ALBERT

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.

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: 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: The work with ideas is perceived by both academics and industry to be an important element in new product development and has thus been the subject of investigation in many different research fields. In this paper, we investigate a specific case showing how a successful product was developed based on piecing together a number of ideas that were developed and disseminated in a large industrial company. We do this through an in-depth case study of the development of the energy-labeled circulation pump Alpha Pro, developed by one of the world’s leading pump manufacturers, Grundfos. Using a socio-technical approach, we focus especially on the actors involved and the contextual factors, and less on the detailed development of technical ideas. In our study, we observe that (1) ideas are pieced together from previous ideas and results; (2) ideas are implemented through continuous mobilization of support and development of legitimate arguments; and (3) idea work is also a socio-technical process, because contextual factors matter. We observe that idea work is an ongoing process undertaken across different projects, actors, departments, strategies, and visions within Grundfos, while also involving external actors outside Grundfos. Based on our socio-technical approach and observations, we begin to develop a broader understanding of idea work in new product development and sketch an analytical framework that can be used to make socio-technical analyses of product development projects in future research.

Description: In a recent publication, we presented a new strategy for engineering design and optimization, which we termed formulation space exploration. The formulation space for an optimization problem is the union of all variable and design objective spaces identified by the designer as being valid and pragmatic problem formulations. By extending a computational search into this new space, the solution to any optimization problem is no longer predefined by the optimization problem formulation. This method allows a designer to both diverge the design space during conceptual design and converge onto a solution as more information about the design objectives and constraints becomes available. Additionally, we introduced a new way to formulate multiobjective optimization problems, allowing the designer to change and update design objectives, constraints, and variables in a simple, fluid manner that promotes exploration. In this paper, we investigate three usage scenarios where formulation space exploration can be utilized in the early stages of design when it is possible to make the greatest contributions to development projects. Specifically, we look at formulation space boundary exploration, Pareto frontier generation for multiple concepts in the formulation space, and a new way to perform targeted boundary expansion. The benefits of these methods are illustrated with the conceptual design of an impact driver.

Description: This paper aims to develop a systematized theory on the thinking process at the ‘very early stage of design.’ Here, ‘very’ is used to exaggerate the beginning of design, which includes the time just prior to or the precise beginning of the so-called conceptual design. First, concept generation is segregated into two phases—the problem-driven phase and the inner sense-driven phase . With regard to theoretical approach, the concept generation process is discussed by comparing metaphor, abduction, and general design theory from the perspective of similarities and dissimilarities. In addition, property mapping , concept blending , and concept integration in thematic relation are explained methodologically. So far, these theories and methods have been discussed independently, and the relations among them have not been clarified. As a result, it was found that the concept generation process could be categorized into two types: first - order concept generation and high - order concept generation . Furthermore, it was shown that high - order concept generation is related to the inner sense-driven phase , whereas first - order concept generation is related to the problem-driven phase .

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: 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: In this paper, relying on the formal framework provided by one of the most recent design theories, C–K theory, we analyse the historical development of design theories in the particular case of German systematic design. We study the three moments in the development of design theories (1850, 1900 and 1950). The analysis leads to the three main research conclusions regarding design theorizing. (1) The development of design theories and methods corresponds to specific rationalizations of the design activity in historical contexts, characterized by types of products, science and knowledge production capacities. (2) While engineering sciences model known objects, design theories support reasoning on unknown objects. (3) Design methods do not target single innovations but aim to improve collective design capacities. Their performance can be assessed by the types of new objects they help design (generative capacity) and in terms of the capacities required by their users (conjunctive capacity). Historically, systematic design emerged as a formal framework with particularly strong generative and conjunctive capacities.

