Knowledge-based Engineering Research Articles

From Requirements to Product: an MBSE Approach for the Digitalization of the Aircraft Design Process

AbstractDuring the aircraft conceptual design phase, many different design options need to be explored and compared in a short time frame. To speed up this process, efforts have been made in the past decades to digitalize parts of the design process, with a focus on the automation of the repetitive and non‐creative tasks inherent to the iterative design process. Whilst many of the newly developed methodologies focus on specific parts of the design process, a holistic model‐based design framework, incorporating the latest design technology developments, is lacking. To fill this gap, this paper presents the latest version of the Design and Engineering Engine (DEE) framework, originally proposed in the early 2000s and progressively matured through the experience of several international research collaborations. The DEE enables the setup and execution of Multidisciplinary Design Analysis and Optimization (MDAO) problems for aircraft (sub)systems, leveraging the automated, rule‐based modeling capabilities offered by Knowledge‐Based Engineering (KBE) and recent developments in the automatic formulation and integration of MDAO workflows. While the traditional MDAO process focuses on a given product architecture, the DEE allows also architectural design studies and makes use of Model‐Based Systems Engineering (MBSE) principles to address the whole design process, from requirements modeling up to the automatic verification of the requirements. In practice, the DEE provides a single conceptual framework or template from which specific design framework instances can be formulated and executed, according to the user's needs. This paper describes the DEE architecture and its implementation concepts. Furthermore, it demonstrates the application of the DEE template to four different scenarios, ranging from a simple requirement verification study, up to the simultaneous synthesis and optimization of an aircraft system and its production process, including multiple system architecture options.

Open Learning Environment for Multimodal Learning Based on Knowledge Base Technology

With the development of Internet technology, multimodal data have become the main data resource in the information age. Multimodal learning mode, as an education and teaching mode developed on multimodal data technology, provides more convenience for multimedia teaching. However, many challenges persist in its actual development and application. Currently, the multimodal learning model is susceptible to classroom noise, lack of teaching information, and other factors, which adversely affect multimodal data collection, teaching application, and achievement output. Thus, this paper optimizes the multimodal learning model in the open learning environment and takes 120 engineering students from a university in Guangxi Province as the research object. First, a sequential modal extraction method is proposed by constructing a multimodal probability generation model and then the data are modeled. Semi-supervised learning is then achieved by analyzing and combining the supervised and unsupervised learning processes. Finally, the knowledge base technology with information fusion characteristics is applied to the multimodal teaching mode. This teaching mode has been proven to improve students’ learning ability and learning achievement and teachers’ teaching effectiveness.

A Knowledge-Based Engineering System for the Planning of Networked Rainwater Harvesting and Distribution Systems

Rainwater harvesting attracts growing interest from the field of municipal planning. When considering a rainwater harvesting system as a design object, questions include whether the system is designed for a single property or for a local water network serving multiple properties, what allows for the inclusion of buffer tanks and resource balancing among participants in the network, how to size the tanks, and how robust the system is in the face of changing demands. Knowledge-based engineering provides methods and a tool set for such planning objects. For this article, the authors applied techniques based on model-based and resource-based configuration and Bayesian decision networks to propose a knowledge-based engineering system for residential, networked rainwater harvesting and distribution systems. This enables designers to investigate the effects of different catchment areas, adjust or minimize the storage tank sizes in the grid and evaluate their effect on the individual harvest and the exchange with a central network buffer, evaluate the demands within a neighborhood based on a detailed consumer model also over time, and test the sensitivities of the single sinks and sources to the water grid. For urban planners, this offers the possibility, for example, to make design obligations for housing construction or for the refurbishment of settlements.

Process Chain-Oriented Design Evaluation of Multi-Material Components by Knowledge-Based Engineering

The design of components suitable for manufacturing requires the application of knowledge about the manufacturing process chain with which the component is to be manufactured. This article presents an assistance system for decision support in the context of design for manufacturing. The assistance system includes explicit manufacturing process chain knowledge and has an inference engine that can automatically evaluate the manufacturability of a component design based on a given manufacturing process chain and resolve emerging manufacturing conflicts by making adjustments on the component or resource side. A link with a CAD system additionally enables the three-dimensional representation of derived manufacturing stages and manufacturing resources. Within the assistance system, a manufacturing process chain is understood as a configurable design object and is implemented via a constraint satisfaction problem. Furthermore, the required abstraction of manufacturing processes within finite domains can be reduced to the extent that necessary modeling resolution is achieved by incorporating empirical or simulative surrogate models into the CSP. The assistance system was conceptually validated on a tailored forming process chain for the production of a multimaterial shaft and provides added value, as valuable manufacturing information for component designs is automatically derived and made available in explicit form during the component development.

