products on the assembly line that tell shop floor machinery how they are to be processed. The core of Industry 4.0 is highly intelligent connected systems that create a fully digital value chain, the 4th industrial revolution enabled by the Industrial Internet of Things.” (Accenture)
We aim to characterize the state of the art of Model-Based Systems Engineering for the smart factory through a systematic mapping study on this topic. Adopting a detailed search strategy over multiple digital libraries, 1467 papers were initially identified as possibly relevant. Of these, 222 papers were selected and categorized using a particular classification scheme. In the study, we present the concerns addressed by modeling community for Industry 4.0, how these are investigated, where these are published, and by whom. The resulting research landscape can help to understand, guide, and compare research in this field. In particular, this paper identifies the Industry 4.0 challenges addressed by the modeling community but also the challenges that seems to be less investigated.
For better transparency and replicability, this website provides
We hope that this data supports better comprehension of the systematic mapping study and of its results.
The paper is available from