Description: Most empirical accounts of design suggest that designing is an activity where objects and representations are progressively constructed. Despite this fact, whether design is a constructive process or not is not a question directly addressed in the current design research. By contrast, in other fields such as Mathematics or Psychology, the notion of constructivism is seen as a foundational issue. The present paper defends the point of view that forms of constructivism in design need to be identified and integrated as a foundational element in design research as well. In fact, a look at the literature reveals at least two types of constructive processes that are well embedded in design research: first, an interactive constructivism, where a designer engages a conversation with media, that allows changing the course of the activity as a result of this interaction; second, a social constructivism, where designers need to handle communication and negotiation aspects, that allows integrating individuals’ expertise into the global design process. A key feature lacking these well-established paradigms is the explicit consideration of creativity as a central issue of design. To explore how creative and constructivist aspects of design can be taken into account conjointly, the present paper pursues a theoretical approach. We consider the roots of constructivism in mathematics, namely the Intuitionist Mathematics, in order to shed light on the original insights that led to the development of a notion of constructivism. Intuitionists describe mathematics as the process of mental mathematical constructions realized by a creative subject over time. One of the most original features of intuitionist constructivism is the introduction of incomplete objects into the heart of mathematics by means of lawless sequences and free choices. This allows the possibility to formulate undecided propositions and the consideration of creative acts within a formal constructive process. We provide an in-depth analysis of intuitionism from a design standpoint showing that the original notion is more than a pure constructivism where new objects are a mere bottom-up combination of already known objects. Rather, intuitionism describes an imaginative constructivist process that allows combining bottom-up and top-down processes and the expansion of both propositions and objects with free choices of a creative subject. We suggest that this new form of constructivism we identify is also relevant in interpreting conventional design processes and discuss its status with respect to other forms of constructivism in design.

Description: In this paper, a proof is given that in design methods, the relation between technical functions and their subfunctions in functional descriptions of technical products cannot be analysed as a formal relation of parthood. This result holds for design methods in which transformations of flows of energy, material and signals are accepted as functions. First, two specific categories of such technical functions are modelled. Second, the composition relation by which ordered sets of these functions define other functions is characterised. Third, it is shown that this composition relation for technical functions does not meet the basic postulates of parthood relations as given by mereology, the theory of parthood. It still may be beneficial to designing to take subfunctions informally as the parts of the functions they compose. Yet, the proof shows that when functional descriptions are formalised for, for instance, the development of automated design reasoning tools or for incorporation in engineering ontologies, the composition relation for technical functions cannot unconditionally be taken as a parthood relation.

Description: This paper studies the influence of the type of method, intuitive or logical, used for idea-generation on the final creative results. An experiment was developed in which 16 design teams were asked to solve a design problem using different creative methodologies. Seven of the teams used the SCAMPER intuitive method and another seven teams used the TRIZ logical method. Two groups acted as control. One of these control groups used brainstorming, and other group used no method. The creativity of the results, considered as the combination of novelty and utility, was evaluated using the Analytical Hierarchy Process. Results show the differences in these parameters in the different methods used in the experiment.

Description: The innovation process may be divided into three main parts: the front end (FE), the new product development (NPD) process, and the commercialization. Every NPD process has a FE in which products and projects are defined. However, companies tend to begin the stages of FE without a clear definition or analysis of the process to go from Opportunity Identification to Concept Generation; as a result, the FE process is often aborted or forced to be restarted. Koen’s Model for the FE is composed of five phases. In each of the phases, several tools can be used by designers/managers in order to improve, structure, and organize their work. However, these tools tend to be selected and used in a heuristic manner. Additionally, some tools are more effective during certain phases of the FE than others. Using tools in the FE has a cost to the company, in terms of time, space needed, people involved, etc. Hence, an economic evaluation of the cost of tool usage is critical, and there is furthermore a need to characterize them in terms of their influence on the FE. This paper focuses on decision support for managers/designers in their process of assessing the cost of choosing/using tools in the core front end (CFE) activities identified by Koen, namely Opportunity Identification and Opportunity Analysis . This is achieved by first analyzing the influencing factors (firm context, industry context, macro-environment) along with data collection from managers followed by the automatic construction of fuzzy decision support models (FDSM) of the discovered relationships. The decision support focuses upon the estimated investment needed for the use of tools during the CFE. The generation of FDSMs is carried out automatically using a specialized genetic algorithm, applied to learning data obtained from five experienced managers, working for five different companies. The automatically constructed FDSMs accurately reproduced the managers’ estimations using the learning data sets and were very robust when validated with hidden data sets. The developed models can be easily used for quick financial assessments of tools by the person responsible for the early stage of product development within a design team. The type of assessment proposed in this paper would better suit product development teams in companies that are cost-focused and where the trade-offs between what (material), who (staff), and how long (time) to involve in CFE activities can vary a lot and hence largely influence their financial performances later on in the NPD process.

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: 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: 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: 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: 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.