Cloud-Based Automated Design and Additive Manufacturing: A Usage Data-Enabled Paradigm Shift

Abstract

Integration of sensors into various kinds of products and machines provides access to in-depth usage information as basis for product optimization. Presently, this large potential for more user-friendly and efficient products is not being realized because (a) sensor integration and thus usage information is not available on a large scale and (b) product optimization requires considerable efforts in terms of manpower and adaptation of production equipment. However, with the advent of cloud-based services and highly flexible additive manufacturing techniques, these obstacles are currently crumbling away at rapid pace. The present study explores the state of the art in gathering and evaluating product usage and life cycle data, additive manufacturing and sensor integration, automated design and cloud-based services in manufacturing. By joining and extrapolating development trends in these areas, it delimits the foundations of a manufacturing concept that will allow continuous and economically viable product optimization on a general, user group or individual user level. This projection is checked against three different application scenarios, each of which stresses different aspects of the underlying holistic concept. The following discussion identifies critical issues and research needs by adopting the relevant stakeholder perspectives.

Design for Additive Manufacturing: Trends, opportunities, considerations, and constraints

“…Eventually, most production scale AM will be done with cyber-physical manufacturing systems. The direct digital nature of AM combined with the use of cyber-physical systems will allow for cloud-based AM [186]. The benefits of cloud-based approaches have already been demonstrated in process optimization [320], adaptive process planning [235], shop-floor planning [234], scheduling [236], and maintenance [237].…”

“…The first commercial 3D printer with the ability to print conductive tracks and embed objects is scheduled to ship in 2016 [340]. For a review of sensor integration in AM, see [186]. Fig.…”

Digital Product Innovation in Manufacturing Industries - Towards a Taxonomy for Feedback-driven Product Development Scenarios

“…Indicated by the case studies and grounded in extant work [7], D5 describes the degree of feedback processing autonomy. Feedback can be incorporated completely manually (C5.1), partially automated (C5.2), or completely automated (C5.3).…”

“…On closer examination, industrial enterprises have very limited information about the actual usage of their products once they are sold to their customers [2,4,5]. Although it is widely acknowledged that information about product usage is highly beneficial for the development of future products [2,4,6,7], manufacturers scarcely get feedback from the field -with the exception of selective snapshots from customer service or even complaints from customers. Conditioned by lacking technological capabilities, product usage has received little attention from product development departments in the past.…”

“…However, in the light of pervasive digitalization, traditional physical products get augmented with digital components [8,9,10] that create the potential of making the whole product lifecycle visible for product developers [2,4,7]. Traditional industrial products ranging from heavy engineer-to-order machinery to automotive make-to-stock-planning modules get infused with digital technologies such as sensors, networks, and processors [8,9,10].…”