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Innovative design of complex systems faces multi-contradiction (MC). The existing methods to solve MC are mainly based on the General Theory of Powerful Thinking (OTSM) which is independent of the classical Engineering Design Method (ED) to form the process model, they cannot inherit the accumulated knowledge and advantages of ED. This paper proposes a product innovation design process model for MC based on the function-structure model. It starts with an initial scenario of the system to build the function-structure model and MC network based on the root contradiction analysis. The network structure entropy and function importance decision methods are introduced for the trimming target confirming. The key contradiction-node is identified and solved by strategies of trimming based on internal and external resources of the system. The function-structure model in ED and trimming in TRIZ are combined to form an innovative design process for MC systems. The proposed method is evaluated in a case study of an innovative design of the girder bridge erector. [ABSTRACT FROM AUTHOR]

The article announces that "Multifaceted Assessment of Ideation: Using Networks to Link Ideation and Design Activity," by Philip Cash and Mario Štorga was selected by the "Journal of Engineering Design" as recipient of the Best Paper Award for 2015.

The physical construct of a dual ontological product is essential for those products which physically interact directly with humans, whereas the product's emotional construct interconnects with human cognition. Multitude of human factor aspects must be considered when designing dual ontological products. To increase the product's impact and reach, designers should also understand the requirements of potential users. Designers find it difficult to achieve the right compromise between these constructions. This research therefore contributes a novel harmonistic knowledge-based computational support tool which makes designers aware of design stage conflicts and consequences of commitments made on human factors in the use phase of the artefact. This paper describes in detail the machine learning and harmonistic knowledge-based system which exploits information collected directly from potential users to proactively assist, guide, and motivate product designers. The paper takes the motorcycle artefact as a case of dual ontological product. The prototype support tool has been evaluated with 28 motorcycle design engineers. The results obtained from this evaluation have shown that the approach and design computational-based tool meet their goals, are beneficial, and are required in design engineering practice. [ABSTRACT FROM AUTHOR]

Traditional approaches to managing uncertainties during product development often lead to increased complexity and resource consumption. This paper introduces the concept of ‘resilient objects’ as an alternative solution, designed to provide passive protection against disruptive events of different kinds, thereby reducing the necessity for complex margins at system interfaces. The paper illustrates the concept of resilient objects through practical examples, which demonstrate the objects’ ability to uphold system functionality even when faced with unexpected disruptive events. By embodying resilience locally in areas of the system that are most susceptible to uncertain conditions, resilient objects offer the potential to minimise interface margins and thus the need for excessive system over-design. The concept of resilient objects offers a new perspective on how to solve the trade-offs between resilience and complexity when addressing uncertainties in the dynamic landscape of product development. [ABSTRACT FROM AUTHOR]

It is often computationally intensive to solve combinatorialoptimisation problems due to the inherent large solution space. These problems are commonly observed in the fields of engineering system design and operations. Traditional techniques are limited in handling the growing complexity and size of these problems efficiently. This paper presents a twofold update quantum-inspired genetic algorithm to solve combinatorial optimisation problems. It is generalised as an improved version of quantum-inspired evolutionary algorithm. The paper proposes a new problem formulation and the solution procedure for quantum-inspired evolutionary algorithms. An improved quantum-inspired genetic algorithm is proposed with a twofold update mechanism along with various operators. The proposed method is applied to solving a real-life engineering system optimisation problem of modular design. The results are compared using a classical genetic algorithm versus a quantum-inspired evolutionary algorithm, indicating that the proposed method outperforms the traditional methods and is more robust and more efficient. [ABSTRACT FROM AUTHOR]

Behavioural economics and nudge theory have attracted much attention for engineering design in a broader context of sociotechnical systems, which provides new perspectives for engineering design when systems have interactions with human. This paper deals with service system design with a particular application to smart tip nudging. The conventional tip nudging approach that uses a set of default tip options lacks context-awareness and sometimes suggests inappropriate tip options. To address this problem, and to also increase tip revenues potentially, this paper proposes a smart tip nudging mechanism based on prospect theoretic modelling of customer tipping behaviours. The model proposes to use joint prospect values of both customers and service providers, which mimics the trade-off that customers make between their own economic gains and losses and the service provided by service providers. Meanwhile, this study provides a data-driven approach to parameter estimation of the prospect theory model, and it enables tip nudging to be context-aware for tip option adjustment by using intelligent reasoning techniques. One field experiment is conducted to validate the proposed system. [ABSTRACT FROM AUTHOR]

The traditional practice of value-driven engineering and systems design is mainly based on net present values (NPVs). It is essentially enacted as a budgetary technique that neglects the future risk and strategic flexibility of a design project. Incorporating real options theory in value-driven decision models can improve the inability of NPV analysis in dealing with the upside potential of managerial flexibility and operational uncertainty over the design project life. This paper examines the critical issues and research opportunities for establishing a theoretical foundation of value-driven multiplayer game decision making in large complex engineering and systems design projects. This paper envisions a research framework for value-driven cooperative negotiation by synthesising the mathematical foundations of utility theory, real options theory and game theory into a coherent framework of design decision analysis. Fundamental issues and research directions are discussed to develop a variety of new methods for enhancing the formulation of value models for value-driven design with decision support to achieving equilibrium solutions with optimal value allocation among multiple decision agents involved in engineering and systems design. [ABSTRACT FROM AUTHOR]

