Abstract.A new vision in manufacturing is to develop product-service integrated value solutions. Today, few firms have fully realized this vision because they are not able to support the reasoning in the early stages of design. The purpose of this paper is to discuss engineers' cognitive challenge when replacing the core product rationale with value logic. The paper problematizes engineering design by dividing knowledge into the categories technically constructed (explicit) and socially constructed (tacit). In doing so, this study contributes the assumed effects of a perspective shift that could guide the development of computational tools.
The manufacturing industry applies approaches in early development stages, i.e. product design, that heavily relies on computer support. The concept of Knowledge Based Engineering systems could represent this approach. However an ongoing trend in manufacturing industry to increase the service contents in their offerings is commonly captured beneath the umbrella term Product-Service Systems (PSS). The paper discusses conceptual examples for changes in product design caused by this increased PSS focus. The examples given are brief descriptions of different demonstrators developed in research projects focusing on PSS and product development in early phases. Examples include a discussion how companies shift from single company to becoming inter-organizational partners, how intangible knowledge, and information in the design process can be made tangible and how companies and engineersshift focus from knowledge transfer to sharing experiences.
In this paper empirical finding from a study conducted at an aerospace company is compared to theory regarding Experience Feedback (EF), Lessons Learned (LL) and Decision Making (DM). The purpose with the study was to examine how EF within the organization was conducted and what problems and possibilities that was seen. A qualitative approach was taken and interviews and a workshop was conducted. The empirical findings show that EF exist on different levels within the organization but current feedback processes are currently leaning more towards archiving and storing than knowledge sharing and learning. Also passive dissemination approaches are mostly used whereas active dissemination within the correct context is needed The aim with this paper is to discuss issues and empirical findings that should be considered when creating work methods and systems that support learning by EF and LL dissemination. NOMENCLATURE INTRODUCTIONIndustry is experiencing an increased competition making it challenging to stay ahead by technological advantage, and opportunities ending up in business with smaller margins. As a strategic shift industry is turning towards competing with knowledge and extended offerings [1] in order to 'do faster, do better, do correct' and gain advantage over competitors [2]. In the past, industry focused a lot to make the manufacturing process faster, better and more robust. One of the issues was to increase productivity with maintained or increased quality of the final product. To achieve this, methods have been developed to make the design and manufacturing more effective and faster. Not being able to compete solely with production effectiveness, the race has turned to make the products and offerings more innovative.Innovative design creates new demands both at the product development process but also on the manufacturing process. Thus, novel ideas regarding manufacturing processes have to be developed simultaneously.Future manufacturing systems have to be developed and adapted for rapid and agile production due to that innovation have become more common from project to project. That is, many projects starts afresh, calling for deeper insights in what is similar to previous projects and what is really new, and how customer value is addressed. The increased pace of innovations between project-to-project makes it important to reuse knowledge and experience. This means that efforts to improve process efficiency focus product development and research and development (R&D) processes, rather than production processes, by managing knowledge and experience from ongoing and previous projects making it available throughout the development process and beyond. Hence competition based on knowledge and competence in early development and innovation has come into play [3].
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