This paper presents XeraWord, an innovative tool for automatically generating nominal phrases. XeraWord can be used for different tasks, ranging from teaching languages to the creation of examples in lexicography, or even for the development of resources for natural language processing. In this area, Xera was the first experiment, allowing the automatic generation of nominal phrases in three languages: German, French and Spanish. This tool was extended to support other languages, namely, Portuguese and Galician.

We start by presenting the theory behind the development of Xera and its new version, XeraWord, namely, the applied base methodology, and the natural language processing resources used to support it. Then, TraduWord, a tool specifically developed to construct resources for new languages, is presented. This tool allows the semi-automatic translation of the data required for the nominal phrase generation. For this, we discuss its advantages and disadvantages, analysing the quality of the translated resources, as well as the amount of manual work required to validate and correct these resources.

Within product development, manufacturing cost estimation provides a sound basis for design and management decisions. This secures companies profitability, but the effort is high and deep knowledge at the interface of design, manufacturing and costs is needed. These issues can be eased with automation enabled by semantic technologies. Therefore, the authors developed a method for reference-based manufacturing cost estimation and created a prototype. This research evaluates the method and the prototype. Observation, interview and questionnaire were conducted with ten experienced cost engineers at a large German manufacturing company.

Based on its results, the study shows the methods contribution to lower estimation effort, while the impact on transparency and the knowledge base was only partly verified. The method steps show different automation potential, so an incremental automation should be considered. Even though semantic technologies show high potential for identifying reference system elements in this study, the limiting factor for automation in manufacturing cost estimation remains the low availability of product and manufacturing information and missing knowledge of its connection within product development.

There are innumerable design methods that exist across a wide spectrum of disciplines, ranging from engineering, to marketing, to psychology. However, the organic, multidisciplinary nature of methodological development in design leads to challenges in comparing or combining methods. Disciplinary perspectives can create conceptual 'boundaries' that may not align with the fluidity of the problems that designers may need to address. It is challenging to work between the boundaries of these design methods due to the unclear delimitation of exactly where and how methods may be integrated. Nomenclature is unstandardized and different terminologies may describe similar phenomena. To address this, a boundary object—the Actor-Abstraction matrix—is developed to recontextualize each of these divergent methods onto a common scale so they may be better understood in reference to their peers. A meta-analysis of four established design methods is performed to demonstrate the flexibility of this conceptual device. With this tool, existing design methods may be more easily examined to identify points of compatibility and gaps in their coverage, and could also serve as a powerful platform for the creation of new design methods in the future.

Design is widely understood as a domain-independent notion, comprising any activity concerned with creating artefacts. This paper shows that models can be viewed as artefacts, and that the design of models resembles the design of artefacts in other domains. The function-behaviour-structure (FBS) ontology of design is applied to models, mapping generic characteristics of models derived from literature on modelling onto basic, design-ontological categories. An example of model design, namely the CRISP-DM model for designing data mining models, is analysed and compared with models of designing in other domains (systems engineering, mechanical engineering, software engineering, and service design). The results show that there are fundamental commonalities but also differences, revealing the need for further research in developing a theory of model design.

Due to the high freedom of design, additive manufacturing (AM) is increasingly substituting conventional manufacturing technology in several sectors. However, the knowledge and the awareness for the suitable design of additively manufactured components or assemblies ensuring manufacturability and fully realizing its potential is still lacking. In recent years, approaches and tools have emerged that allow the incorporation of existing knowledge of Design for Additive Manufacturing (DfAM) into the design process. Nevertheless, these applications mostly do not consider the formalisation of both restrictive and opportunistic DfAM guidelines for their integration in design tools.

Therefore, the following article presents a framework for the knowledge-driven adaptation of existing designs in the context of DfAM within an expert system. The novelty of the presented approach lies in the interdisciplinarity between the formalization of design guidelines and their integration and consideration within computeraided design for the semi-automated adaptation of functional non-assembly mechanisms. The application of the presented framework to a case study manufactured via Fused Layer Modeling (FLM) illustrates the applicability and benefits.