Engineering companies face the challenge of optimising margins within product platforms while balancing individual product optimisation and maximising platform commonality. Key obstacles include organisational silos, diverse design variables, design space allocation, and varying time perspectives. This paper proposes a value-based modelling methodology that integrates both internal and external variety within the manufacturer. Using an automotive Head-Up Display (HUD) case study, we demonstrate how to effectively utilise platform margins to maximise technological variety and minimise internal variety, thereby enhancing long-term system value. This approach helps design teams understand the implications of their decisions, optimise platform margins to meet evolving technological demands, reduce costs, and maximise value. Our findings advance the understanding of margin optimisation in product platforms and support informed decision-making for engineering companies facing conflicting objectives. [ABSTRACT FROM AUTHOR]

Knowledge transfer in engineering design activity involves effectively applying prior practical experience in novel contexts. While related works fostering knowledge transfer focus on educational practices and experience generalisation, recent advancements enable us to analyze its complex cognitive processes using neuroimaging technology. This paper proposes a multimodal approach for facilitating knowledge transfer in engineering design, utilising functional near-infrared spectroscopy (fNIRS) and eye-tracking technologies based on neurocognitive profiling. We conducted knowledge transfer experiments using mixed and extended design tasks. Meanwhile, The analysis focused on gaze duration, gaze counts, brain region activation levels, functional connectivity, and effective connectivity of the participants. Finally, we employed stepwise linear regression to identify significant and potential associated factors of knowledge transfer. By combining eye-tracking predictors and brain network predictors, a multivariate linear discriminant analysis (LDA) significantly differentiated between participants in near-transferred and far-transferred states, achieving an accuracy of 91.16% using leave-one-out cross-validation. The ‘basic-supplementary-target task’ method effectively improved the knowledge transfer performance by 27.6%. Our findings demonstrate the efficacy of the proposed multimodal approach in facilitating knowledge transfer in engineering design activities. [ABSTRACT FROM AUTHOR]

During recent decades, there has been growing awareness of human safety in the design process. The purpose of this paper is to review the literature on design for human safety (DfHS) in manufacturing systems. To this end, a process for systematically reviewing DfHS studies was used. The authors focused in particular on the applications of design theories and methodologies (DTM) and design tools and techniques (DTT) to analyse and identify work situations in order to improve human safety in manufacturing system design. The authors also tried to identify the design phases in which these DTM and DTT could be applied. This research review covered papers published between 1980 and 2015, and combined seven groups of terms: DfHS, design, safety, DTM, DTT, risk and working situation. A critical analysis was also performed in view to defining a research agenda and the most prominent key actions capable of pointing out paths for future research. [ABSTRACT FROM PUBLISHER]

This paper presents a systematic literature review aimed at assessing how well current technology-based interventions that focus on dementia and other cognitive impairments align with the principles of the P4 vision for healthcare: Predictive, Preventive, Personalised and Participative. A search of the SCOPUS database yielded 887 articles, of which 48 were ultimately selected for analysis. Looking at whether and how each intervention implements each 'P'-principle, our results suggest a partial and non-systemic embrace of the P4 vision. Reasoning on possible explanations for this state-of-the-art, we propose that our findings represent an opportunity for the engineering design community to engage with P4-based healthcare delivery models through the development of design frameworks, new indicators for assessing the success of such healthcare delivery models, as well as tools and methods. [ABSTRACT FROM AUTHOR]

Despite the existence of several methods and tools for engineering products and services, the Product-Service Systems (PSS) design field still lacks some pragmatic support. This paper assumes the existence of a gap between the existing approaches and logics used in product and service engineering that challenges the product-service integration in PSS design. To better support product-service integration in PSS, this paper proposes a system-based conceptual framework for PSS engineering. The framework is based on a system concept that defines products and services as ‘subsystems’ sharing similar properties. The conceptual framework supports the PSS design progression process by integrating and coupling product and service engineering viewpoints. Its aim is to support the engineering process of an entire system until reaching the most detailed phases. The main point of interest of the proposed approach is the specific light it shines on product and service engineering logics and its ability to unify disjoint definitions and processes by proposing a communication basis via a system-based framework. [ABSTRACT FROM PUBLISHER]

Unplanned design iterations are considered one of the reasons for the high failure rate of new product development (NPD) projects. Generally, organisations employ 'proactive risk management' (PRM) and 'reactive fast learning' (RFL) to manage unplanned design iterations. This paper aims to explore how organisations employ PRM and RFL approaches to manage unplanned design iterations in the NPD process. To that end, a cross-sectional interview study was conducted in eight organisations. The interview transcripts were analysed as a primary data source using thematic qualitative text analysis technique. For PRM approach, results demonstrate that the design teams were more active in risk monitoring in the design phase as compared to risk identification in the concept development phase. Generally, design teams reduced the likelihood of unplanned design iteration risks by employing learning methods in addition to risk mitigation strategies. For RFL approach, results reveal that organisations lacked a structured approach to select suitable learning methods for fast resolution of unplanned design iterations and to convert new knowledge into organisational learning. We conclude that PRM is more established as compared to RFL in managing unplanned design iterations. We develop recommendations of how organisations can use RFL approaches more efficiently alongside PRM approaches. [ABSTRACT FROM AUTHOR]

Novel design creations often exist in the form of patents. It is well acknowledged that patents are a great source of design inspiration, therefore designers are encouraged to engage patents early in the design process. Studies of patent analysis have been carried out to benefit engineering design activities such as patent classification, technology forecasting, idea generation and emerging design-prior art comparison. However, the design intent behind inventions has received little attention in patent analysis. Designers can gain better design insight by looking at a patent from a systematic perspective starting from design intent to principal solutions. In this paper, an approach is proposed to extract and link the knowledge conveyed within patent descriptive sections to typical early engineering design stages, namely Motivation, Specification and Structure. This knowledge is then conceptualised into TRIZ engineering parameters and reconciled functional basis to enable cross-patent analysis. When compared to expert analysis, the proposed approach achieves an average of 63% accuracy with respect to Motivation, 56% with respect to Specification function and 44% with respect to Specification flow. Potential applications of such linking for early design use are then demonstrated through a prototype knowledge network. [ABSTRACT FROM AUTHOR]