Knowledge-based engineering and computer vision for configuration-based substation design

Introduction: As the increase in electrification poses new demands on power delivery, the quality of the distribution system is paramount. Substations are a critical part of power grids that allow for control and service of the electrical distribution system. Substations are currently developed in a project-based and manually intensive manner, with a high degree of manual work and lengthy lead times. Substations are primarily sold through tenders that are accompanied by an inherent need for engineering-to-order activities. Although necessary, these activities present a paradox as tender processes must be agile and fast. To remedy this shortcoming, this article outlines a knowledge capture and reuse methodology to standardize and automate the product development processes of substation design. Methods: A novel framework for substation design is presented that implements knowledge-based engineering (KBE) and artificial intelligence methods in computer vision to capture knowledge. In addition, a product configuration system is presented, utilizing high-level CAD templates. The development has followed the KBE methodology MOKA. Results: The proposed framework has been implemented on several company cases where three (simplified) are presented in this paper. The framework decreased the time to create a 3D model from a basic electric single line diagram by performing the identification and design tasks in an automated fashion. Discussion: Ultimately, the framework will allow substation design companies to increase competitiveness through automation and knowledge management and enable more tenders to be answered without losing engineering quality.

An Ontology-based Engineering system to support aircraft manufacturing system design

During the conceptual design phase of an aircraft manufacturing system, different industrial scenarios need to be evaluated against performance indicators in a collaborative engineering process. Domain experts’ knowledge and the motivations for decision-making is a crucial asset for enterprises which is challenging to be captured and capitalised. Ontology-based Engineering (OBE) systems emerge as a new generation of Knowledge-based Engineering techniques with advancements of ontology engineering methods and computer science technologies. Ontologies enable to capture both explicit and implicit domain knowledge from historical records and domain experts. These Ontology-based Engineering systems can stand highly complex collaborative design processes involving multidisciplinary stakeholders and various digital tools. This paper proposes a tradespace framework with Ontology-based Engineering features included on top of existing Model-Based System Engineering and interoperability capabilities. These additional Ontology-based Engineering features reuse formalised knowledge via knowledge graph technologies and generative algorithms, changing the cognitive process from the designer, to an automatic process which generates design alternatives for the designer. The tradespace framework is demonstrated in a case study to design the aircraft fuselage orbital joint process, helping the designer to take better strategic decisions at conceptual phase and proving to be an advantageous paradigm for the design process.

An Ontology-Based Cost Estimation for Offsite Construction

Design for manufacturing and assembly (DfMA) has been widely applied to support the decision-making process in offsite construction. With a DfMA approach, cost estimation requires taking product design and production processes into consideration. Current studies conduct cost estimation built upon quantity take-offs. However, they do not provide a vocabulary to relate cost estimates to offsite construction processes. This paper presents a new domain ontology, Offsite Housing Ontology (OHO) using the NeOn methodology framework to support cost estimation considering products, resources, and production processes. OHO semantically defines offsite construction domain terminology and relationships. This supports a unified model, required for efficient collaborative design management. The efficiency and effectiveness of the OHO approach are demonstrated in a real-world DfMA scenario through the development of a Knowledge-Based Engineering tool to automate cost estimation. The approach can be adapted and extended to accommodate a very wide range of offsite housing, delivering important optimization and automation benefit from DfMA solutions.

CFD Investigations of Water Supply and Distribution Systems of Ancient Old and New World Archaeological Sites to Recover Ancient Water Engineering Technologies

New to archaeological studies is the field of paleohydrology characterized by the use of modern hydraulic engineering and computational fluid dynamics (CFD) analysis of ancient urban and agricultural water supply and distribution systems. Examples are presented in nine chapters of CFD investigations of old and new world archaeological sites (several of which are World Heritage sites) using FLOW-3D CFD software to bring forward new discoveries revealing the depth of ancient water engineers’ knowledge and creativity not previously noted in the archaeological literature. As modern analysis methods reveal technical details of ancient water systems, equivalent ancient technologies exist that were used in the design and operation of ancient water systems, albeit in formats, texts, and origins yet to be discovered. The nine chapters to follow present brief summaries of ancient sites’ water systems and the use of CFD and modern hydraulic engineering methods to discover the water engineering knowledge base used by ancient water engineers. Results are new revelations unknown in the current literature of ancient sites. Paleohydrology studies presented serve to add a further dimension to the history of ancient new and old world archaeological sites by bringing forward added details of water engineering projects accomplished by ancient engineers.

