ALBERT

Description: Designing Product-Service Systems (PSS) is associated with multiple problems and challenges, usually derived from its multidisciplinarity and partially intangible nature. One particular issue is the high likelihood of ignoring the creation of relevant information regarding one or more PSS elements during the early design phases. Proceeding to later stages (e.g., detailed design) without generating the required information regarding all PSS elements and their relationships may lead to rework and lack of integration. Dealing with this problem requires adequate planning and evaluation of the artifacts (such as documents and models) created in the initial design phases. As a fundamental theoretical basis to support the creation of solutions that may help project managers dealing with this challenge, this paper presents a concept map to structure the concepts that compose artifacts resulting from the initial stages of PSS design and how those concepts interrelate. This concept map aims to structure which classes of information should be defined in the early phases of the design process before proceeding to a detailed design. The concept map was created by extracting concepts and relationships proposed in classifications, taxonomies, ontologies, meta-models, and concept maps in the PSS and servitization fields. Those documents were identified through a comprehensive systematic literature review. The resulting concept map was verified for completeness against formal documentation of two retrospective PSS design projects. The final proposed concept map is composed of 143 concepts interconnected through 278 relationships. In its current format, the concept map may be used as a checklist to support project managers in planning and evaluating early phases of PSS design based on information completeness. Researchers may also employ it to deploy ontologies, approach further knowledge and information-related challenges in PSS design, or structure PSS-related model-based systems engineering approaches. In future research, this concept map shall be deployed in a meta-model based on artifacts commonly used in PSS design, structuring a computational tool to allow and support practical application on planning and evaluating PSS design projects.

Description: 266 fuzzy front-end (FFE) studies in the new product development (NPD) sector were examined. The studies were selected using a bibliometrics method, and chronologically and statistically examined with ten criteria divided into two dimensions. The first dimension is associated with overall attributes of the FFE, consisting of six criteria: the study taxonomy, model type, NPD speed, NPD attributes, model characteristic, and model structure. The second dimension is relevant to the FFE performance structure related to process parameters, comprised of four criteria: the FFE task, activity, performance method, and toolkit. In terms of those two dimensions, the paper looks at previous FFE studies to gain an understanding of features of each FFE study along with related knowledge and theories, as well as identification of evolution trends of FFE studies. Based on the identification, an FFE model development strategy for each criterion is formulated, and this paper proposes possible options for executing those strategies which exert influence on the form of the cluster network. The intention is for the database to be utilised as an overview of all existing FFE studies and allow specific FFE studies to be selected to examine FFE approaches.This paper provides FFE model development guidance on how to deal with the overall attributes and outcomes of the FFE which affect the entirety of the innovation process, and how to manage the performance structure related to process parameters.

Description: The aim of this work is to determine how personal intrinsic factors towards a design problem are related to novelty and circularity. A deeper understanding of this relationship will be a valuable aid when it comes to making an adequate selection of design teams. The factors studied are the level of the designer's motivation, relevance, knowledge and affinity with regard to the design problem. To this end, a study was conducted with 35 novice designers, organised in groups of between two and five members. Each group had to propose a conceptual solution to two different design problems. Novelty was assessed using the SAPPhIRE causality model (which stands for State–Action–Part–Phenomenon–Input–oRgan–Effect) and the Circular Economy Toolkit was applied to measure circularity. The results show that as motivation, level of knowledge, perception of relevance and affinity for the problem increase, the solution displays greater novelty and less circularity, although for circularity, the difference is not statistically significant.

Description: In recent years, space projects have evolved to faster and more variable projects. To adjust the design processes in accordance, new work methodologies arise, as the Concurrent Engineering (CE). This working discipline is characterized by collaborative design and the flux of information being improved by working in a dedicated environment. CE has been recently adopted by space industry for the preliminary design phase of spacecrafts and other space systems. However, this methodology does not envisage tasks prioritization, which is a fundamental aspect to achieve an optimal design solution with an efficient allocation of resources. In this work a variation of CE discipline by applying Agile methodologies (in which the aspect of task prioritization is essential), is proposed. Agile methodologies allow the proper distribution of the design effort depending on the project priorities, the state of the design and the requirements, in a continuous process to improve the design solution. The general aspects of the proposed method are presented and applied to the design of a space mission, the results being analysed and compared with to the classical CE process in order to outline its differences and similarities with CE and Agile methodologies and show its potential for a new environment for space project design.

Description: This paper introduces an Enhanced Sequence Diagram (ESD) as the basis for a structured framework for the functional analysis of complex multidisciplinary systems. The ESD extends the conventional sequence diagrams (SD) by introducing a rigorous functional flow-based modelling schemata to provide an enhanced basis for model-based functional requirements and architecture analysis in the early systems design stages. The proposed ESD heuristics include the representation of transactional and transformative functions required to deliver the use case sequence, and fork and join nodes to facilitate analysis of combining and bifurcating operations on flows. A case study of a personal mobility device is used to illustrate the deployment of the ESD methodology in relation to three common product development scenarios: (i) reverse engineering, (ii) the introduction of a specific technology to an existent system; and (iii) the introduction of a new feature as user-centric innovation for an existing system, at a logical design level, without reference to any solution. The case study analysis provides further insights into the effectiveness of the ESD to support function modelling and functional requirements capture, and architecture development. The significance of this paper is that it establishes a rigorous ESD-based functional analysis methodology to guide the practitioner with its deployment, facilitating its impact to both the engineering design and systems engineering communities, as well as the design practice in the industry.