With the support of advanced information and communication technologies and open innovative design platforms, the emerging and blooming paradigm of mass personalization drives the process of engineering design to include knowledge with higher heterogeneity and more complex modalities. To this end, Multi-Modal Knowledge Graphs (MMKG), evolved from semantic networks and knowledge graphs, provide a powerful technology system for more effectively organizing and utilizing this knowledge. To understand the state-of-the-art of key aspects that enables MMKG, and recognize the potential challenges for forefront applications in engineering design, a literature review of MMKG-related publications is conducted. With selected 131 representative papers together with other 32 supplementary studies (up to 11/11/2023), this article summarizes the technical and practical efforts of multi-modal knowledge extraction, fusion technology, and specific applications in the engineering design process. Meantime, the challenges that MMKG faces and its foreseeable development potentials are discussed, which is hoped to provide a basis for the futuristic explorations and implementations of MMKG-enhanced availability and productivity in engineering design. [ABSTRACT FROM AUTHOR]

Engineering equipment can efficiently assist humans in completing engineering projects and reduce work intensity. As the difficulty and scope of operations increase, higher requirements are placed on function and integration. In product design, excessive user requirements and design constraints lead to discrete results, difficult to converge. Under multi-functionality and high integration constraints, traditional mapping sub-functions to structures one by one results in overabundant mappings, and discrete, redundant structures after mapping, poorly achieving integration and reducing subsequent iteration efficiency. To address these issues, this paper proposes a conceptual design methodology for engineering equipment with function units configuration and schemes iterative solution. First, the Fuzzy Quality Function Deployment (FQFD) method applies fuzzy theory to requirement-to-function conversion, overcoming ambiguity and subjectivity of user requirements. Second, with the goal of integrated structures, an improved FBS method, i.e. Function-Function Units-Structure (FFUS), aggregates sub-functions after decomposition into function units, and then maps to structures, improving engineering equipment integration. Moreover, the Interactive Genetic Algorithm (IGA) method involves users in an interactive process to generate an optimised design scheme, overcoming blind solution generation. Prototype design and simulation of 8VN1 Gas Insulated Switchgear (GIS) handing equipment demonstrate that the methodologies are effective in aiding engineering equipment conceptual design. [ABSTRACT FROM AUTHOR]

Additive Manufacturing (AM) has become an established discipline in both research and education. However, to achieve its full potential AM requires a step-change in design thinking, which makes Design for AM (DfAM) education and training crucial. This paper reports results from the first attempt to investigate the uptake of DfAM in higher education. This research required the development and administration of an articulated online survey, in which educators worldwide who teach AM and DfAM have participated. The results show that DfAM is taught in a considerable number of courses. However, the survey revealed that DfAM is seldom recognised as a distinct course or topic and the relevance attributed and proportion of teaching dedicated to DfAM within wider AM is typically marginal. DfAM is being mostly taught in North America and Europe and is also typically taught in institutions that are research active in AM or specifically DfAM, suggesting the subject has not yet reached maturity or diffusion into mainstream design and engineering curricula. It was interesting to find that currently, the contents of courses do not differ significantly between engineering and design programmes. [ABSTRACT FROM AUTHOR]

Two kinds of design ideation process may be distinguished in terms of the problems addressed: (i) solution-focused, i.e. generating solutions to address a fixed problem specifying a desired output; and (ii) exploratory, i.e. considering different interpretations of an open-ended problem and generating associated solutions. Existing systematic analysis approaches focus on the former; the literature is lacking such an approach for the latter. In this paper, we provide a means to systematically analyse exploratory ideation for the first time through a new approach: Analysis of Exploratory Design Ideation (AEDI). AEDI involves: (1) open-ended ideation tasks; (2) coding of explored problems and solutions from sketches; and (3) evaluating ideation performance based on coding. We applied AEDI to 812 concept sketches from 19 open-ended tasks completed during a neuroimaging study of 30 professional product design engineers. Results demonstrate that the approach provides: (i) consistent tasks that stimulate problem exploration; (ii) a reliable means of coding explored problems and solutions; and (iii) an appropriate way to rank/compare designers' performance. AEDI enables the benefits of systematic analysis (e.g. greater comparability, replicability, and efficiency) to be realised in exploratory ideation research, and studies using open-ended problems more generally. Future improvements include increasing coding validity and reliability. [ABSTRACT FROM AUTHOR]

The formal representation and capturing of uncertainty knowledge are always essential but difficult. Typically, the uncertainties due to incompleteness and inaccuracies of model information in engineering design necessitate the designing of robust decision workflows to improve the quality of process/product in variations. This requests extending a designer's abilities in managing various uncertainties in system design and making decisions that are robust, flexible, and comprehensive. To enable the management of various uncertainties, in this paper, we propose an ontology for robust design and a template-based ontological method that is employed to design decision workflows. We achieve the aforementioned goals through the identification of: (1) procedural knowledge – defining a procedure of designing robust decision workflows, including the sequence of activities, to determine the right combination of design information for a specific type of uncertainty, and (2) declarative knowledge – developing a frame-based ontology for the formal representation of tacit knowledge to capture and document the re-usable information of a robust design by utilising the process templates. We demonstrate the efficacy by carrying out the robust design of the hot rod rolling process based on the analysis and synthesis of the processing-microstructure (cooling module) and the microstructure-mechanical (rod module) simulation models. [ABSTRACT FROM AUTHOR]

