Managing general domain knowledge and asset-specific information in the form of digital representations is especially important and challenging when focusing on long-living and complex assets. Implicit knowledge and existing structures need to be captured and digitalised, ideally without introducing unnecessary complexity through unfamiliar wording or new structures. To achieve this, a methodical approach that utilises ontologies as well as system modelling techniques and focuses on early-stage model instantiation is presented and applied to the cabin retrofit of aircraft

The complexity of process plants and the growing demand for digitalization require efficient and accurate information retrieval throughout the lifecycle phases of a process plant. This paper discusses the concept of instantiation and introduces a method for identifying and multiplying required information in plant engineering using scalable so-called Instantiation Blocks linked to the Bill of Material. Core functionality, an ontology graph and a user interface based on Python and React are developed to demonstrate the implementation of the framework and validate its effectiveness in practice.

Engineering standards are an important source of knowledge in product development. Despite the increasing digitalisation, the provision and usage of standards is characterised by lots of manual steps. This research paper aims at applying automatic knowledge graph creation in the domain of engineering standards to enable machine-actionable standards. For this, a formula knowledge graph ontology as well as suitable information extraction techniques are developed. The concept is validated using the example of DIN ISO 281, showing the overall capability of automatic knowledge graph creation.

This study explores the application of competency mapping models, incorporating in knowledge management for consulting firms. It evaluates 15 different models, focusing on their suitability for consulting contexts based on data collection, advantages, risks, and limitations. The findings indicate that AI and ML-enhanced competency mapping models are particularly more effective in consulting firms. Finally, the article proposes three key applications of these models for improving knowledge management in consulting firms via empowering communities and collaboration.

During a design process, designers are supported by several purposive product models. To enable designers to switch between them, researchers need to consider the linking of product models during their development. To assist researchers in doing so, the capabilities of a standardizing description approach, stances towards product models, was investigated. The results show that the description approach was able to identify indicators of linking possibilities by facilitating comparability. This is a step towards assisting researchers in considering the linking of product models systematically.

Decentralized E/E architectures (EEAs) are facing challenges and bottlenecks in implementing new features and technologies. The shift towards centralized EEAs has many challenges and needs to be handled pragmatically by considering concurrency with the existing EEAs. To address the challenges of architectural shift, the paper showcases the quantitative comparison of EEAs and visualizes the flow of shifting sub-function and hardware blocks using the Sankey diagram. The observations from the diagram as a result will support OEMs to analyse and take decisions on the shift while developing EEAs.

The amount of data within the product development process requires a structured approach to coordinate them. Knowledge management solutions, such as ontologies, are a suitable way of linking data and representing semantic relationships. However, making all relevant data usable to ensure their target-oriented application is still a challenge. Thus, this contribution presents an approach to identify and classify heterogeneous data in product development. Besides this single ontology approach, interface solutions for data integration into an ontology are proposed.

In today's competitive market, design firms are under pressure to enhance the speed of their decision-making processes to foster innovative products. Due to specialized nature of contemporary technology, enterprises are directed to consider Design for X factors during the product development process like environmental impact and production efficiency. This transformation leads to an increase in gaining knowledge from different fields. This paper presents a comprehensive framework for efficiently acquiring and applying knowledge, aimed at improving knowledge management and sharing practices.

Manufacturing process selection presents numerous challenges to designers, including product complexity, consideration of production volumes and part tolerances. This paper introduces a design support tool based on the axiomatic design model to systematically transform requirements into functions and technological capabilities. The results from an evaluation of the implemented prototype tool in the field of medical device design demonstrates its usefulness in selecting the most suitable candidate manufacturing process for a given artifact, while taking into account multiple user requirements.

When designing battery packs, opposing target-conflicts and design goals arise due to the different disciplines involved in the development process. Looking at the available technologies for battery pack design, different solutions can be found on the market. The development of a battery pack for use in various scenarios therefore presents an interesting use case to evaluate product modularisation approaches. Hence, this paper discusses the application of the Integrated PKT Approach based on a fictious use case of a modular battery pack to derive potential starting points for its improvement.