Description: The final architecture of a complex system reflect preferences of several value chain stakeholders on system attributes, also called “ilities”. Owing to differences in their individual roles and responsibilities, different stakeholders prefer different approaches to architect and decompose a system to optimize their attributes of interest. However, owing to increasing complexity of modern engineering systems, optimizing multiple attributes of complex systems has become challenging; moreover, very few researches have been published in this regard. Thus, to address this gap in available literature, this paper presents a multi-attribute optimization framework for complex system decomposition. The proposed framework primarily optimizes two attributes—system robustness (to the perspective of the stakeholder), and modularity—while system maintainability is considered an optimization constraint. Feasibility of the proposed framework has been demonstrated through a case study, wherein system attributes of three different mechanical clock models having different architectures were optimized.

Description: In systems engineering, verification activities evaluate the extent to which a system under development satisfies its requirements. In large systems engineering projects, multiple firms are involved in the system development, and hence verification activities must be coordinated. Self-interest impedes the implementation of verification strategies that are beneficial for all firms while encouraging each firm to choose a verification strategy beneficial to itself. Incentives for verification activities can motivate a single firm to adopt verification strategies beneficial to all firms in the project, but these incentives must be offered judiciously to minimize unnecessary expenditures and prevent the abuse of goodwill. In this paper, we use game theory to model a contractor-subcontractor scenario, in which the subcontractor provides a component to the contractor, who further integrates it into their system. Our model uses belief distributions to capture each firm’s epistemic uncertainty in their component’s state prior to verification, and we use multiscale decision theory to model interdependencies between the contractor and subcontractor’s design. We propose an incentive mechanism that aligns the verification strategies of the two firms and using our game-theoretic model, we identify those scenarios where the contractor benefits from incentivizing the subcontractor’s verification activities.

Description: This paper explores the formal roles of non-functional requirements’ (NFR) elicitation, definition, and verification in the early stages of an engineering design project. This is performed using a case study conducted at an automotive original equipment manufacturer (OEM) during the design and development of a rear bumper sub-system. The purpose of this exploration is to determine if NFRs should be formalized within requirements modeling scheme. This can capture conceptual design information to identify their impact on other requirements while conducting design changes. The modeling scheme in this paper consists of a sequence of following domains—requirements, functions, working principle, components, design parameters, test measures, and tests—that are mapped to each other using matrices. It is revealed through this case study that non-functional requirements drive much of the design decision-making process and constrain the manner in which the product functionality is realized. Hence, the inclusion of NFRs as a separate and distinct domain in the design process is critical to recognize their significance during design changes. Based on the observations made in the case study, the NFR domain is included in the requirements modeling scheme.

Description: Aggregating the preferences of a group of experts is a recurring problem in several fields, including engineering design; in a nutshell, each expert formulates an ordinal ranking of a set of alternatives and the resulting rankings should be aggregated into a collective one. Many aggregation models have been proposed in the literature, showing strengths and weaknesses, in line with the implications of Arrow's impossibility theorem. Furthermore, the coherence of the collective ranking with respect to the expert rankings may change depending on: (i) the expert rankings themselves and (ii) the aggregation model adopted. This paper assesses this coherence for a variety of aggregation models, through a recent test based on the Kendall's coefficient of concordance (W), and studies the characteristics of those models that are most likely to achieve higher coherence. Interestingly, the so-called Borda count model often provides best coherence, with some exceptions in the case of collective rankings with ties. The description is supported by practical examples.

Description: Requirement change propagation, if not managed, may lead to monetary losses or project failure. The a posteriori tracking of requirement dependencies is a well-established practice in project and change management. The identification of these dependencies often requires manual input by one or more individuals with intimate knowledge of the project. Moreover, the definition of these dependencies that help to predict requirement change is not currently found in the literature. This paper presents two industry case studies of predicting system requirement change propagation through three approaches: manually, linguistically, and bag-of-words. Dependencies are manually and automatically developed between requirements from textual data and computationally processed to develop surrogate models to predict change. Two types of relationship generation, manual keyword selection and part-of-speech tagging, are compared. Artificial neural networks are used to create surrogate models to predict change. These approaches are evaluated on three connectedness metrics: shortest path, path count, and maximum flow rate. The results are given in terms of search depth needed within a requirements document to identify the subsequent changes. The semi-automated approach yielded the most accurate results, requiring a search depth of 11 %, but sacrifices on automation. The fully automated approach is able to predict requirement change within a search depth of 15 % and offers the benefits of full minimal human input.

Description: The reuse of knowledge and information arising from the different phases of a product’s lifecycle is crucial for a company in order to achieve competitive advantage. This paper describes a case study from the oil industry investigating the transfer of knowledge within the service phase and also between the service and design phases. Interviews with engineering designers and service engineers were conducted. Knowledge arising from servicing the drilling equipment that was identified as relevant for service engineers was compared to that relevant for engineering designers. Furthermore, the mechanisms involved in the transfer of knowledge between service and design were investigated. Knowledge about changes, issues and improvements generated during service was found to be relevant to both groups; however, engineering designers were interested in knowledge of equipment at a component level whilst service engineers were more interested in obtaining an overview of the systems. The study showed that communication between the departments consisted prevalently of the service engineers pushing knowledge and information to the engineering designers. The reusing service knowledge (RSK) model is proposed based upon the findings and the understanding from a general framework for developing a knowledge management strategy. Additionally, the initial model was revised to explicitly address the factors that emerged from the case study. The RSK model was developed based on a case study from a customised industry; however, previous studies indicated that similar issues are also of relevance to a variant design industry.