Decision-making methods have proven to be an effective support to engineering design. However, it is proved that very often designers prefer tested procedures and experience-based approaches. Many reasons have been discussed in the literature, dealing with consolidated design habits of people and companies, high cost in terms of time consumption, and lack of tools and knowledge. The paper systematically investigates, through an extended critical review, how decision-making methods can be used by automotive designers to solve the most common engineering problems involved along the design process. In particular, the paper proposes an original classification of the most widely used decision-making methods in engineering design, a match between such techniques with the typical design phases, and a mapping of their application into the automotive field. This research can be considered as a further step to transfer the state-of-the-art knowledge on decision-making methods to the industrial context, establishing a common background for practitioners and researchers. [ABSTRACT FROM AUTHOR]

This paper focuses on the engineering design of modular systems in the manufacturing industry, in which companies can benefit from modular and configurable products that fulfil a variety of customer needs. The purpose of this paper is to study the types of challenges faced in the engineering design of modular systems and the types of support needed to address these challenges. The topic is studied via a literature review and seven industrial case studies. The analysis method for the case studies combines engineering and business perspectives. The engineering perspective highlights engineering concepts related to designing modular systems, while the business perspective focuses on related managerial issues. We find that the studied companies emphasised different aspects of modular system development, despite having similar high-level goals related to the benefits of modularity and design reuse. We also identify several challenges, along with the need for support related to the engineering design of modular systems in the manufacturing industry. Current engineering design practices related to modular systems are not sufficient to generate the typical benefits related to modularity and design reuse; organisations must also focus on other aspects of the design process, such as knowledge retrieval. [ABSTRACT FROM AUTHOR]

This paper demonstrates a general iterative technique for discovering a taxonomy that categorises information contained within a weakly structured design project archive. It is common for large engineering organisations to maintain archives about past design projects. In principle, engineering organisations could mine these archives to extract useful lessons and relationships that would improve future design projects. However, this is difficult in practice, since archives often consist of weakly structured data formats, such as plaintext documentation. This restricts the use of many useful analysis tools. The taxonomy-discovery process presented here is a critical first step towards unlocking the value of such archives. The technique is based on methods from the qualitative research literature. We demonstrate this process by creating a taxonomy of risk-mitigating actions in design projects based on a design project archive from a large engineering organisation. We discuss practical considerations such as missing contextual information as part of the case study. The taxonomy is sufficiently generic to be of use to other organisations. Furthermore, individual organisations can use the iterative technique introduced in this paper to tailor the taxonomy to their own project archives. Thus, this research provides an important foundation for unlocking the value of archived design project information. [ABSTRACT FROM AUTHOR]

In spite of the increasing importance placed on the creation and delivery of value, it is unclear what value is and how it is determined in design. In this paper, the first descriptive model of value determination (ValueD) is presented to clarify the key elements and mechanisms involved. ValueD describes value determination as a cognitive process that is situated and dependent on an agent's knowledge. The variables involved are: an entity interpreted by an agent; a situation of an agent; knowledge of an agent; a criteria prioritisation activity; a criteria selection activity; and a criteria judgement activity. The output of the value determination process is a value statement. Value is shown to refer to a judgement on the extent an interpreted entity satisfies an agent's criteria. The ValueD model is evaluated through comparison against seven axioms of value and a protocol analysis of an engineering design episode. The article concludes with a discussion of strengths, limitations, and future work on ValueD, and its relationship with key value concepts such as added value, exchange and perceived value, benefit, and need. [ABSTRACT FROM AUTHOR]

Engineering design automation has been an active field of research and application for more than five decades. Despite a multitude of available methods stemming from research fields such as Knowledge-Based Engineering (KBE) and Computational Design Synthesis (CDS) the application context in industry is mostly limited to routine tasks. Here we propose a means to foster the transition of academic methods to industrial practice through a comprehensible and comprehensive design automation task categorisation that allows practitioners to grasp the opportunities state-of-the-art design automation offers. The categorisation is based on a critical investigation of 77 papers stemming from KBE and CDS, respectively, and is detailed with respect to knowledge needed for complete formalisation of a task, i.e. inputs, outputs and goals, as well as available automation methods. A thorough discussion indicates the context of the work with current design practice and provides a consolidation of the research fields KBE and CDS including the derivation of technological requirements for design automation task definition by practitioners. Thus, this paper contributes not only by consolidating two research fields but also by presenting technological requirements for further streamlining the process of realising design automation applications in industry. [ABSTRACT FROM AUTHOR]

Function modelling is proposed in textbooks to support solution finding early in a development process. Although it has great potential to support the comprehensiveness and systematisation of conceptual design, it has been taken up in design practice only to a limited extent. Based on a literature review, potential barriers hampering its widespread application are discussed. A central problem revolves around the abstract nature of function modelling, which makes it difficult to apprehend the concrete benefits from its implementation. The article contributes to related research by showcasing success stories in the implementation of function modelling in six companies. The implemented models include morphological charts, use case modelling and two approaches developed in-house. The paper presents an interview study with managers and design leaders investigating the motivations and reasons leading up to the decision to newly implement function modelling in the companies. Furthermore, the paper explores the interviewees’ reflections on experiences gained while (gradually) implementing function models, the specific advantages attained, and also the challenges faced in doing so. The findings show that shared function modelling has great potential to support interdisciplinary collaboration and comprehension and to lead to a significant increase in the efficiency of the design process. [ABSTRACT FROM PUBLISHER]