Aspects Regarding Knowledge-based Engineering

Knowledge management (KM) has become an effective way of managing organization’s intellectual capital or, in other words, organization’s full experience, skills and knowledge that is relevant for more effective performance in future. The paper proposes a knowledge management to achieve a competitive control of the machining systems. Then an application of Knowledge Management in engineering has been attempted to explain. The model can be used by the manager for the choosing of competitive orders.

Implementing Artificial Intelligence (AI) and Knowledge Based Engineering (KBE) in Ship Design: A Case Study Based on ACQUAINT

Implementing Artificial Intelligence (AI) and Knowledge Based Engineering (KBE) in Ship Design: A Case Study Based on ACQUAINT

Semi-Automated Design Workflow for Bolt Clamping Interfaces to Post-Process Additive Manufactured Parts

Metal additive manufacturing (AM) enables the production of complex and individualized designs. However, most AM parts require postprocessing with subtractive manufacturing processes, which can account for a significant percentage of the total manufacturing cost of an AM part. Positioning and clamping of complex AM parts within post-processing machines often lead to increased prestresses and reduced tool accessibility. One concept to address this problem is the integration of clamping interfaces in the part. But this leads to the new design challenge of optimal and material-saving placement of clamping interfaces on the part. To overcome this challenge new design tools are desired that facilitate this work and automatically generate the design of clamping interfaces.A recently developed clamping system uses bolts that are directly printed onto parts as clamping interfaces. These printed bolts and the clamping jaws of the system enable a unique spatial positioning and rigid clamping of AM parts for post-processing. This work introduces a design workflow that supports the positioning of bolts using a knowledge-based engineering (KBE) approach. The workflow thus allows the user to easily find a feasible clamping configuration and automatically generates the geometries of the bolt-shaped clamping interfaces. As input, the workflow uses the part geometry and an AM build direction. During the workflow, the user can modify the position of the clamping system relative to the part and find feasible positions for bolts. The bolt geometries are then generated automatically, and the part can be exported. This paper describes the workflow in detail and provides a vision for future developments of the tool and its potential for the AM process chain.

Sequential parameter optimization for algorithm-based design generation using data from multiphysics simulations

The implementation of algorithmic modelling in CAD technologies is an opportunity to reduce manual design work in repetitive design tasks. This increases the importance of design automation and digital workflows. This technology can process the results from computational fluid dynamics (CFD) and finite element analysis (FEA) automatically and can optimize designed geometries sequentially. Nevertheless, this design process often sets high computational requirements. The aim of this paper is to present a design automation workflow that reduces the computational time of a design process. The computational resource requirements of the system are reduced by using knowledge-based engineering techniques to obtain information from previous successful designs, decomposing the design into sub-parts according to their functions and optimizing each sub-part individually. Furthermore, through algorithmic modelling, the different input geometries required for the physical description of each simulation are made separately. This allows different design simplifications to be made for each simulation domain. Once the output of the simulations is obtained, the design is evaluated in CAD to optimize the geometry. After each sub-part has been optimized, the sub-parts are composed to obtain the final design. The case study of a reactor for methanol synthesis supports the results of this paper.

Technological Innovations and Allied Ethical Trepidations

Advancements in technology usually do not raise ethical or moral issues. Instead it is the application of these developments which raises some ethical questions; from the perspective of history, almost any use of a product of technological innovation can be made into a moral issue. Although the development of science and technology has a lot of advantages especially in the present context of knowledge-based technology, the questions of moral values and ethics are essential. Regardless of how well intended innovation and development of new technology have an ethical dimension. There is therefore, an increasing need for emphasis on the teaching of values, moral and ethics in institutions of higher learning alongside technical subjects. This paper examines the ethical implications in three broad thematic areas namely; information communication technology and the Internet, climate change and global warming and agricultural biotechnology. The paper therefore is an attempt to explore ways of minimizing the negative and adverse impact of science and technological advancement through ethical education in Kenya’s institutions. The paper is hinged on the concept of humanism in ethical philosophy which elevates the individual to the global level to preserve the environment and all therein. Ethical philosophy avoids possibilities for biological or nuclear conflicts, alleviates poverty, and faces the challenge of extremism, terrorism and intolerance. In other words, science and technological education should be guided by the humanism philosophy which is concerned with an ethical life. It emphasizes that human worthiness should be valued and technological innovations should be utilized while enhancing the dignity associated with the human person thus making novelty and scientific discoveries of greater value to humanity.