Description: Capturing and managing requirements are crucial to the success of product design and development. This paper presents and analyzes the causes of requirements change during the design process of a complex aerospace system developed by Rolls-Royce during the course of 6 years. The study was part of a series of efforts ongoing at this original equipment manufacturer to improve requirements engineering practices and involved a group of engineers in the assessment of the root causes of change. A large data set was examined, containing 700 system requirements and more than 1,000 changes released during the project studied. The results showed that more than 80 % of the changes had internal root causes and change driven by the customer accounted for about 15 % of the total. The structured approach that was implemented to understand the causes of change allowed the group of engineers to identify and dissect various management guidelines aiming to further improve requirements engineering in practice. This paper thus also reports the guidelines captured at this aerospace manufacturer and intends to support practitioners across the industrial community.

Description: The reuse of knowledge and information arising from the different phases of a product’s lifecycle is crucial for a company in order to achieve competitive advantage. This paper describes a case study from the oil industry investigating the transfer of knowledge within the service phase and also between the service and design phases. Interviews with engineering designers and service engineers were conducted. Knowledge arising from servicing the drilling equipment that was identified as relevant for service engineers was compared to that relevant for engineering designers. Furthermore, the mechanisms involved in the transfer of knowledge between service and design were investigated. Knowledge about changes, issues and improvements generated during service was found to be relevant to both groups; however, engineering designers were interested in knowledge of equipment at a component level whilst service engineers were more interested in obtaining an overview of the systems. The study showed that communication between the departments consisted prevalently of the service engineers pushing knowledge and information to the engineering designers. The reusing service knowledge (RSK) model is proposed based upon the findings and the understanding from a general framework for developing a knowledge management strategy. Additionally, the initial model was revised to explicitly address the factors that emerged from the case study. The RSK model was developed based on a case study from a customised industry; however, previous studies indicated that similar issues are also of relevance to a variant design industry.

Description: This research addresses a need in systems engineering to verify that a system can meet performance requirements; this is done by integrating failure behavior into the system’s nominal model during the initial stages of design. In general, failure behavior is not used in early assessments, lending toward increased uncertainty in the model’s validity. Current libraries do not model failures and thus cannot confidently address how a design will function in the intended operational environments. Since failures occur from effects on the environment, they should be included during verification and validation efforts. Current approaches capture off-nominal behavior using parameter variation where flow variables and parameters are varied to measure the system-level effect. This approach is ad hoc and does not accurately capture failure mode behavior. To address this limitation, an approach is developed to understand and implement failure mode behavior into nominal models. The Modelica Standard Library (MSL) is used as an example for the component library of nominal models. MSL has a significant amount of basic nominal component behavior and therefore is desirable for this research. Two approaches are developed to implement failure mode behavior; the first uses transfer function and use case graphs, and the second uses existing literature. In addition, complex systems often have a large number of components and an even larger number of failure modes. Since the goal is to limit the development time, we generate an approach to identify high-risk failure modes. This captures an early system-level effect of each failure mode and uses an occurrence to calculate risk. To show the usefulness of each method, two examples are provided including a vehicle drivetrain subsystem with a variety of failures and a diesel engine with fuel injector and valve failures.

Description: This paper introduces metrics derived from application of a Markov decision process to evaluate a design’s changeability. Changeability is known to improve product performance if conscientious early-stage design decisions are matched with structured management of the system in response to exogenous disturbances—shifts which may be environmental, market, technological, and political in nature. Included in the paper is a brief discussion of changeability’s role in ensuring strategic product performance as well as a review of past metrics developed, highlighting the open design challenge to more fully capture the managerial and process dimensions inherent to changeability. The proposed metrics are featured in a case study related to the ballast water system of an ocean-going vessel. The result of such application is greater context for the value changeability offers and an improved understanding of the resources required to manage uncertainty over the product’s life cycle.

Description: This research addresses a need in systems engineering to verify that a system can meet performance requirements; this is done by integrating failure behavior into the system’s nominal model during the initial stages of design. In general, failure behavior is not used in early assessments, lending toward increased uncertainty in the model’s validity. Current libraries do not model failures and thus cannot confidently address how a design will function in the intended operational environments. Since failures occur from effects on the environment, they should be included during verification and validation efforts. Current approaches capture off-nominal behavior using parameter variation where flow variables and parameters are varied to measure the system-level effect. This approach is ad hoc and does not accurately capture failure mode behavior. To address this limitation, an approach is developed to understand and implement failure mode behavior into nominal models. The Modelica Standard Library (MSL) is used as an example for the component library of nominal models. MSL has a significant amount of basic nominal component behavior and therefore is desirable for this research. Two approaches are developed to implement failure mode behavior; the first uses transfer function and use case graphs, and the second uses existing literature. In addition, complex systems often have a large number of components and an even larger number of failure modes. Since the goal is to limit the development time, we generate an approach to identify high-risk failure modes. This captures an early system-level effect of each failure mode and uses an occurrence to calculate risk. To show the usefulness of each method, two examples are provided including a vehicle drivetrain subsystem with a variety of failures and a diesel engine with fuel injector and valve failures.

Description: This paper introduces metrics derived from application of a Markov decision process to evaluate a design’s changeability. Changeability is known to improve product performance if conscientious early-stage design decisions are matched with structured management of the system in response to exogenous disturbances—shifts which may be environmental, market, technological, and political in nature. Included in the paper is a brief discussion of changeability’s role in ensuring strategic product performance as well as a review of past metrics developed, highlighting the open design challenge to more fully capture the managerial and process dimensions inherent to changeability. The proposed metrics are featured in a case study related to the ballast water system of an ocean-going vessel. The result of such application is greater context for the value changeability offers and an improved understanding of the resources required to manage uncertainty over the product’s life cycle.