Many engineering design optimisation problems are multi-objective and subjected to multiple constraints. These problems may encounter uncertainties in their inputs, which may cause uncontrollable variations in the objectives and constraints. Multi-objective robust optimisation (MORO) approaches aim to obtain Pareto solutions with the least sensitivity to uncertainties. In this paper, an improved sequential MORO approach considering interval uncertainty reduction under mixed uncertainties (SMORO-IM) is proposed. Firstly, it adopts the efficient sequential optimisation framework based on the worst possible point constraint cuts. Secondly, a formulation for obtaining robust optimal solutions under mixed interval and probabilistic uncertainties is employed. In addition, considering that the interval uncertainties in inputs can be reduced at allowable cost, the cost of interval uncertainty reduction is defined as an extra objective function in the proposed approach, aiming at obtaining optimal solutions with different interval uncertainties. Two numerical examples and two engineering cases are used to illustrate the effectiveness of the proposed SMORO-IM approach. The objective and feasibility robustness of the obtained optimal solutions are verified by the Monte Carlo Method. [ABSTRACT FROM AUTHOR]

The increasing complexity of engineering activities emphasises the need to enhance software support for design team collaboration and improve the management of design process dynamics, especially in critical situations. Thus, this paper proposes a new approach in which a set of Coloured Petri Nets (CPNs) enable a practical implementation of design activities ontology by modelling rules and relationships simultaneously with the instantiation of taxonomy elements. The development of the proposed model is based on an in-depth analysis of several long-lasting development projects in a large industrial company and three case studies on designers' collaboration. To facilitate the implementation of ontology models into industrial practice, this work focuses on the issues of interoperability between design support systems and ontology models. The proposed method has significant potential to provide real-time updating and propagation of design information in teamwork. [ABSTRACT FROM AUTHOR]

As engineering applications require management of ever larger volumes of data, ontologies offer the potential to capture, manage, and augment data with the capability for automated reasoning and semantic querying. Unfortunately, considerable barriers hinder wider deployment of ontologies in engineering. Key among these is lack of a shared top-level ontology to unify and organise disparate aspects of the field and coordinate co-development of orthogonal ontologies. As a result, many engineering ontologies are limited to their scope, and functionally difficult to extend or interoperate with other engineering ontologies. This paper demonstrates how the use of a top-level ontology, specifically the Basic Formal Ontology (BFO), greatly facilitates interoperability of multiple engineering-related ontologies. We constructed a system of formal linked ontologies by re-engineering legacy ontologies to be conformant with BFO and developing new BFO-conformant ontologies to capture knowledge in the engineering design, enterprise, human factors, manufacturing, and application domain of additive manufacturing. The resulting Integrated Framework for Additively Manufactured Products (IFAMP), including the body knowledge instantiated on its basis, serve as the basis for a proposed Design with Additive Manufacturing Method (DWAM), which we believe can support the design of innovative products with semantically enhanced ideation tools and enhanced access to application domain knowledge. The method and its facilitation through the ontological framework are demonstrated using a case study in medicine. [ABSTRACT FROM AUTHOR]

Product design becomes more than just dealing with pieces of hardware, but rather is realised through co-design of an entire product ecosystem, involving coordinated product fulfilment, services, experiences and human satisfaction at the individual and the community levels (Jiao et al. [4]). I Design education i , including design education and pedagogy in engineering; design thinking and design doing; complex sociotechnical systems; public policy design; design engineering epistemologies; design learning mechanisms and learning systems; design ethics; design diversity, equity and inclusivity; as well as design education assessment methods, instruments, and metrics. I Design of product realisation systems i with focus on planning, optimisation, control and management of processes, fulfilment and systems, including systems design and design complexity; integrated engineering design development; manufacturing systems design; design for changeable and reconfigurable production systems; supply chain design; design for logistics; operations engineering design; service delivery system design; integrated product and process development; global and distributed engineering design; and multi/inter/trans-disciplinary engineering design. The subject matter of design has traditionally been focused on design of engineered (e.g., physical/mechanical) products. [Extracted from the article]

This paper identifies, describes and classifies a comprehensive collection of variation reduction principles (VRP) that can be used to increase the robustness of a product and reduce its variation in functional performance. Performance variation has a negative effect on the reliability and perceived quality of a product and efforts should be made to minimise it. The design principles are identified by a systematic decomposition of the Taguchi Transfer Function in combination with the use of existing literature and the authors’ experience. The paper presents 15 principles and describes their advantages and disadvantages along with example cases. Subsequently, the principles are classified based on their applicability in the various development and production stages. The VRP are to be added to existing robust design methodologies, helping the designer to think beyond robust design tool and method application, towards forming product variation management strategies. [ABSTRACT FROM PUBLISHER]

An introduction is presented in which the editor discusses various reports including the link between interaction and the industry contexts, one on user response, and the factors that lead to object attachment.

In this study, we envision engineering design activities for collective computing, an upcoming era of complex systems of massive social interaction through a wide variety of connected computing devices. A literature review reveals how collective computing, compared to the previous eras of personal and ubiquitous computing, may lead to new design tasks and design processes, as well as new roles for designers. Based on this review, new design activities for the collective computing era are envisioned, and further revised in an interview study with 24 informants. The result is a vision for design in the collective computing era, with actionable guidance for designers in terms of a coherent set of new design activities proposed in relation to advances in computing. [ABSTRACT FROM AUTHOR]

