One problem in incremental product development is that geometric models are limited in their ability to explore radical alternative design variants. In this publication, a function modeling approach is suggested to increase the amount and variety of explored alternatives, since function models (FM) provide greater model flexibility. An enhanced function-means (EF-M) model capable of representing the constraints of the design space as well as alternative designs is created through a reverse engineering process. This model is then used as a basis for the development of a new product variant. This work describes the EF-M model's capabilities for representing the design space and integrating novel solutions into the existing product structure and explains how these capabilities support the exploration of alternative design variants. First-order analyses are executed, and the EF-M model is used to capture and represent already existing design information for further analyses. Based on these findings, a design space exploration approach is developed. It positions the FM as a connection between legacy and novel designs and, through this, allows for the exploration of more diverse product concepts. This approach is based on three steps – decomposition, design, and embodiment – and builds on the capabilities of EF-M to model alternative solutions for different requirements. While the embodiment step of creating the novel product's geometry is still a topic for future research, the design space exploration concept can be used to enable wider, more methodological, and potentially automated design space exploration.

Research and industrial practice have produced a host of function models and modeling approaches over the last decades. Each of these is meant to support designers in their design endeavors. Industrial practice is excessively diversified in terms of contextual requirements, aims, and adopted processes; this automatically begs the question which of the existing models should be selected for application in a specific situation. This paper sets out to contribute to this discourse. It strives to benchmark the fairly novel integrated function modeling (IFM) framework against the well-established function structures modeling approach. The paper comparatively investigates the respective capabilities of the approaches, following the benchmarking protocol used earlier in relation to this Special Issue. Function structures are used as reference as they represent one of the most widespread function modeling approaches in research and practice. Both function structures and the IFM framework are exemplarily applied for modeling a glue gun. The gradual generation and refinement of the models is used to showcase their respective benefits and shortcomings. Eventually, the IFM framework is found to excel over function structures in terms of comprehensiveness and support for different types of function analyses. Finally, future research directions are proposed.

Modular product design is an efficient strategy to let manufacturing companies meet the customers’ requirements by offering a wide variety and customization of products and significantly saving time and cost during engineering and production (Fei et al., 2011). Despite numerous approaches for function modeling and modular product design (Srinivasan et al., 2012; Eckert, 2013; Vermaas, 2013) that have been developed in the last decades, carrying out an efficient product variants’ design process is still an open issue for many manufacturing companies. The proposed approaches offer numerous ways to model information about product functionality, but each approach is useful and particularly well suited for different applications and domains (Summers et al., 2013). The present research compares the existing approaches for product variants design and defines a function-based model to support product design and redesign according to a modular framework, merging qualitative technical issues with business-oriented evaluation. Such a framework has been used to develop a multiuser IT platform, composed of a knowledge-based engine and four different tools to support designers and engineers in product variants creation, management, and configuration, from product functional modeling to cost estimation and life cycle assessment. The proposed model has been tested on industrial cases in the context of household appliances. Experimental results demonstrates that, after a preliminary context analysis and a proper knowledge base creation, such a model supports a more conscious decision-making and promote collaboration within an interdisciplinary design team. Finally, the case study shows the necessity, but in the meanwhile the insufficiency, of a functional decomposition as the only representation viewpoint.

This paper introduces a rigorous framework for function modeling of complex multidisciplinary systems based on the system state flow diagram (SSFD). The work addresses the need for a consistent methodology to support solution-neutral function-based system decomposition analysis, facilitating the design, modeling, and analysis of complex systems architectures. A rigorous basis for the SSFD is established by defining conventions for states and function definitions and a representation scheme, underpinned by a critical review of existing literature. A set of heuristics are introduced to support the function decomposition analysis and to facilitate the deployment of the methodology with strong practitioner guidelines. The SSFD heuristics extend the existing framework of Otto and Wood (2001) by introducing a conditional fork node heuristic, to facilitate analysis and aggregation of function models across multiple modes of operation of the system. The empirical validation of the SSFD function modeling framework is discussed in relation to its application to two case studies: a benchmark problem (glue gun) set for the engineering design community; and an industrial case study of an electric vehicle powertrain. Based on the evidence from the two case studies presented in the paper, a critical evaluation of the SSFD function modeling methodology is discussed based on the function benchmarking framework established by Summers et al. (2013), considering the representation, modeling, cognitive, and reasoning characteristics. The significance of this paper is that it establishes a rigorous reference framework for the SSFD function representation and a consistent methodology to guide the practitioner with its deployment, facilitating its impact to industrial practice.