Description: Requirement change propagation, if not managed, may lead to monetary losses or project failure. The a posteriori tracking of requirement dependencies is a well-established practice in project and change management. The identification of these dependencies often requires manual input by one or more individuals with intimate knowledge of the project. Moreover, the definition of these dependencies that help to predict requirement change is not currently found in the literature. This paper presents two industry case studies of predicting system requirement change propagation through three approaches: manually, linguistically, and bag-of-words. Dependencies are manually and automatically developed between requirements from textual data and computationally processed to develop surrogate models to predict change. Two types of relationship generation, manual keyword selection and part-of-speech tagging, are compared. Artificial neural networks are used to create surrogate models to predict change. These approaches are evaluated on three connectedness metrics: shortest path, path count, and maximum flow rate. The results are given in terms of search depth needed within a requirements document to identify the subsequent changes. The semi-automated approach yielded the most accurate results, requiring a search depth of 11 %, but sacrifices on automation. The fully automated approach is able to predict requirement change within a search depth of 15 % and offers the benefits of full minimal human input.

Description: Managing uncertainty levels is important for organizations carrying out complex product development processes since it fosters design process improvements and optimization. Among the different uncertainties, design imprecision is known to represent uncertainty in decision-making that typically triggers changes to the value assigned to design variables during the early stages of the development process. This paper presents a method aiming to support large organizations understanding, quantifying and communicating this type of uncertainty. The imprecision management method that is proposed relies on five main steps: collection of historical records of change, time evolution reconstruction, statistical characterization of the typical levels of imprecision that should be expected, communication to new projects and continuous knowledge update. In addition, we present results from a case-study performed at Rolls–Royce that tested the method’s applicability in practice. The study shed light to interesting empirical findings about the typical level of imprecision in design variables and its evolution during real product development projects. The results from this initial evaluation suggest that the method provides useful support for design process management and thus has industrial value.

Description: This paper presents a model of the way that designers move between situations when interpreting during design activity. Three hypotheses are presented that arise from this model: that designers change their situation during interpretation, that small changes in a source can lead to large changes in the representation and that changes to the situation have their origins in the experience of the designer. The paper demonstrates how this internal movement between situations can be computationally implemented using three examples. The systems implemented demonstrate the way that interpretation can lead to changes in the situation and present an example of how the changes to a designer’s situation can be guided by past experiences.

Description: The variability of products affects customers’ satisfaction by increasing flexibility in decision-making for choosing a product based on their preferences in competitive market environments. In product family design, decision-making for determining a platform design strategy or the degree of commonality in a platform can be considered as a multidisciplinary optimization problem with respect to design variables, production cost, company’s revenue, and customers’ satisfaction. In this paper, we investigate evolutionary algorithms and module-based design approaches to identify an optimal platform strategy in a product family. The objective of this paper is to apply a multi-objective particle swarm optimization (MOPSO) approach to determine design variables for the best platform design strategy based on commonality and design variation within the product family. We describe modifications to apply the proposed MOPSO to the multi-objective problem of product family design and allow designers to evaluate varying levels of platform strategies. To demonstrate the effectiveness of the proposed approach, we use a case study involving a family of General Aviation Aircraft. We show that the proposed optimization algorithm can provide a proper solution in product family design process through experiments. The limitations of the approach and future work are also discussed.

Description: Search of design spaces to generate solutions affects the design outcomes during conceptual design. This research aims to understand the different types of search that occurs during conceptual design and their effect on the design outcomes. Additionally, we study the effect of other factors, such as creativity, problem-solving style, and experience of designers, on the design outcomes. Two sets of design experiments, with experienced and novice designers, are used in this study. We find that designers employ twelve different types of searches during conceptual design for problem understanding, solution generation, and solution evaluation activities. Results also suggest that creativity is influenced positively by the type and amount of searches, duration of designing, and experience of designers.

Description: This paper addresses the problem of describing the decision-making process of a committee of engineers based upon their verbalized linguistic appraisals of alternatives. First, we show a way to model an individual’s evaluation of an alternative through natural language based on the Systemic-Functional Linguistics system of APPRAISAL. The linguistic model accounts for both the degree of intensity and the uncertainty of expressed evaluations. Second, this multi-dimensional linguistic model is converted into a scalar to represent the degree of intensity and a probability distribution function for the stated evaluation. Finally, we present a Markovian model to calculate the time-varying change in preferential probability, the probability that an alternative is the most preferred alternative. We further demonstrate how preferential probability toward attributes of alternatives correspond to preferential probability toward alternatives. We illustrate the method on two case studies to highlight the time-variant dynamics of preferences toward alternatives and attributes. This research contributes to process tracing in descriptive decision science to understand how engineers actually take decisions.

Description: Benefits of modularity are often achieved from module independence that allows for independent development to reduce overall lead time and economies of scale due to sharing similar modules across products in a product family. Current modularity methods tend to describe only one of these views, either the module–module independence or the product–product shared module similarity. This paper proposes a new hybrid module generation algorithm that balances both module independence and product similarity, allowing product similarity strategy to influence the coupling-driven architecture considerations. The proposed method builds on two popular matrix-based methods: the design structure matrix approach and modular function deployment that each has been developed to support these two different aspects of the module generation. This paper presents a novel algorithm that integrates both views and allows a balanced clustering that takes both interactions and company portfolio strategy into account. Usefulness of the algorithm is presented using a cordless handheld vacuum cleaner as a case study and by comparing it to alternative approaches.