While the causes of failures in complex engineered systems are often clear in hindsight, it can be challenging to predict failures proactively during the design of novel engineered products or systems. Identifying patterns can be useful for capturing common characteristics that may lead to failure. In this paper, we present a methodology for identifying patterns of failure from NASA's publicly available Lessons Learned Information System (LLIS). We apply an ontology development and clustering approach to identify representative patterns leading to failures in historical lessons learned. A joint inductive-deductive approach reveals the key themes in lessons that lead to failure, which are formalized and recorded as an ontology of complex systems failure causes. Documents from the LLIS are manually tagged with relevant characteristics from the ontology. From the tagged set, clustering is used to capture co-occurring sets of characteristics that lead to failure. The primary contribution of this work is a method for extracting a set of generic failure patterns in complex engineered systems and characteristics for these patterns that can be identified at design time, knowledge of which can be used to plan mitigation strategies.

Representation of design information using causal ontologies is very effective for creative ideation in product design. Hence researchers created databases with models of engineering and biological systems using causal ontologies. Manually building many models using technical documents requires significant effort by specialists. Researchers worked on the automatic extraction of design information leveraging the computational techniques of Machine Learning. But these methods are data intensive, have manual touch points and have not yet reported the end-to-end performance of the process. In this paper, we present the results of a new method inspired by the cognitive process followed by specialists. This method uses the Knowledge Graph with Rule based reasoning for information extraction for the SAPPhIRE causality model from natural language texts. Unlike the supervised learning methods, this new method does not require data intensive modelling. We report the performance of the end-to-end information extraction process, which is found to be a promising alternative.

Taking a geopolitical perspective centred in the Argentinian Andes, the authors propose a hermeneutical view of dialogical archaeology. The application of this theoretical and methodological approach to the example of the archaeological site of Huayatayoc (Puna de Jujuy, Argentina) enables an interpretation of the site as a complex woven fabric of diachronic local and scientific practices and narratives. The authors’ work at Huayatayoc provides an example of the potential of this approach for the development of a critical Latin American archaeology, which seeks to acknowledge the multiple interests and narratives of researchers and local communities in dialogue.

The rapid pace of development in Digital Engineering has led to an explosion of ideas and new practice in how it can support Engineering Design and Manufacture. You may have heard of the terms Digital Transformation, Digital Twin, Digital Thread, Digital Tapestry and Digital Footprint amongst many other forms of “Digital X” but how have these come about and how do they come together to provide the landscape of what Digitalisation has to offer?

In this paper, we analyse the emergence, definition, use and co-occurrence of “Digital X” terminology from an academic dataset of 19,627 papers curated from Scopus. The results reveal that these terms are being used without being fully contextualised in terms of a hierarchy or equivalent to effectively articulate the Digital landscape.

Through this analysis, an emerging “Digital X” framework is proposed, with evidence given to support suggested links, and knowledge gaps highlighted for further investigation. Once this framework is complete, a rich lexicon describing the Digital Landscape will pave the way for the future in Digital Engineering.

One of the greatest challenges of effectively managing knowledge in an organization is promoting seamless connections of operations between departments, the Product Lifecycle Management paradigm. It is also a paradigm that fosters organizational adaptability and quick change in production. Historically, information systems supporting operations have been developed with a specific department's culture in background. Due to this legacy, connecting data, information systems and people across the product lifecycle is an ongoing puzzle for organizations. Theorists and practicians agree on the need to include employees' expertise and vision in this process. However, this involves multiple perspectives and needs that are different but equally valid make. This study explores a tacit knowledge capture tool to be used as a means to voice the interaction and negotiation among employees. Through its influence on ontologies, concept maps collaborative creation can provide a usability tool focused on meaning throughout the product lifecycle. A literature review of the challenges involved and of the proposed tool is presented, followed by a use case and concluded with recommendations drawn from theory and practice.

We present OntoScene, a framework aimed at understanding the semantics of visual scenes starting from the semantics of their elements and the spatial relations holding between them. OntoScene exploits ontologies for representing knowledge and Prolog for specifying the interpretation rules that domain experts may adopt, and for implementing the SceneInterpreter engine. Ontologies allow the designer to formalize the domain in a reusable way and make the system modular and interoperable with existing multiagent systems, while Prolog provides a solid basis to define complex rules of interpretation in a way that can be affordable even for people with no background in Computational Logics. The domain selected for experimenting OntoScene is that of prehistoric rock art, which provides us with a fascinating and challenging testbed.

With the more and more growing demand for semantic Web services over large databases, an efficient evaluation of Datalog queries is arousing a renewed interest among researchers and industry experts. In this scenario, to reduce memory consumption and possibly optimize execution times, the paper proposes novel techniques to determine an optimal indexing schema for the underlying database together with suitable body-orderings for the Datalog rules. The new approach is compared with the standard execution plans implemented in DLV over widely used ontological benchmarks. The results confirm that the memory usage can be significantly reduced without paying any cost in efficiency.

