The paper presents a Model-Driven approach for Product-Service System (PSS) Design promoting an increased digitalization of the PSS design process based on the combination of data-driven design (DDD) activities and value-driven design (VDD) methods. The approach is the results of an 8-year long research profile named (omitted for blind review) featuring the collaboration between (omitted for blind review) and nine industrial companies, in the field of PSS Design. It combines VDD models and the supporting data-driven activities in the frame of PSS design and aligns with the product value stream and the knowledge value stream in the product innovation process as described by Kennedy et al. (2008). The paper provides a high-level overview of the approach describing the different stages and activities, and provides references to external scientific contributions for more exhaustive descriptions of the research rationale and validity. The approach is meant to ultimately drive the development and implementation of a simulation environment for cross-functional and multi-disciplinary decision making in PSS, named Model-Driven Decision Arena, describe in the concluding part of the paper.
Heavy equipment manufacturers recognise an opportunity to realise customer value gains through offering new Product-Service Systems. Such transition implies a radical shift in how new systems are designed. Based on a set of interviews the paper investigates how radical PSS innovation can be enabled by the use of physical prototypes as boundary object to navigate early PSS design ambiguity. On such basis, suggestions for augmenting existing support tools are made in relation to the existing literature.
Product Service System (PSS) solutions have proven to be a valuable innovation approach for industry organizations to differentiate themselves in a competitive market. Modern interpretations of PSS design have urged a move towards developing transformative innovations which are more than the sum of their parts. Achieving this transition in PSS design requires new tools to support designers in broader exploration of the design space to find a potentially transformative solution concept. These solutions will involve looking three to four product generations in the future adding ambiguity to the inherent complexity of PSS solutions. To embody and gather insight on these complex concepts, this paper explores the impact of a tangible low fidelity scenario prototype activity in the early fuzzy front end of the PSS design process.
Prototypes are an established tool for rapidly increasing learning, communication and decision making rationale for design projects. The proven success has spawned a litany of approaches and methods for building and planning the efficient planning and construction of prototypes. Translating these methods into simple usable tools to assist novice designers has generated broadly applicable canvases to support prototyping across the design process. Product Service System design has similarly introduced prototyping methods and tools into the process. Presently there is a lack of support for generating early phase tangible prototypes for functional PSS design aimed at more radically innovative solutions instead of currently dominant traditional products with traditional add-on services. This work explores the viability of utilizing existing prototyping support tools in the context of early PSS design through workshops with student designers and practitioners. The data from these workshops illuminates the alignments and misalignment gaps presented as guidelines to enable better support for early PSS designers.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.