Description: Complex systems are increasingly being developed as part of portfolios or sets of related complex systems. This enables synergies such as commonality between portfolio systems that can significantly reduce portfolio life-cycle cost and risk. While offering these benefits, commonality usually also incurs up-front as well as life-cycle penalties in cost and risk due to increased design complexity. The resulting trade-off needs to be carried out during the architecting stage of the portfolio life cycle when there is maximum leverage to improve life-cycle properties due to degrees of freedom available in architectural and design decisions. This paper outlines a 4-step methodology for the identification and assessment of commonality opportunities in complex systems portfolios during the architecting stage of the portfolio life cycle. The methodology transforms a solution-neutral description of a portfolio of aerospace systems based on system functionality, requirements, and metrics into a set of preferred portfolio design solutions with commonality. The methodology is based on a 2-stage approach that identifies preferred architectures for each system in the portfolio individually prior to heuristic commonality analysis between systems based on a pairwise assessment of system overlap in functionality, technologies, operational environments, and scale. Application of the methodology is demonstrated with a retrospective analysis of NASA’s Saturn launch vehicle portfolio.

Description: Introduced nearly 25 years ago, the paradigm of mass customization (MC) has largely not lived up to its promise. Despite great strides in information technology, engineering design practice and manufacturing production, the necessary process innovations that can produce products and systems with sufficient customization and economic efficiency have yet to be found in wide application. In this paper, the state-of-the-art in MC is explored in the context of an envisioned MC development process for both the firm and the customer. Specifically, 130 references are reviewed within the process frameworks (Sect. 3 ) and/or to highlight opportunities for future development in MC (Sect. 4 ) based on the review. This review yields opportunities in four primary areas that challenge MC development: (1) customer needs and preference assessment tools, (2) approaches for requirement specification and conceptual design, (3) insights from methodologies focused on the development of durable MC goods and (4) enhancements in information mapping and handling.

Description: While cyber–physical system sciences are developing methods for studying reliability that span domains such as mechanics, electronics and control, there remains a lack of methods for investigating the impact of the environment on the system. External conditions such as flooding, fire or toxic gas may damage equipment and failing to foresee such possibilities will result in invalid worst-case estimates of the safety and reliability of the system. Even if single component failures are anticipated, abnormal environmental conditions may result in common cause failures that cripple the system. This paper proposes a framework for modeling interactions between a cyber–physical system and its environment. The framework is limited to environments consisting of spaces with clear physical boundaries, such as power plants, buildings, mines and urban underground infrastructures. The purpose of the framework is to support simulation-based risk analysis of an initiating event such as an equipment failure or flooding. The functional failure identification and propagation (FFIP) framework is extended for this purpose, so that the simulation is able to detect component failures arising from abnormal environmental conditions and vice versa: Flooding could be caused by a failure in a pipe or valve component. As abnormal flow states propagate through the system and its environment, the goal of the simulation is to identify the system-wide cumulative effect of the initiating event and any related common cause failure scenario. FFIP determines this effect in terms of degradation or loss of the functionality of the system. The method is demonstrated with a nuclear reactor’s redundant coolant supply system.

Description: ‘Someone else has patented this before’. This is the last thing you would want to hear after months of intensive engineering design work. Yet, this is not uncommon. There is a link between engineering design and intellectual property (IP). However, the boundary between them is not always well defined, especially on when and how IP infringement checks should be conducted during the engineering design process. Hence, this letter seeks to reach out to researchers in the engineering design community to come together and tackle this common design issue.

Description: We propose a framework for measuring the complexity of aerospace systems and demonstrate its application. A measure that incorporates size, coupling, and modularity aspects of complexity is developed that emphasizes the importance of indirect coupling and feedback loops in the system. We demonstrate how hierarchical modular structure in the system reduces complexity and present an algorithm to decompose the system into modules. The measure is tested and found to be scalable for large-scale systems involving thousands of components and interactions (typical in modern aerospace systems). We investigate the sensitivity of the measure and demonstrate the ability of the framework to identify incorrectness in system representation. The merits of the framework are exemplified through a case study comparing three spacecraft. The framework provides the designer with three key capabilities that can positively influence the aerospace (or other) design process: the ability to identify complex subsystems, the ability to classify misrepresentations, and the ability to trade-off commercially of the shelf (COTS) and non-COTS components.

Description: We present a comprehensive robot development process and its evaluation. We designed this process in the context of a robotics course in high schools. The motivation for designing this new process was improving the robustness and reliability of robots developed by students and preparing students for becoming better designers. The newly designed process proved to be highly successful in designing top quality robots. In the process design, we explored and adapted existing design tools and methods to the specific designers, the nature of the product, the environment, the product needs, and the design context goals. At the end of this thorough design, we selected a synergetic integration of six tools and methods to compose the new comprehensive development process for this product context: conceptual design, fault-tolerant design, atomic requirements, fuzzy logic for control, creative thinking, and microprogramming-based design. The design skills of the students that learned the design process and the performance of robots they designed and participated in an international robotics contest were examined. The high school teams that studied the proposed process won the first places in an international contest. The robots developed by the students had better performance than robots built by engineers and faculty teams. Professional experts rated the robots’ designs as excellent. The students that studied the process demonstrated high level of diverse design skills including creativity and design management capabilities. Additionally, they improved their science subject grades and their attitude toward engineering. Both the results obtained by the study and the authors’ experience in teaching robotics demonstrate that the proposed robot development process could be taught successfully in high school and that it leads to superior robotic products. Our experience also indicates that this process could serve industry design by improving the robustness of robots operating in uncertain environments and supporting fast change management practices.