Studies of design activity have been dominantly reporting on different aspects of the design process, rather than the content of designing. The aim of the presented research has been the development and application of an approach for a fine-grain analysis of the design content communicated between designers during the team conceptual design activities. The proposed approach builds on an engineering design ontology as a foundation for the content categorisation. Two teams have been studied using the protocol analysis method. The coded protocols offered fine-grain descriptions of the content communicated at different points in the design session and enabled comparison of teams’ approaches and deriving some generalisable findings. For example, it has been shown that both teams focused primarily on the use of the developed product and the operands within the technical process, in order to generate new technical solutions and initial component design. Moreover, teams exhibit progress from abstract to concrete solutions as the sessions proceeded and focused on the functional requirements towards the end of the sessions.

Samsung recently introduced a new smartphone display with increased breaking resistance, which will probably be relevant for future cars as well. This example shows that subsystems, in general artefacts from former development processes can be relevant for subsequent projects. Their integration has to be planned, i.a. even before the original product is in the market and across branches. The research on supporting methods requires a suitable description model for this phenomenon. Research in design reuse and PGE – product generation engineering addresses this only partially yet. Design reuse focuses on the informational aspect, PGE refers primarily to reference products. This contribution aims at closing this gap as a basis for future research. Two case studies from industry projects by the authors and an example from foresight and product planning show the role of artefacts from former development processes in running projects. It is described which artefacts are used as a reference, why they are used and when. Based on these findings the authors propose the term “reference system” to depict the whole set of artefacts, which serves as a basis for every product development project.

Representation of territorial knowledge based on the ontology is an approach which explains the nature and reasoning of this knowledge for sustainability. This research proposes an ontology of domain according to the principles for modelling an ontology. This proposed ontology is named DOTK (descriptive ontology for territorial knowledge). DOTK ontology has specialized the entities of territorial knowledge for sustainability and its aim is enhancing the sustainable knowledge of actors within industries. This ontology is a guide for identifying an operational ontology of real example. This research show that ontology of domain can assist to the identifying of tangible and intangible resources of the local territory. So, these identified resources can help the industries and territory for sustainable objectives and improve the available territorial knowledge within local or regional industries.

Demands on developers are increasing due to the growing complexity of products in engineering. As many different disciplines are involved in planning the communication and data exchange becomes difficult. Systems engineering and especially the model-based development have proven themselves for this sector. However, the different languages for system modeling, such as SysML, offer considerable potential for optimization. A corresponding data model must be modelled so that data is available continuously and across all levels. Based on this data model, various engineering processes like risk management can be integrated into this model. New stereotypes are defined within SysML so that errors and risks can be implemented in the system model. This makes it possible to determine influences and effects that risks and errors have on other components of a product across all structures.

Global competition in combination with the increasing specialization of labor requires organizations to leverage their employees' competences. The approach presented in this paper empowers organizations to do so in two ways. First, we give employers a lean tool to allocate their employees to current and upcoming projects and make informed decisions whether they should take on new projects. Secondly, we provide the means to identify potential areas for innovation by identifying blind spots of technology transfer. The approach presented relies on semantic web technologies, i.e. an ontology built in OWL and SPARQL queries. To increase usability, we realized a user interface based on a semi-formalized spreadsheet and a python script for the transformation.

Vast amounts of information and knowledge is produced and stored within product design projects. Especially for reuse and adaptation there exists no suitable method for product designers to handle this information overload. Due to this, the selection of relevant information in a specific development situation is time-consuming and inefficient. To tackle this issue, the novel approach Intentional Forgetting (IF) is applied for product design, which aims to support reuse and adaptation by reducing the vast amount of information to the relevant. Within this contribution an IF-operator called Cascading Forgetting is introduced and evaluated, which was implemented for forgetting related information elements in ontology knowledge bases. For the evaluation the development process of a test-rig for studying friction and wear behaviour of the cam/tappet contact in combustion engines is analysed. Due to the interdisciplinary task of the evaluation and the characteristics of semantic model, challenges are discussed. In conclusion, the focus of the evaluation is to consider how reliable the Cascading Forgetting works and how intuitive ontology-based representations appear to engineers.