A scenario approach is often used to envision sustainable futures. Several important scenario design factors are identified in the literature, which include the demonstration of deliberation and the participation of stakeholders; however, specific methodologies of scenario design are yet to be established. Accordingly, in this study, we demonstrate a series of workshops involving ordinary citizens for energy visioning in Suita city, Japan, and propose a new citizen-participatory scenario design methodology based on the combination of scenario design and future design approaches. It is shown that the inclusion of future generations in deliberation is effective for creating future visions in a specific context and deriving policy implications. Specifically, by analyzing the deliberation process and the proposed scenarios, it was confirmed that the scenarios proposed by future generations were proactive in terms of paying the costs incurred to facilitate the realization of policies toward achieving a long-term vision. Furthermore, even though the proposals made by the future generations imposed additional burdens for current generations, post-workshop scenario assessment revealed that current generations are supportive of these scenarios. It is concluded that the proposed methodology is effective since it can overcome uncertainties, include holistic scopes, and consider a long-term time horizon.
This paper presents a case study of product architecture design for industrial robots, which extends the scope of conventional product architecture. Industrial robots are required to meet a wide range of customer needs depending on the end-use environment. While modularization with various options can effectively meet customer needs, the selection of options is often planned in a haphazard way, which may cause consumer confusion and result in non-optimal solutions. This research attempts to solve this issue by refining product architecture design with consideration of not only relationships between physical functions and entity structure, but also their relationships to customer needs. This study uses design structure matrixes (DSM) which represent the interactions between these three aspects (i.e. customer needs, physical functions, and entity structure), and domain mapping matrixes (DMM) which integrate the three DSMs. A function to evaluate the rationality and integrity of the module architecture is formulated with those DSMs and DMMs. A simulated annealing-based method is then used to explore optimal modular architectures. The case study shows that an industrial robot can be modularized to reflect customer needs, including those related to maintenance and productivity. IntroductionIndustrial robots are custom built to function in a variety of end-use environments and must meet individual user requirements quickly and economically. To achieve these goals, robot manufacturers often employ modularized option packages, allowing a manufacturer to customize the robot unit options in accordance with end-use environments (Benhabib and Dai, 1991). However, in recent years industrial robots have been applied to a growing set of diverse and complex tasks as customer needs and applications have proliferated. Robot manufacturers have responded to this growing set of needs by increasing the types of units and/or options they offer, often in a rather haphazard way. The result has sometimes been option packages offered to the customer that include excess or undesired equipment and are ill-suited to customers' needs. This is called consumer confusion.Product architecture (Ulrich, 1995) that addresses the relationships between the physical structure and functions of the product is important for product family design and modularization. A product's physical function can be changed independently by replacing components in its structure. This enables a variety of products that may satisfy various customer needs flexibly when product architecture is used to realize a one-to-one mapping from a physical function to a component structure. To design such product architecture, it is important to design modules that are as independent as possible, that is, to design modules that have relatively more interactions among physical functions and components within the modules than those outside the modules. It is a common approach for individual product design to consider customer needs, physical functions, and components, and link t...
Much attention has been paid internationally to the adoption of sustainable development goals to achieve sustainable outcomes. Although roadmapping is widely used by companies and other organizations to plan long-term strategies, relatively few studies have examined the development of roadmapping methods aiming at sustainability. To address this challenge, in this article, a backcasting-based method to design roadmaps that could be used to facilitate decision making and plan sustainable futures is proposed. By drawing on the concept of backcasting, the proposed roadmap design method consists of two phases: defining a sustainable vision, and describing the pathways that are required to realize that vision. In order to develop pathways that bridge the gap between the present and the vision, we develop a roadmap template called a "four-arrow model." To demonstrate the proposed method, roadmaps are developed for Japanese manufacturing from the present to 2050 by organizing an expert workshop. As a result, two different roadmaps that connected sustainable visions and associated pathways are successfully developed. The number of ideas generated through the workshop indicates that the proposed method encouraged brainstorming and concept development. Future research will focus on making the roadmap design process more comprehensive by conducting industrial case studies.
Generating novel design concepts is a cornerstone for producing innovative products. Although many methods have been proposed for supporting the task, their performance depends on human ability. The goal of this research is to build a method supporting designers to generate novel design concepts with the knowledge of what factors have positive effects on the novelty. Toward the goal, this research assumes that the more distant two function concepts chosen, the more novel idea would come up with by the combination of the two concepts. Based on the assumption, this paper introduces a notion of novelty potential of the combination of two function concepts, and proposes a method to assess it by the function similarity. It is calculated with the integration of a lexical database for natural language called WordNet and a distributional semantics method called word2vec. The proposed method is adapted to case studies in which students perform design concept generation for given design tasks. The correlation analysis is performed to verify the assessment performance of the proposed method. This paper discusses its possibility based on the results of the case studies.
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