Functional modeling is an analytical approach to design problems that is widely taught in certain academic communities but not often used by practitioners. This approach can be applied in multiple ways to formalize the understanding of the systems, to support the synthesis of the design in the development of a new product, or to support the analysis and improvement of existing systems incrementally. The type of usage depends on the objectives that are targeted. The objectives can be categorized into two key groups: discovering a totally new solution, or improving an existing one. This article proposes to use the functional modeling approach to achieve three goals: to support the representation of physics-based reasoning, to use this physics-based reasoning to assess design options, and finally to support innovative ideation. The exemplification of the function-based approach is presented via a case study of a glue gun proposed for this Special Issue. A reverse engineering approach is applied, and the authors seek an incremental improvement of the solution. As the physics-based reasoning model presented in this article is heavily dependent on the quality of the functional model, the authors propose a general approach to limit the interpretability of the functional representations by mapping the functional vocabulary with elementary structural blocks derived from bond graph theory. The physics-based reasoning approach is supported by a mathematical framework that is summarized in the article. The physics-based reasoning model is used for discovering the limitations of solutions in the form of internal contradictions and guiding the design ideation effort.

Function modeling is considered potentially useful in various fields of engineering, including engineering design. However, a close look at practices reveals that practitioners do not use formal function modeling so much, while the concept of “function” frequently appears in many practical methods without a vigorous definition. This paper tries to understand why formal function modeling is not practically utilized in industry by analyzing usage cases of function. By observing product development activities in industry, the paper identifies three problems that prevent formal function modeling from wider applications in practices, namely, practitioners' neglect of function modeling, the lack of practically useful function reasoning, and the complexity of the methods and tools of formal function modeling that make them impractical. Finally, the paper proposes strategies to tackle these problems and illustrates some research efforts in this regard.

Function-based design and modeling have been taught, studied, and practiced in various forms for several years with efforts centered on using function modeling to help designers understand problems or to facilitate idea generation. Only limited focus has been placed on potential use for qualitative and quantitative reasoning and analysis of the design concept. This potential for early stage analysis has not been fully explored partly because computational reasoning tools have not been developed for this express purpose. This paper presents a set of requirements and their justification to realize this design enabling tool. The requirements include coverage, consistency, validity against physics laws, domain neutrality, physics-based definitions, normative and descriptive modeling, and qualitative and quantitative modeling and reasoning. Each requirement is defined in concrete terms and illustrated with examples and logic. With the requirements for function-based reasoning and representation clearly identified, future research toward formalizing of function-based design will be more focused and objective validation of proposed representations against these requirements would be possible.

The relative significance of conceptual design to basic design or detail design is widely recognized, due to its influential roles in determining the product's fundamental features and development costs. Although there are some general methodologies dealing with functions in design, virtually no commercial CAD systems can support functional design, in particular so-called synthetic phase of design. Supporting the synthetic phase of conceptual design is one of the crucial issues of CAD systems with function modeling capabilities. In this paper, we propose a computer tool called a Function-Behavior-State (FBS) Modeler to support functional design not only in the analytical phase but also in the synthetic phase. To do so, the functional decomposition knowledge and physical features in the knowledge base of the modeler, and a subsystem Qualitative Process Abduction System (QPAS) play crucial roles. Modeling scheme of function in relation with behavior and structure and design process for conceptual design in the FBS Modeler are described. The advantages of the FBS Modeler are demonstrated by presenting two examples; namely, an experiment in which designers used this tool and the design of functionally redundant machines, which is a new design methodology for highly reliable machines, as its application.

This work is aimed at establishing a common frame and understanding of function modeling (FM) for our ongoing research activities. A comparative review of the literature is performed to grasp the various FM approaches with their commonalities and differences. The relations of FM with the research fields of artificial intelligence, design theory, and maintenance are discussed. In this discussion the goals are to highlight the features of various classical approaches in relation to FM, to delineate what FM introduces to these fields, and to discuss the applicability of various FM approaches in these fields. Finally, the basic ideas underlying our projects are introduced with reference to the general framework of FM.