Systematic design methods are widely diffused in academia, representing a standard in many engineering courses. Nevertheless, some flaws related to the conceptual design phase have been ascribed to these methods, especially concerning a non-comprehensive support to innovation. However, literature acknowledges several creativity-enhancing tools that can be conveniently combined with systematic design methods. In particular, many scholars refer to TRIZ, i.e. the well-known Russian problem-solving theory. Moreover, recent literature contributions propose some alternatives to the classical Functional Decomposition and Morphology (FDM), claiming to overcome some of the related flaws. One of them is the Problem Solution Network (PSN) approach, i.e. a systematic conceptual design method strongly based on a problem-solution co-evolutionary logic. In this context, our work aims at combining the potentialities of TRIZ with the benefits claimed for the PSN, by proposing a comprehensive integration procedure. Accordingly, this paper reports a detailed description of the proposal, where TRIZ tools are exploited to support problem solving within the PSN approach. Furthermore, an application is also reported where an industrial case study is presented to argue about possible potentialities and lacks of the proposed approach. [ABSTRACT FROM AUTHOR]

Mechanical designers strive to create a simple design that will reduce product's cost and increase its reliability. This paper presents an experimental method for measuring the simplicity of a mechanical design. It also presents a quantitative metric for evaluating the simplicity of product design based on quantifiable design parameters. The simplicity metric was developed by using experts’ evaluations of functionally equivalent products. The dominant parameter for predicting an expert's simplicity rating is the number of features required to fully define the examined computer-aided design (CAD) model. This parameter is highly correlated with two additional measured design parameters: number of parts and number of interfaces between parts. [ABSTRACT FROM PUBLISHER]

Human factors/ergonomics (HFE) can make great contributions to product design (PD). This paper presents a cross-sectional study conducted at the Federal University of Santa Catarina (UFSC), located in Florianopolis, SC, Brazil, with the students of the engineering department in order to assess their understanding of HFE and its use by students in PD. The results showed that 70.3% of students do not apply HFE in PD and it has no correlation with the fact of taking an HFE class or with the PD methodologies they use. Because of that, it presented an analysis of the approach of HFE in the PD methodologies known by the students, clarifying that these methodologies do not provide proper support for the HFE application. [ABSTRACT FROM AUTHOR]

Cradle to grave product support has been a key issue in the engineering sector over many years, particularly because product engineering legacy knowledge is often lost during the product development process unless rigorously captured in some way. This is particularly the case during formal design reviews at any point during a product's lifecycle where engineering changes are not fully documented or where salient but important aspects of decision making are difficult to document explicitly. Though many software systems are available to support design reviews, they have not necessarily met the expectations of industry. Consequently, traditional knowledge capture methods tend to be time-consuming, costly and disruptive leading to many companies simply giving up on this crucial aspect of product development. This paper presents research carried out with regard to prototyping and testing a potential knowledge engineering capture and reuse solution, demonstrating real-time user-logging using virtual design environments focused on team-based design ‘reviews’. Called the Virtual Aided Design Engineering Review (VADER) system, it provides millisecond precision time-phased knowledge capture in an automatic and unobtrusive manner. Both structured and unstructured data are synthesised via a ubiquitous integration and temporal synchronisation (UbiITS) framework that enables interactive information mapping, retrieval and mining. VADER's frontend includes a virtual reality based 3D model view display as a multiuser collaborative interface and an auxiliary web interface for concurrent access by multiple distributed users during product design discussions. Feedback from engineers using the system demonstrated that this concept is one which believe would substantially enhance their engineering task knowledge capture, rapid retrieval and reuse capability. It was also surmised that, if required, such a system can be extended throughout the whole product development process capturing individual and team-based engineers’ inputs across the whole cradle-to-grave product life cycle. Also, due to its generic nature, this approach is not limited only to engineering applications or virtual environments but can potentially be used in other sectors using computer-based technologies of any kind. [ABSTRACT FROM PUBLISHER]

Communication between people is commonly thought to play a major role in determining the success or failure of collaborative design projects. We conducted 8 weeks of observation and 62 interviews in three design companies. Our findings indicate that communication is blamed for causing many problems which are not of obvious technical nature. However, such problems are more often symptomatic of underlying factors related to information, representation, individual, team, and organisational issues. Examples of factors influencing communication at interfaces are people's understanding of the 'sequence of tasks' or 'goals and objectives' in the design process. With a system-theory informed conceptualisation of communication, we propose that awareness of such factors could assist design practitioners in targeting interventions and researchers in generating hypotheses about communication and design performance. [ABSTRACT FROM AUTHOR]

In the field of design, novelty is widely acknowledged as a key parameter for creativity assessments. Accordingly, scholars have proposed several definitions, metrics and procedures to assess novelty for different purposes. Although the availability of many alternatives allows researchers to perform in-depth investigations, it makes the orientation among the available combinations of novelty concepts, types and metrics quite hard. In such a manifold context, the aim of this work is to map the literature about novelty assessment in engineering design. To this purpose, a systematic literature review has been performed on the Scopus database to identify a relevant set of contributions through specific search strategies and skimming processes. A map of novelty metrics has been obtained, which shows that most of them belong to the uncommonness type, while others need further investigations. The obtained results are intended to support scholars in browsing the different metrics, when selecting the most suited for their specific research objectives. [ABSTRACT FROM AUTHOR]

Recent developments in engineering design management point to the need for more dynamic, fine-grain measurement approaches able to deal with multi-dimensional, cross-level process performance in product design. Thus, this paper proposes a new approach to the measurement and management of individual and teamwork performance in engineering design projects. This integrates multiple, previously disparate, aspects of design management and performance measurement theory in a single framework. Further, a fully realised performance measurement approach is developed, which complements existing management strategies. This framework is synthesised from an extensive review and illustrated via an in-depth case study. As such, this work contributes to performance measurement theory in engineering design and has significant implications for both engineering design research and industry. [ABSTRACT FROM AUTHOR]