Цифровые технологии за границами хайпа: глобальный ландшафт

The paper discusses three key issues that play a special role in the development of strategies and policies for digital technologies: 1) particularities of digital technologies that greatly influence the principles and methodological approaches to the development of strategic documents, 2) drivers, main players and trends of global market, 3) trends in the accumulation of a technological knowledge base to provide competitive advantages to national companies in the short and medium term.

Six steps for building a technological knowledge base for future taxonomic work.

Abstract Species are fundamental biological units, but their discovery and delimitation requires appropriate data and methods. To better circumscribe species, we must improve our species concepts and bolster the underlying data resources necessary to enact them. Here, we provide six prescriptions for better collecting and synergizing our knowledge on species.

An ontology-based KBE application for supply chain sustainability assessment

Product Lifecycle Management (PLM) plays a key role in digital transformation demanded by Industry 4.0 and life cycle assessment, including sustainability assessment. Knowledge Based Engineering (KBE) applications can support PLM by integrating heterogeneous knowledge from different stages throughout the product life. However, the integration of knowledge from different stages and teams can cause misunderstanding if not represented in a unified form. Furthermore, different forms of knowledge used by different software are neither machine-readable nor human-readable, which also sets obstacles to knowledge integration in KBE applications. Supply chain sustainability assessment is such a scenario that entails integrating knowledge from different sources. This paper firstly implements a sustainability assessment method from other scholar to calculate the supply chain sustainability performance and adapts a sustainability assessment ontology for supply chain sustainability assessment. Then, an example KBE application is developed by implementing the sustainability assessment ontology and calculation method to simulate the knowledge sharing and integration between different teams. Finally, through this example application, it is discussed that the implementation of ontology to represent knowledge in PLM application for collaborative tasks like sustainability assessment can increase the efficiency of data sharing and integration. This paper is a proof of concept for the ontology-based framework. This framework can facilitate to represent knowledge but not create new knowledge, which means it can increase the efficiency of the software development, but can not provide a better calculation method and assessment framework for supply chain sustainability assessment. • An ontology-based application simulates the knowledge sharing and integration in sustainability assessment. • Ontology-based knowledge representation provides a unified and flexible data format. • Ontology-based knowledge representation makes a unified knowledge base possible. • Ontology increases the efficiency of data sharing and integration in collaborative tasks. • High-efficient software development contributes to supply chain sustainability management.

SpyPhage: A Cell-Free TXTL Platform for Rapid Engineering of Targeted Phage Therapies.

The past decade has seen the emergence of multidrug resistant pathogens as a leading cause of death worldwide, reigniting interest in the field of phage therapy. Modern advances in the genetic engineering of bacteriophages have enabled several useful results including host range alterations, constitutive lytic growth, and control over phage replication. However, the slow licensing process of genetically modified organisms clearly inhibits the rapid therapeutic application of novel engineered variants necessary to fight mutant pathogens that emerge throughout the course of a pandemic. As a solution to this problem, we propose the SpyPhage system where a "scaffold" bacteriophage is engineered to incorporate a SpyTag moiety on its capsid head to enable rapid postsynthetic modification of their surfaces with SpyCatcher-fused therapeutic proteins. As a proof of concept, through CRISPR/Cas-facilitated phage engineering and whole genome assembly, we targeted a SpyTag capsid fusion to K1F, a phage targeting the pathogenic strain Escherichia coli K1. We demonstrate for the first time the cell-free assembly and decoration of the phage surface with two alternative fusion proteins, SpyCatcher-mCherry-EGF and SpyCatcher-mCherry-Rck, both of which facilitate the endocytotic uptake of the phages by a urinary bladder epithelial cell line. Overall, our work presents a cell-free phage production pipeline for the generation of multiple phenotypically distinct phages with a single underlying "scaffold" genotype. These phages could become the basis of next-generation phage therapies where the knowledge-based engineering of numerous phage variants would be quickly achievable without the use of live bacteria or the need to repeatedly license novel genetic alterations.