Anticipating all technical requirements that a product must meet throughout its lifespan has become difficult due to a rise in market, regulatory, and technological uncertainty. As a result, the attribute values of these requirements may be highly uncertain at the start of product development. We propose a mathematical model that captures and quantifies this uncertainty in a clear and comprehensive manner. We evaluate the approach by encoding uncertain requirements for an automotive project. Misconceptions regarding probabilities are alleviated and the requirements are unambiguously defined.

Adaptive structures have the potential to play a significant role in saving resources in the construction industry in the future. For realisation, this requires actuators that meet the requirements of different buildings with their specific load-bearing structures. In the past, the actuators were mainly developed particularly for one exemplary load-bearing structure. This paper analyses the primary classifications for buildings, followed by challenges of adaptive structures, before outlining the draft of a framework for actuators for adaptive structures to speed up and simplify development.

To achieve higher functionality in mechatronic systems, the management of disturbance factors plays a crucial role. For this purpose, a method was developed in prior works to address this management via the optimisation of product structures. However, this method lacks applicability due to the complexity of one step of the method. It is the goal of this paper to present a software tool, utilizing cluster-analysis to sort components into assemblies, with which this step is supported. Additionally, the method is generally adapted to address a wider spectrum of phenomena in mechatronic systems.

In HMLV manufacturing, assembly mistakes by operators are common due to the ever increasing product variability and complexity. If mistakes can be detected early-on in the design process, product designers can reduce the possibility for mistakes. We present an algorithm to automatically detect and evaluate potential misplacements of parts that need to be fastened. Evaluation starts from a product CAD and returns the risk of misplacement as well as visual feedback on possible misplacements. An implementation with FreeCAD of our algorithm is illustrated on different use cases.

Most manufacturing companies have tested and adopted sustainable design methods to navigate their product's environmental transition. While successful at first in enhancing their environmental performance, these companies later struggle to pursue their environmental transition. This entails mastering two critical competencies: identifying transition unknowns, and fostering adequate design efforts. This action research with an innovative design intermediary - which has completed four sustainable packaging missions - reveals the specific design barriers encountered for environmental transition.

Shorter product lifecycles and a shift from mechatronic to cyber-physical systems are leading to greater product complexity. This complexity can be addressed by more intensive cooperation between product and production system development. Despite intensive development in recent years, these process models have not been able to establish themselves in corporate practice. Therefore, this paper analyses the existing integrative product and production methods to identify the reasons for their lack of use in practice. The analysis has shown that there are nine barriers.

In research environments and laboratories e.g. for material sciences the in- and output of simulation data is manually managed. Therefore, physical experiments as well as simulations might be carried out several times, learnings are not systematically gathered, and experiments do not systematically build on learnings from data. This paper proposes to engage an ontology in conjunction with a simulation to use data from already carried out experiments and on that basis predict material behaviour under certain condition and plan further physical experiments.

We present a data-driven approach to support decision-making in CAD modelling and to improve design for manufacturing. Based on automated estimated production planning, information is provided on possible design actions and their impact. A study was conducted on perspectives on and visualizations in CAD modelling. Requirements for a user interface of the described support system were identified. The results serve as basis for further research and development on the interaction of engineering designers with data-driven decision-making support in CAD modelling.

Various industries use computer simulation for verifying product properties in early phases of development. Traditionally, such properties include the stability of mechanical structures or the efficiency of aircraft turbines. More recently, research also focuses on the mountability of industrial products using virtual assembly. While research on virtual assembly already started in the mid-1990s, the applicability in different industries remains largely unclear today. To advance the state-of-the-art, in this paper we present learnings from developing a virtual assembly environment for cooling cabinets.

PLM systems are key enabling systems in the development of today's products. Introduction of a new PLM capability is an expensive and risky undertaking. Many implementation projects end in tears in the sense that they are frequently late or even cancelled. In this paper, a federated PLM architecture pattern – Genesis – is introduced and evaluated against prevalent PLM approaches. From an architecture perspective, Genesis with its two distinct integration tiers decrease the number of integration points and thus cost and complexity.