Description: To demystify the debate about the validity of selection methods that utilize aggregation procedures, it is necessary that contributors to the debate are explicit about (a) their personal goals and (b) their methodological aims. We introduce three additional points of clarification: (1) the need to differentiate between the aggregation of preferences and of performances, (2) the application of Arrow’s theorem to performance measures rather than to preferences, and (3) the assumptions made about the information that is available in applying selection methods. The debate about decision methods in engineering design would be improved if all contributors were more explicit about these issues.

Description: When designing mechatronic products, ‘complex dependencies’ are often reported to be a major challenge. This paper focuses on managing dependencies between attributes of the product during the design process. The literature study shows that there is a gap in the literature with regard to the classification of product-related dependencies. Traditionally, these dependencies have been described as appearing between the following product attributes: function, properties and structure. By analysing three mechatronic projects from industry, we identified and classified 13 types of product-related dependencies. Each product-related dependency is described and illustrated using the practical examples from the industrial projects. The value of the classification is evaluated by applying it to an industrial development setting not used for the analysis. The evaluation shows that delays in the project schedule, loss of functionality and quality issues can be avoided if attention is directed toward the product-related dependencies in the development process.

Description: We present a comprehensive robot development process and its evaluation. We designed this process in the context of a robotics course in high schools. The motivation for designing this new process was improving the robustness and reliability of robots developed by students and preparing students for becoming better designers. The newly designed process proved to be highly successful in designing top quality robots. In the process design, we explored and adapted existing design tools and methods to the specific designers, the nature of the product, the environment, the product needs, and the design context goals. At the end of this thorough design, we selected a synergetic integration of six tools and methods to compose the new comprehensive development process for this product context: conceptual design, fault-tolerant design, atomic requirements, fuzzy logic for control, creative thinking, and microprogramming-based design. The design skills of the students that learned the design process and the performance of robots they designed and participated in an international robotics contest were examined. The high school teams that studied the proposed process won the first places in an international contest. The robots developed by the students had better performance than robots built by engineers and faculty teams. Professional experts rated the robots’ designs as excellent. The students that studied the process demonstrated high level of diverse design skills including creativity and design management capabilities. Additionally, they improved their science subject grades and their attitude toward engineering. Both the results obtained by the study and the authors’ experience in teaching robotics demonstrate that the proposed robot development process could be taught successfully in high school and that it leads to superior robotic products. Our experience also indicates that this process could serve industry design by improving the robustness of robots operating in uncertain environments and supporting fast change management practices.

Description: Search of design spaces to generate solutions affects the design outcomes during conceptual design. This research aims to understand the different types of search that occurs during conceptual design and their effect on the design outcomes. Additionally, we study the effect of other factors, such as creativity, problem-solving style, and experience of designers, on the design outcomes. Two sets of design experiments, with experienced and novice designers, are used in this study. We find that designers employ twelve different types of searches during conceptual design for problem understanding, solution generation, and solution evaluation activities. Results also suggest that creativity is influenced positively by the type and amount of searches, duration of designing, and experience of designers.

Description: Design-by-analogy is a growing field of study and practice, due to its power to augment and extend traditional concept generation methods by expanding the set of generated ideas using similarity relationships from solutions to analogous problems. This paper presents the results of experimentally testing a new method for extracting functional analogies from general data sources, such as patent databases, to assist designers in systematically seeking and identifying analogies. In summary, the approach produces significantly improved results on the novelty of solutions generated and no significant change in the total quantity of solutions generated. Computationally, this design-by-analogy facilitation methodology uses a novel functional vector space representation to quantify the functional similarity between represented design problems and, in this case, patent descriptions of products. The mapping of the patents into the functional analogous words enables the generation of functionally relevant novel ideas that can be customized in various ways. Overall, this approach provides functionally relevant novel sources of design-by-analogy inspiration to designers and design teams.

Description: The parameter analysis method of conceptual design is studied in this paper with the help of C–K theory. Each of the fundamental design activities—idea generation, implementation of the idea as hardware and evaluation—is explained and defined as a specific sequence of C–K operators. A case study of designing airborne decelerators is used to demonstrate the modeling of the parameter analysis process in C–K terms. The theory is used to explain how recovery from an initial fixation took place, leading to a breakthrough in the design process. It is shown that the innovative power of parameter analysis is based on C-space “de-partitioning” and that the efficient strategy exhibited by parameter analysis can be interpreted as steepest-first, controlled by an evaluation function of the design path. This logic is explained as generalization of branch-and-bound algorithms by a learning-based, dynamically evolving evaluation function and exploration of a state space that keeps changing during the actual process of designing.

Description: Capturing and managing requirements are crucial to the success of product design and development. This paper presents and analyzes the causes of requirements change during the design process of a complex aerospace system developed by Rolls-Royce during the course of 6 years. The study was part of a series of efforts ongoing at this original equipment manufacturer to improve requirements engineering practices and involved a group of engineers in the assessment of the root causes of change. A large data set was examined, containing 700 system requirements and more than 1,000 changes released during the project studied. The results showed that more than 80 % of the changes had internal root causes and change driven by the customer accounted for about 15 % of the total. The structured approach that was implemented to understand the causes of change allowed the group of engineers to identify and dissect various management guidelines aiming to further improve requirements engineering in practice. This paper thus also reports the guidelines captured at this aerospace manufacturer and intends to support practitioners across the industrial community.

