Functional design is regarded as a design activity primarily aimed at clarifying customer needs, and developing the functional architecture and solution concepts for a system under development. Existing functional design approaches are mainly focused on how to assist designers in searching for solution principles for desired products, which, however, do not adequately take into account the interactions between a smart system under development and its environment, and cannot explicitly represent the complex functional logic of the system, resulting in that they cannot effectively assist designers in the functional design of smart systems. Therefore, this paper proposes a scenario-integrated approach for functional design of smart systems to address the above issues. Based on the concept of scenario in software engineering, the proposed approach explicitly elaborates how to employ scenarios to express subjective customer needs and how to generate the functional architectures and the corresponding solution concepts through a structured process. The functional design of the automated doors-unlocking system of a smart vehicle is employed to illustrate the proposed approach, which also demonstrates that the proposed approach is suitable for functional design of smart systems.

This paper aims to situate functional abstraction in light of systems thinking. While function does not extensively appear in systems thinking literature, the literature does identify function as part of systems thinking that enables us to recognize and connect that function has a role in building a systems thinking approach for students. A systems thinking approach is valuable for students since it helps them view a system holistically. In this research, we measure how well students are able to abstract function. We asked students to generate functions for two different products and examined how students taught functional modeling and function enumeration compare to students who are only taught function enumeration. The student responses were examined using a rubric that we developed and validated for assessing function. This rubric may be used to classify functions by correctness (correct, partially correct, and incorrect) and categories (high level, interface, low level, and ambiguous). On questions where students were not explicitly asked to write a high-level function or low-level function, and so on, students who were taught functional modeling were able to better demonstrate systems thinking in their responses (low-level and interface functions) than those students who were only taught function enumeration.

Critical chains composed of critical flows and functions have been demonstrated as an effective qualitative analogy retrieval approach based on performance metrics. In prior work, engineers used expert knowledge to transform functional models into critical chain models, which are abstractions of the functional model. Automating this transformation process is highly desirable so as to provide for a robust transformation method. Within this paper, two paradigms for functional modeling abstraction are compared. A series of pruning rules provide an automated transformation approach, and this is compared to the results generated previously through an expert knowledge approach. These two approaches are evaluated against a set of published functional models. The similarity of the resulting transformation of the functional models into critical chain models is evaluated using a functional chain similarity metric, developed in previous work. Once critical chain models are identified, additional model evaluation criteria are used to evaluate the utility of the critical chain models for design analogy identification. Since the functional vocabulary acts as a common language among designers and engineers to abstract and represent critical design artifact information, analogous matching can be made about the functional vocabulary. Thus, the transformation of functional models into critical chain models enables engineers to use functional abstraction as a mechanism to identify design analogies. The critical flow rule is the most effective first step when automatically transforming a functional model to a critical chain model. Further research into more complex critical chain model architectures and the interactions between criteria is merited.

Research on design and analysis of complex systems has led to many functional representations with several meanings of function. This work on conceptual design uses a family of representations called structure–behavior–function (SBF) models. The SBF family ranges from behavior–function models of abstract design patterns to drawing–shape–SBF models that couple SBF models with visuospatial knowledge of technological systems. Development of SBF modeling is an instance of cognitively oriented artificial intelligence research that seeks to understand human cognition and build intelligent agents for addressing complex tasks such as design. This paper first traces the development of SBF modeling as our perspective on design evolved from that of problem solving to that of memory and learning. Next, the development of SBF modeling as a case study is used to abstract some of the core principles of an artificial intelligence methodology for functional modeling. Finally, some implications of the artificial intelligence methodology for different meanings of function are examined.

Understanding product functions is a key aspect of the work undertaken by engineers involved in complex system design. The support offered to these engineers by existing modeling tools such as the function tree and the function structure is limited because they are not intuitive and do not scale well to deal with real-world engineering problems. A research collaboration between two universities and a major power system company in the aerospace domain has allowed the authors to further develop a method for function analysis known as function analysis diagram that was already in use by line engineers. The capability to generate and edit these diagrams was implemented in the Decision Rationale editor, a software tool for capturing design rationale. This article presents the intended benefits of the method and justifies them using an engineering case study. The results of the research have shown that the function analysis diagram method has a simple notation, permits the modeling of product functions together with structure, allows the generation of rich and accurate descriptions of product functionality, is useful to work with variant and adaptive design tasks, and can coexist with other functional modeling methods.

Authors across disciplines propose functional modeling as part of systematic design approaches, in order to support and guide designers during conceptual design. The presented research aims at contributing to a better understanding of the diverse functional modeling approaches proposed across disciplines. The article presents a literature review of 41 modeling approaches from a variety of disciplines. The analysis focuses on what is addressed by functional modeling at which point in the proposed conceptual design process (i.e., in which sequence). The gained insights lead to the identification of specific needs and opportunities, which could support the development of an integrated functional modeling approach. The findings suggest that there is no such shared sequence for functional modeling across disciplines. However, a shared functional modeling perspective has been identified across all reviewed disciplines, which could serve as a common basis for the development of an integrated functional modeling approach.

Conceptual design produces a number of functions the designed product is to fulfill, several solution principles (means) for each function, and multiple overall principle solutions (concepts). Besides concept synthesis, it is important to determine the (few) early solution properties that are of interest at the concept stage. Further activities are assessing the consequences of the chosen means and their instantiation, the effects of changes, and how decisions affect other elements. Using a quantitative functional representation can facilitate these tasks, but a balance is needed between product-dependent tools predicting many detailed properties, and product-independent, generally applicable tools with limited prediction capabilities. A balance between a closed, general set of predefined building blocks and extensibility by modeling application-specific, individual elements is also necessary. In this paper, a generally applicable conceptual design model is presented, which has been established by theoretical reasoning applied to a number of products. These products were the subjects of previous company-ordered student projects. The resulting information model spans continuously from requirements to concepts and permits modeling desired functionality (functions), achieved functionality (means and their value choices), and explicit constraints (internal and external relations between parameters of requirements, functions and means). To indicate the suitability in principle, the model has been implemented in an interactive, incremental prototype for computer support that permits modeling, storage, and reuse in a database. It can be concluded that the model permits explicit modeling of complex relations, automatic change propagation, and handling of many concept alternatives. Integrated, bidirectional, and continuous connections from requirements to concepts facilitate conceptual design, reuse, documentation of the results, and allow changes to be made and their effects assessed easily. Incremental constraint networks are approved, for example, in configuration design or geometry modelers, and the significance of this article is to enable their use also for quantitative analysis of incomplete, evolving concepts in original design tasks allowing different principle solutions, and for various products of mechanical design.

This paper is an informal description of some recent insights about what a device function is, how it arises in response to needs, and how function arises from the structure of a device and the functions of its components. These results formalize and clarify a set of contending intuitions about function that researchers have had. The paper relates the approaches, results, and goals of this stream of research, called functional representation (FR), with the functional modeling (FM) stream in engineering. Despite the occurrence of the term function in the two streams, often the results and techniques in the two streams appear not to have much to do with each other. I argue that, in fact, the two streams are performing research that is mutually complementary. FR research provides the basic layer for device ontology in a formal framework that helps to clarify the meanings of terms such as function and structure, and also to support representation of device knowledge for automated reasoning. FM research provides another layer in device ontology, by attempting to identify behavior primitives that are applicable to subsets of devices, with the hope that functions can be described in those domains with an economy of terms. This can lead to useful catalogs of functions and devices in specific areas of engineering. With increased attention to formalization, the work in FM can provide domain-specific terms for FR research in knowledge representation and automated reasoning.