System VVT (verification, validation, and testing) are essential activities within the domain of system engineering and need to be performed before delivering or marketing products; but to ensure the product complies with customer and engineering requirements in the best possible manner, all three activities should be implemented throughout the product project life cycle. The main objective of VVT is to ensure the customer receives a quality product and neither the customer nor the supplier is burdened with the cost of rework due to failures of the product after delivery. The literature includes very little research for effectively associating VVT methods to VVT activities and also taking into consideration project constraints such as cost, risk, and schedule. In our previous studies, we developed an analytical model that, given project constraints, produced an optimal VVT plan and provided a recovery procedure to manage unexpected events within the VVT process. The use of the model was demonstrated on a sample problem incorporating some unforeseen events. In this paper, we go one step further and use our model to analyse a real industrial project. As expected in a case study, the model has been further developed throughout the case implementation; specifically, a new quantitative model for assessing quality as a function of the test coverage of the VVT process was developed. The project manager found the model output valuable and informative to his work and thus enthusiastically collaborated on this case study research. Besides the report of the case study, we also conducted three focus group discussions to obtain insights, opinions, attitudes, and perceptions of the participants on the proposed analytical model as a decision support model. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of dynamic decoupling of adjustable serial manipulators via a new mechatronic design approach, which is based on the opposite motion of manipulator links and the optimal command design. The goal is to simplify the control by reducing the effects of complicated manipulator dynamics. The opposite motion of links with optimal redistribution of masses allows the cancellation of the coefficients of nonlinear terms in the manipulator’s kinetic and potential energy equations. Then, by using the optimal control design, the dynamic decoupling is achieved. The proposed approach, which is a symbiosis of mechanical and control solutions, improves the known design concepts permitting the dynamic decoupling of serial manipulators whilst taking into account the changing payload. It has two main advantages: at first, the dynamic decoupling of the manipulator is achieved without connection of gears to the links of the manipulator having oscillating motions and at second, the performance of the dynamic decoupling is improved by the changing payload. The suggested design methodology is illustrated by simulations carried out using ADAMS and MATLAB software, which have confirmed the efficiency of the developed approach. [ABSTRACT FROM AUTHOR]

Ideation is core to the innovation process, and has been the subject of study across a range of fields, from psychology to engineering. However, despite substantial progress in outcome-based descriptions of idea generation, research has often resulted in more questions than answers. For example, open questions remain with respect to the differences in behaviour related to ideation between novices and experts, the change in rates of ideation over time in different design teams, and the changing role of ideation from conceptual to detailed design. In each of these cases, robust explanation has proved elusive due to difficulties in characterising the ideation process itself. This paper discusses a major new approach for elucidating ideation and its related design processes through direct observation. A novel network visualisation approach is demonstrated in practice for the first time. This uses network analysis to link ideas dynamically to both the engineering context and the wider design process. This linking analysis gives a substantial new insight into what drives ideation and how previously inscrutable results can potentially be explained by linking ideation into other design processes. [ABSTRACT FROM AUTHOR]

Product design stage has a profound impact on a product's carbon footprint in its life cycle. Existing low-carbon design approaches are either not able to achieve low-carbon design solutions in product life cycle or prone to a loss of optimal solutions with the consideration of product life cycle. At each stage of product life cycle, there are several alternative design solutions, which can provide extra design space and bring more opportunities for low-carbon design. In this paper, a feature-based carbon footprint element model is proposed to estimate the carbon footprint at each stage of product life cycle. A five-layer weighted directed graph-based life cycle decision space is also proposed to represent the alternative life cycle paths. The low-carbon design process is to search the design solution with the lowest carbon footprint based on the mapping between design solution space and life cycle decision space. The proposed design process is to provide an integrated approach to enumerate and combine alternative solutions at each stage of product life cycle. The low-carbon design of a cold heading machine is given as an example to demonstrate the design methodology. [ABSTRACT FROM AUTHOR]

Observational studies of designers play an important role in engineering design research, yet there is currently no accepted standard approach for comparing, combining, or contrasting studies. Consequentially, reuse, reanalysis, replication, and aggregation of data are limited and the potential impact of individual studies is severely constrained. This paper begins to address this issue by introducing and developing a foundational method for observational design research to improve replicability, reuse, and overall comparability of empirical studies. A three-step foundational method is proposed that covers capture, coding, and analysis. The capture step defines overall and situational context as well as multiple capture streams, generating a broad data-set that can be examined from multiple perspectives. The coding step employs a multi-level approach that seeks to minimise workload while describing both detailed and high-level information. The analysis step builds on the multi-level approach to provide for a flexible yet standardised examination of the data-set. The overall approach is introduced theoretically and illustrated using a comparison of an industrial study and an experimental study. Finally, it is argued that the proposed method promotes rigour, reliability, and standardisation; and could provide one means for improving comparison and aggregation, ultimately increasing impact in academia and practice. [ABSTRACT FROM PUBLISHER]

The aim of this section is to provide an overview on the state of the current research, the exposition of the challenges faced in various fields of knowledge formalisation and representation (KFR), and to cast light on the relationship between ontology development and semantic reasoning in engineering design. Covering multiple purposes in various engineering design fields (e.g. system engineering, assembly design, simulation to name a few), the selected authors have developed different kinds of ontology ranged from endurantist to perdurantist stances, having various levels of expressiveness and granularity. Although these research efforts have introduced an interesting spectrum of ontology engineering approaches and some reasoning mechanisms, its remains important to cover the generative aspect, that is the way ontologies are computing, therefore inferring logical/semantic/pragmatic consequences to support engineering design issues (e.g. creative combination, control design, etc.). [Extracted from the article]