Description: When developing an artifact, designers must first capture and represent user needs. These needs can then be transformed into system requirements or objectives. The contribution of this work is rooted in the formalization of the affordance-based approach for capturing user needs in the early stages of design. This formalization comes in three forms: the first affordance basis for engineering design (a defined set of affordances), a formal structure for affordance statements, and a new relational model structure. This formalization is intended to improve model quality and consistency, while managing model creation resources. Further, this affordance-based approach to capturing user needs imposes a level of abstraction that forces solution independence yet is capable of capturing the large range of user needs. As such, the approach provides a structured approach to problem abstraction—the process of specifying user needs without reference to specific solutions. This affordance-based problem representation relies on other design process tools to help develop the actual artifact, which is also discussed.

Description: Engineering changes are essential for any product development, and their management has become a crucial discipline. Research in engineering change management has brought about some methods and tools to support dealing with changes. This work extends the change prediction method through incorporation of a function–behaviour–structure (FBS) scheme. These additional levels of detail provide the rationales for change propagation and allow a more proactive management of changes. First, we develop the ontology of this method based on a comprehensive comparison of three seminal functional reasoning schemes. Then, we demonstrate the FBS Linkage technique by applying it to a diesel engine. Finally, we evaluate the method.

Description: Managing uncertainty levels is important for organizations carrying out complex product development processes since it fosters design process improvements and optimization. Among the different uncertainties, design imprecision is known to represent uncertainty in decision-making that typically triggers changes to the value assigned to design variables during the early stages of the development process. This paper presents a method aiming to support large organizations understanding, quantifying and communicating this type of uncertainty. The imprecision management method that is proposed relies on five main steps: collection of historical records of change, time evolution reconstruction, statistical characterization of the typical levels of imprecision that should be expected, communication to new projects and continuous knowledge update. In addition, we present results from a case-study performed at Rolls–Royce that tested the method’s applicability in practice. The study shed light to interesting empirical findings about the typical level of imprecision in design variables and its evolution during real product development projects. The results from this initial evaluation suggest that the method provides useful support for design process management and thus has industrial value.

Description: In the design process of products or systems, a current trend consists in taking into account judgments of users. In this context, a multiobjective optimisation method taking into account judgments of a panel of subjects is proposed. It is aimed at identifying the best trade-offs between quantitative objectives and judgments of users. The method is divided in two steps: (1) judgment data acquisition and (2) integration of the judgment data into the multiobjective optimisation process. The method is based on a stochastic Pareto-based evolutionary algorithm for optimisation and on a multilinear interpolation for judgment modelling. The combination of these techniques makes it possible to solve complex problems, with up to eight decision variables and up to at least eight objectives. Relevant applications of the method include optimisation with judgments about various aspects of the product or system, identification of the best trade-offs satisfying at the same time several groups with different judgments, and analysis of the interest of market segmentation. For illustration purpose, a pilot study about an individual office lighting design problem is processed.

Description: Despite the development of a variety of decision-aid tools for assessing the value of a conceptual design, humans continue to play a dominant role in this process. Researchers have identified two major challenges to automation, namely the subjectivity of value and the existence of multiple and conflicting customer needs. A third challenge is however arising as the amount of data (e.g., expert judgment, requirements, and engineering models) required to assess value increases. This brings two challenges. First, it becomes harder to modify existing knowledge or add new knowledge into the knowledge base. Second, it becomes harder to trace the results provided by the tool back to the design variables and model parameters. Current tools lack the scalability and traceability required to tackle these knowledge-intensive design evaluation problems. This work proposes a traceable and scalable rule-based architecture evaluation tool called VASSAR that is especially tailored to tackle knowledge-intensive problems that can be formulated as configuration design problems, which is demonstrated using the conceptual design task for a laptop. The methodology has three main steps. First, facts containing the capabilities and performance of different architectures are computed using rules containing physical and logical models. Second, capabilities are compared with requirements to assess satisfaction of each requirement. Third, requirement satisfaction is aggregated to yield a manageable number of metrics. An explanation facility keeps track of the value chain all along this process. This paper describes the methodology in detail and discusses in particular different implementations of preference functions as logical rules. A full-scale example around the design of Earth observing satellites is presented.

Description: Design tasks need to be rescheduled and reprioritised frequently during product development. Inappropriate priority decisions generate rework; thus, the policy used to guide such decisions may have a significant effect on design cost and lead time. Generic priority rules provide easily implementable guidelines for task prioritisation and are theoretically effective for many planning problems. But can they be used in design processes, which include iteration, rework and changes? In this article, a discrete-event simulation model is developed to investigate priority policies in design. The model explores the combined effects of progressive iteration, rework and change propagation during design of interconnected parts in a product architecture. Design progression is modelled as an increase in the maturity of parts; rework and change propagation cause maturity levels in certain parts to reduce. Twelve product architecture models ranging in size from 7 to 32 elements are simulated to draw qualitative and general insights. Sensitivity of the findings to assumptions and model inputs is tested. Generally effective priority policies are identified, and their impact is shown to depend on the interconnectedness and organisation of product architecture, as well as the degree of concurrency in the design process.

Description: When developing an artifact, designers must first capture and represent user needs. These needs can then be transformed into system requirements or objectives. The contribution of this work is rooted in the formalization of the affordance-based approach for capturing user needs in the early stages of design. This formalization comes in three forms: the first affordance basis for engineering design (a defined set of affordances), a formal structure for affordance statements, and a new relational model structure. This formalization is intended to improve model quality and consistency, while managing model creation resources. Further, this affordance-based approach to capturing user needs imposes a level of abstraction that forces solution independence yet is capable of capturing the large range of user needs. As such, the approach provides a structured approach to problem abstraction—the process of specifying user needs without reference to specific solutions. This affordance-based problem representation relies on other design process tools to help develop the actual artifact, which is also discussed.

