Piping and Instrumentation Diagrams (P&IDs) are used in the process industry to visualize the elements present in a process plant and the connections between them. In reality, P&IDs are often only available as image, PDF, or as hard-copy. Methods to digitize P &IDs exist, but there are only few publicly available P &IDs that can be utilized for the development of new, especially data-driven, methods. We address this lack by proposing an algorithm that is able to create a random structure of P&IDs. Different parameters, such as the number and type of components, inflows, and outflows, can be defined. Our goal is to create a large, labeled, random dataset for the training and validation of models for the digitization of P &IDs. The algorithm consists of the two parts: graph creation and visualization. In this work, we present the graph creation part.

The implementation of Systems Engineering (SE) offers a solution for organizations facing challenges from digitalization and increasing product complexity and interconnectivity. However, the implementation of SE company-wide requires a holistic approach that considers human and organizational factors beyond just technology and technical processes. This paper presents a systematic literature review (SLR) that aimed to determine the key principles for the effective application of SE in industrial practice. Through open, axial, and selective coding, 12 key principles were identified. Finally, an application example is given to show how the principles can be used to improve the process of the offer phase in special purpose machinery.

The rise of new technologies due to digitization leads to challenges for the development of new technical products. Companies are dealing with increasing market dynamics and global pressure while trying to remain innovative and competitive. The offering of customer-oriented products is becoming a key factor for success in the market. As a result, companies' product portfolios are changing to meet varying customer demands, driving up product and organizational complexity. The development of solutions that are not tailored to customer needs has serious consequences for the success of companies. At this point, early validation in the innovation process offers great potential. Through the early consideration of stakeholder feedback, companies can test the desirability of technical product ideas and realize a higher product-market fit and shorter development cycles. In order to plan a validation successfully, engineers need to have an overview about the existing solution knowledge regarding the methods for early prototyping and validation. This paper describes a survey on methods for early prototyping and validation of the desirability of technical product ideas. For that, a systematic procedure was defined and executed for extracting solution knowledge from literature and practice. The outcome of the survey are structured and evaluated methods for early prototyping (84) and early validation (41) and linked practical examples, which are consolidated in fact sheets.

Currently, practitioners follow a top-down approach in automotive development projects. However, recent studies have shown that this top-down approach is not suitable for the implementation and testing of modern automotive systems. Specifically, practitioners increasingly fail to specify requirements and tests for systems with complex component interactions (e.g., e-mobility systems). In this paper, we address this research gap and propose an integrated and iterative scenario-based technique for the specification of requirements and test scenarios. Our idea is to combine both a top-down and a bottom-up integration strategy. For the top-down approach, we use a behavior-driven development (BDD) technique to drive the modeling of high-level system interactions from the user's perspective. For the bottom-up approach, we discovered that natural language processing (NLP) techniques are suited to make textual specifications of existing components accessible to our technique. To integrate both directions, we support the joint execution and automated analysis of system-level interactions and component-level behavior. We demonstrate the feasibility of our approach by conducting a case study at Kostal (Tierl supplier). The case study corroborates, among other things, that our approach supports practitioners in improving requirements and test specifications for integrated system behavior.