| Summary: | Abstract Industry 4.0 relevant systems (eg, cyber‐physical systems, digital twins, and alike) need digitized knowledge to function. Before digitizing knowledge, a fundamental question arises: What is knowledge? In order to answer this question, this study first reviews the definitions of knowledge found in the extant literature of epistemology, engineering design, manufacturing, organization science, information science, and education science. Since the definitions reported so far are not succinct and suffer circularity, this study overcomes this by introducing a three‐element‐based definition of knowledge—a piece knowledge consists of three elements defined as claim, provenance, and inference. This results in four types of knowledge defined as definitional, deductive, inductive, and creative knowledge, and each type of knowledge is again divided into some categories. Some real‐life scenarios relevant to engineering design and manufacturing are used to clarify the proposed knowledge types/categories; the relevant pieces of knowledge are represented by knowledge graphs (concept maps) for the sake of digitization. The myriad proximal and distal relationships between knowledge and other relevant entities (human/machine learning, logical inferences, experimental data, analytical results, creative thinking, and cognitive reflections) become succinct and transparent due to the proposed definition of knowledge. Consequently, this study establishes the fundamentals of developing sophisticated methods and tools for the advancement of Industry 4.0.
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