Description: Design tasks need to be rescheduled and reprioritised frequently during product development. Inappropriate priority decisions generate rework; thus, the policy used to guide such decisions may have a significant effect on design cost and lead time. Generic priority rules provide easily implementable guidelines for task prioritisation and are theoretically effective for many planning problems. But can they be used in design processes, which include iteration, rework and changes? In this article, a discrete-event simulation model is developed to investigate priority policies in design. The model explores the combined effects of progressive iteration, rework and change propagation during design of interconnected parts in a product architecture. Design progression is modelled as an increase in the maturity of parts; rework and change propagation cause maturity levels in certain parts to reduce. Twelve product architecture models ranging in size from 7 to 32 elements are simulated to draw qualitative and general insights. Sensitivity of the findings to assumptions and model inputs is tested. Generally effective priority policies are identified, and their impact is shown to depend on the interconnectedness and organisation of product architecture, as well as the degree of concurrency in the design process.

Description: In the design process of products or systems, a current trend consists in taking into account judgments of users. In this context, a multiobjective optimisation method taking into account judgments of a panel of subjects is proposed. It is aimed at identifying the best trade-offs between quantitative objectives and judgments of users. The method is divided in two steps: (1) judgment data acquisition and (2) integration of the judgment data into the multiobjective optimisation process. The method is based on a stochastic Pareto-based evolutionary algorithm for optimisation and on a multilinear interpolation for judgment modelling. The combination of these techniques makes it possible to solve complex problems, with up to eight decision variables and up to at least eight objectives. Relevant applications of the method include optimisation with judgments about various aspects of the product or system, identification of the best trade-offs satisfying at the same time several groups with different judgments, and analysis of the interest of market segmentation. For illustration purpose, a pilot study about an individual office lighting design problem is processed.

Description: The parameter analysis method of conceptual design is studied in this paper with the help of C–K theory. Each of the fundamental design activities—idea generation, implementation of the idea as hardware and evaluation—is explained and defined as a specific sequence of C–K operators. A case study of designing airborne decelerators is used to demonstrate the modeling of the parameter analysis process in C–K terms. The theory is used to explain how recovery from an initial fixation took place, leading to a breakthrough in the design process. It is shown that the innovative power of parameter analysis is based on C-space “de-partitioning” and that the efficient strategy exhibited by parameter analysis can be interpreted as steepest-first, controlled by an evaluation function of the design path. This logic is explained as generalization of branch-and-bound algorithms by a learning-based, dynamically evolving evaluation function and exploration of a state space that keeps changing during the actual process of designing.

Description: Engineering changes are essential for any product development, and their management has become a crucial discipline. Research in engineering change management has brought about some methods and tools to support dealing with changes. This work extends the change prediction method through incorporation of a function–behaviour–structure (FBS) scheme. These additional levels of detail provide the rationales for change propagation and allow a more proactive management of changes. First, we develop the ontology of this method based on a comprehensive comparison of three seminal functional reasoning schemes. Then, we demonstrate the FBS Linkage technique by applying it to a diesel engine. Finally, we evaluate the method.

Description: Despite the development of a variety of decision-aid tools for assessing the value of a conceptual design, humans continue to play a dominant role in this process. Researchers have identified two major challenges to automation, namely the subjectivity of value and the existence of multiple and conflicting customer needs. A third challenge is however arising as the amount of data (e.g., expert judgment, requirements, and engineering models) required to assess value increases. This brings two challenges. First, it becomes harder to modify existing knowledge or add new knowledge into the knowledge base. Second, it becomes harder to trace the results provided by the tool back to the design variables and model parameters. Current tools lack the scalability and traceability required to tackle these knowledge-intensive design evaluation problems. This work proposes a traceable and scalable rule-based architecture evaluation tool called VASSAR that is especially tailored to tackle knowledge-intensive problems that can be formulated as configuration design problems, which is demonstrated using the conceptual design task for a laptop. The methodology has three main steps. First, facts containing the capabilities and performance of different architectures are computed using rules containing physical and logical models. Second, capabilities are compared with requirements to assess satisfaction of each requirement. Third, requirement satisfaction is aggregated to yield a manageable number of metrics. An explanation facility keeps track of the value chain all along this process. This paper describes the methodology in detail and discusses in particular different implementations of preference functions as logical rules. A full-scale example around the design of Earth observing satellites is presented.

Description: This paper presents a model of the way that designers move between situations when interpreting during design activity. Three hypotheses are presented that arise from this model: that designers change their situation during interpretation, that small changes in a source can lead to large changes in the representation and that changes to the situation have their origins in the experience of the designer. The paper demonstrates how this internal movement between situations can be computationally implemented using three examples. The systems implemented demonstrate the way that interpretation can lead to changes in the situation and present an example of how the changes to a designer’s situation can be guided by past experiences.

Description: We propose a framework for measuring the complexity of aerospace systems and demonstrate its application. A measure that incorporates size, coupling, and modularity aspects of complexity is developed that emphasizes the importance of indirect coupling and feedback loops in the system. We demonstrate how hierarchical modular structure in the system reduces complexity and present an algorithm to decompose the system into modules. The measure is tested and found to be scalable for large-scale systems involving thousands of components and interactions (typical in modern aerospace systems). We investigate the sensitivity of the measure and demonstrate the ability of the framework to identify incorrectness in system representation. The merits of the framework are exemplified through a case study comparing three spacecraft. The framework provides the designer with three key capabilities that can positively influence the aerospace (or other) design process: the ability to identify complex subsystems, the ability to classify misrepresentations, and the ability to trade-off commercially of the shelf (COTS) and non-COTS components.