Digital transformation increases the need for interdisciplinary collaboration along the product lifecycle. It is currently hindered by a low data consistency resulting from the use of heterogeneous systems and data models. Especially in work planning, where several data models are combined, this decreases efficiency. Systems Lifecycle management (SysLM) offers a solution to this remedy. However, a sudden switch to SysLM is not possible in brownfields. Thus, it is necessary to examine the challenges and opportunities to derive case-specific measures that enable its adoption in work planning.

The increasing proportion of software in technical products means that both the products and the associated development processes are becoming more complex. An integration of the existing lifecycle considerations Application Lifecycle Management and Product Lifecycle Management into an interdisciplinary System Lifecycle Management promises to make the complexity manageable. To obtain an overview of the current benefits, challenges, requirements, approaches and open research gaps in the context of an ALM-PLM integration, this contribution presents the results of a Systematic Literature Review.

Engineering Digitalization enables development of new high intelligent products containing mechanical, electrical, software and communication components. As these complex products are result of multidisciplinary engineering processes, digitalization also enforces companies to raise, adapt and revise their engineering competencies and process capabilities to increase agility and maintain competitiveness. Also, the growing amount of data related to product and processes requires a well-structured management concept. In order to encounter all these changes and new requirements companies should identify their specific strengths and weaknesses and derive needs for action. This paper presents a novel maturity model for evaluation of capabilities of Engineering Digitalization in areas of processes, products, services, data, human and organization. The maturity model enables the detection of enhancement potentials and conception of individual digitalization plans for production companies. It has been composed based on a proven multidisciplinary engineering methodology along the product lifecycle process, which includes Model Based Systems Engineering Methods, and a multilevel IT architecture integration concept.