Impact of Inventor’s Cooperation Network on Ambidextrous Innovation in Chinese AI Enterprises

With the intensification of artificial intelligence (AI) industry competition, innovation has become an important practical way for companies to achieve sustainable development. In this context, it is important to study the transmission paths affecting the development of ambidextrous innovation in AI firms from the perspectives of inventor cooperation networks and technological knowledge base variety. This study uses a sample of 399 of China’s AI organizations from 2008 to 2017. We explore the impact of an inventor cooperation network on ambidextrous innovation and dissect the mediating role of technological knowledge base variety between inventor cooperation network and ambidextrous innovation. We find that inventor cooperation network structural hole and centrality have an inverted U-shape relationship with a firm’s ambidextrous innovation. Additionally, inventor cooperation network centrality has a positive effect on technological knowledge base variety. In addition, there is an inverted U-shaped relationship between inventor cooperative network structure holes and technological knowledge base variety. Meanwhile, the research also finds that the unrelated variety of technological knowledge base mediates the relationship between the inventor cooperation network and ambidextrous innovation. The related variety of technological knowledge base mediates the relationship between the inventor cooperation network and exploitative innovation. However, the related variety of technological knowledge base cannot play a mediating role between inventor cooperation network and exploratory innovation.

Teachers’ cognitive beliefs about their assessment and use of tools when evaluating students’ learning of technological systems: a questionnaire study

In technology education, assessment is challenging and underdeveloped as it is a nascent practice and teachers do not have a well-defined subject tradition to lean on when assessing students. The aim of this study is to explore Swedish secondary technology teachers’ cognitive beliefs about assessing students’ learning of technological systems, in relation to the assessment tools they use. Data for the study were collected through a questionnaire which was completed by 511 Swedish technology teachers in lower secondary education (grades 7–9). The data were analysed statistically in three main steps. Exploratory factor analysis revealed underlying dimensions in teachers’ cognitive beliefs, which was followed by correlation analysis to discern associations between dimensions of cognitive beliefs. Finally, comparisons were made between groups of teachers to discern how teachers’ cognitive beliefs are influenced by their experience and educational background. The results show that additional education in the technology and engineering fields relates to more positive cognitive beliefs concerning teachers’ ability to assess students’ learning of technological systems. Teachers’ cognitive beliefs about assessment therefore did not primarily relate to the content of technological systems per se but to increased engineering and technology competence more broadly, which may indicate the importance of a comprehensive technological knowledge base in order to be confident in assessment. Furthermore, strong cognitive beliefs about assessment were connected specifically to local, regional and national technological systems, which are generally well-known and visible types of systems, and to the human, socio-technical dimensions of the systems. Cognitive beliefs about knowledge for assessment were also associated with positive attitudes to assessment tools that followed the formative tradition, which may be explained by the prevalence of procedural epistemic practices and modelling in the design and understanding of technological systems. Technology teachers would need additional in-service courses in engineering to broaden their knowledge and increase their cognitive beliefs about assessment. Formative assessment should also be preferred, and it might be appropriate to begin teaching and assessment with well-known local and regional infrastructural systems with a clear socio-technical dimension.

Entity alignment based on relational semantics augmentation for multilingual knowledge graphs

Seeking similar entity pairs pointing to their counterpart real-world objects in knowledge graphs (KGs) is one of the most challenging and critical steps for entity alignment (EA), also known as KG integration. EA has prompted the development of knowledge-based technologies such as recommender systems, semantic search engines, chatbot systems, and knowledge reasoning. Recent years have witnessed increasing interest in representation learning-based entity alignment methods. Most of these represent different KG entities as low-dimensional vector embeddings via their neighborhood structure and then find counterpart entities by estimating the similarities between entity representations. However, most of the studies on the mainstream methods for entity alignment have paid little attention to abundant information on entity one-hop bidirectional neighbors and relational semantics centrality in KGs. Due to the heterogeneity of the knowledge graph, it is difficult to achieve satisfactory alignment results for entity alignment methods based on structure encoding. This paper investigates multilingual entity alignment strategies and proposes a novel relational semantics augmentation (RSA) model to alleviate these issues. RSA can fuse the entity’s bidirectional neighborhood path information and their connected relational semantics contexts. Comprehensive experiments on five benchmark EA datasets with the comparison of state-of-the-art entity alignment methods demonstrate the better performance of our RSA model.