Framework For The Successful Set-up Of A Common Data Model In The Context Of An Industry 4.0-ready Plant Design Process

The production plant design process consists of a multitude of individual engineering disciplines, which rely on a variety of digital models. The individual tasks build up on each other, while each discipline consumes information from the previous processes. However, sharing relevant data across multiple companies is challenging and susceptible to miscommunication and delays. Furthermore, integrating diverse software systems, tools, and technologies create compatibility issues and hinder seamless integration. As a result, a heterogeneous, non-automated data and information landscape is created, characterized by a high level of manual data transfer. This represents a major problem on the way towards Industry 4.0. The goal of this paper is to provide a framework for the successful set-up of a common data model in the context of an Industry 4.0-ready plant design process across and along the value chain. For this purpose, a literature review of current problems in the cross-company and cross-departmental collaboration in the plant design process is provided and requirements for the framework are derived. Existing solutions and research projects are compiled and evaluated against the requirements, from which the framework's structure is concluded. The framework itself is intended to be holistic and must therefore not only include technical aspects (e.g. data interfaces, semantics), but also enable the entire organization and value chain to implement the common data model as part of the digital transformation process (e.g. employee skills, business strategy, legal conditions). Based on this, the framework is further elaborated by deducing calls for action for a successful set-up of a common data model within the research project DIAMOND (Digital plant modeling with neutral data formats). The focus should be on employees and their competencies, as these are prerequisites for shaping digital transformation. Future research must prioritize these actions to enhance technology readiness and organizational Industry 4.0 preparation