The design of complex engineered systems highly relies on a laborious zigzagging between computer-aided design (CAD) software and design rules prescribed by design manuals. Despite the emergence ofknowledge management techniques (ontology, expert system, text mining, etc.), companies continue tostore design rules in large and unstructured documents. To facilitate the integration of design rules andCAD software, we propose a knowledge graph that structures a large set of design rules in a computableformat. The knowledge graph organises entities of design rules (nodes), relationships among design rules(edges), as well as contextual information. The categorisation of entities and relationships in four sub-contexts: semantic, social, engineering, and IT – facilitates the development of the data model, especiallythe definition of the “design context” concept. The knowledge graph paves the way to a context-awarecognitive design assistant. Indeed, connected to or embedded in a CAD software, a context-aware cog-nitive design assistant will capture the design context in near real time and run reasoning operationson the knowledge graph to extend traditional CAD capabilities, such as the recommendation of designrules, the verification of design solutions, or the automation of design routines. Our validation experi-ment shows that the current version of the context-aware cognitive design assistant is more efficientthan the traditional document-based design. On average, participants using an unstructured design rulesdocument have a precision of 0.36 whereas participants using our demonstrator obtain a 0.61 precisionscore. Finally, designers supported by the design assistant spend more time designing than searching forapplicable design rules compared to the traditional design approach.