In engineering design optimisations, the dimensionality of the design space plays a critical role in determining the number of computationally expensive evaluations required to explore the design space and reach convergence. Dimensionality reduction allows engineers to represent high-dimensional design spaces in a more compact form to reduce the computational cost while retaining design flexibility. In order to reduce the dimensions of design space for shape optimisation problems, we propose a deep learning-based architecture named DeepMorpher. Our proposed architecture is a PointNet-based encoder-decoder network, which can directly be trained on 3D point-cloud geometries, and generate simulation-ready high-quality geometries without any pre-processing or post-processing steps. Our proposed DeepMorpher can work with multiple baseline templates and allows explainability and disentanglement of learned low-dimensional latent space through sampling, interpolation and feature space visualisation. To evaluate our approach, we created an engineering dataset consisting of 3D ship hull designs. The quantitative and qualitative experimentation results of the present study demonstrate that DeepMorpher can outperform previous state-of-the-art autoencoder-based shape-generative models by several orders of magnitudes. To demonstrate the high representation capacity and compactness of learned low-dimensional latent space, we employed DeepMorpher within a simulation-based design optimisation framework to perform a real-world constrained multi-objective optimisation to find optimal ship hull designs. Highlights A deep learning-based autoencoder network for reducing the dimensionality of design space in shape optimisation is proposed. The proposed network learns an explainable and disentangled low-dimensional latent space where each dimension captures different attributes of high-dimensional input shape. The proposed network incorporates free-form deformation within the architecture to generate simulation-ready geometries with high visual quality. The efficacy of the proposed network was demonstrated inside a simulation-based design optimisation framework to perform multi-objective Bayesian optimisation using multiple baseline templates to find optimal designs. [ABSTRACT FROM AUTHOR]

Specific design knowledge (SDK) plays a crucial role in engineering design, as it enables designers to define a system structure that can fulfil the required functions through its behaviour. A variety of modelling methods aim at supporting the gain of this knowledge. However, they are usually evaluated concerning the designs produced rather than the knowledge generated in the process. Also, established operationalisations of SDK are missing. This results in a lack of understanding of the generation of SDK. Hence, an experimental study is conducted to investigate the impact of an exemplary modelling method on the generation of SDK. The study is set up with 35 participants, who analyse two technical systems. Intuitive approaches are compared with the application of the modelling method. On the system level, SDK is assessed through relations of structure and behaviour. On the detail level, function-critical system areas and function-relevant system states, are investigated. Results show, that the modelling method increases SDK at the system level compared to intuitive approaches. At the detail level, no statement about statistically significant differences could be derived. The presented study design can provide a baseline for investigations of similar modelling methods or other design methods supporting the generation of SDK. [ABSTRACT FROM AUTHOR]

This quasi-experimental study presents the integration of cooperative learning pedagogy with the tasks of the engineering design process at a first-year interdisciplinary design course for undergraduate engineering students at a private engineering university in India. With a sample of 118 students, 59 each in the experimental group and control group, the integration presented as four interventions were tested for their effectiveness in two aspects: performance in the three tasks of the engineering design process: problem definition, concept generation and detailed design, and satisfaction with team interpersonal processes and, individual wellbeing and learning. The performance was measured using rubrics-based assessment, and satisfaction was measured using two subscales of a team diagnostic survey after demonstrating its validity and reliability. Results revealed significant differences in performance between the two groups with large to medium effect sizes. While cooperative learning brings members together at a level that increases interdependencies, often leading to arguments and conflicts, the proposed interventions yielded contrary results. Despite increased interdependence, the interventions did not lead to statistically significant between-group differences in team interpersonal processes and individual wellbeing and learning. Thus, this study has important implications for how engineering educators structure interdependencies between students in courses focusing on design problem-solving. [ABSTRACT FROM AUTHOR]

Technological innovations pave the way for alternative interaction paradigms, which allow for more intuitive and pleasurable user experiences. Such new interaction types are particularly called for when considering that people are facing an ever-increasing information flow that in the end oftentimes hamper satisfying experiences with technology. Connecting knowledge from the fields of interaction design, product design, and psychology, we present a theoretical framework that explains how different modalities can be used in interaction with products. We will focus on the tactile modality in particular and present two case studies that show how designers can design for this modality in a direct (functional) and in an abstract (symbolic) manner, respectively. [ABSTRACT FROM PUBLISHER]

Additive manufacturing (AM) presents designers with unique manufacturing capabilities while imposing several limitations. Designers must leverage AM capabilities – through opportunistic design for AM (O-DfAM) – and accommodate AM limitations – through restrictive (R-) DfAM – to successfully employ AM in engineering design. This dual DfAM approach – comprising O- and R-DfAM – starkly contrasts traditional, limitation-based design for manufacturing (DfM). Therefore, designers must transition from a restrictive DfM mindset towards a 'dual' design mindset. Designers' prior experience, especially with DfM could inhibit their ability to transition towards dual DfAM. On the other hand, experienced designers' auxiliary skills (e.g. with computer-aided design) could help them implement DfAM in their solutions. However, little research has studied the influence of prior experience on DfAM use in the later design stages (i.e. embodiment and detail design), and we explore this research gap. Specifically, we conducted an experimental study comprising a task-based DfAM educational intervention with first-year student designers and upper-level student designers. Participants' DfAM self-efficacy and their integration of DfAM in their solutions were compared between the two groups. From our results, we see that experienced designers report higher baseline self-efficacy with R-DfAM but not O-DfAM. We also see that experienced designers demonstrate a greater use of certain DfAM concepts (e.g. part and assembly complexity) in their designs. These findings suggest that introducing designers to O-DfAM early could help develop a dual design mindset; however, having more engineering experience might be necessary for them to implement DfAM into their designs. [ABSTRACT FROM AUTHOR]