Stefan Wellsandt

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

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.

A survey of product lifecycle models: towards complex products and service offers

Lifecycle thinking is a concept that is used to express a holistic perspective on conventional and extended products, such as Product-Service Systems and Cyber-Physical Systems. Many authors of academic literature make use of this concept by defining or reusing product lifecycle models. Those models express how products are designed, produced, delivered, used, maintained and finally recycled or disposed of. The goal of this paper is to describe differences between lifecycle models, in order to clarify how heterogeneous the models are. A selection of 71 visual models was extracted from literature and analysed. The analysis addresses the preferences in modelling based on paper context, geometric topology of models, and the number of lifecycles contained in a single representation of the product lifecycle. The outlook of this paper suggests topics for future research, such as covering multiple lifecycles at once and discussing whether lifecycle models should be expressed with a common language.

Information Quality in PLM: A Production Process Perspective

Recent approaches for Product Lifecycle Management (PLM) aim for the efficient utilization of the available product information. A reason for this is that the amount of information is growing, due to the increasing complexity of products, and concurrent, collaborative processes along the lifecycle. Additional information flows are continuously explored by industry and academia – a recent example is the backflow of information from the usage phase. The large amount of information, that has to be handled by companies nowadays and even more in the future, makes it important to separate the “fitting” from the “unfitting” information. A way to distinguish both is to explore the quality of the information, in order to find those information that are “fit for purpose” (information quality). Since the amount of information is so large and the processes along the lifecycle are diverse in terms of their expectations about the information, the problem is similar to finding a needle in a hay stack.This paper is one of two papers aiming to address this problem by giving examples why information quality matters in PLM. It focuses on one particular lifecycle process, in this case production. An existing approach, describing information quality by 15 dimensions, is applied to the selected production process.

Information Quality in PLM: A Product Design Perspective

Recent approaches for Product Lifecycle Management (PLM) aim for the efficient utilization of the available product information. A reason for this is that the amount of information is growing, due to the increasing complexity of products, and concurrent, collaborative processes along the lifecycle. Additional information flows are continuously explored by industry and academia – a recent example is the backflow of information from the usage phase. The large amount of information that has to be handled by companies nowadays and even more in the future, makes it important to separate “fitting” from “unfitting” information. A way to distinguish both is to explore the characteristics of the information, in order to find those information that are “fit for purpose” (information quality). Since the amount of information is so large and the processes along the lifecycle are diverse in terms of their expectations about the information, the problem is similar to finding a needle in a hay stack.

Modellierung der Lebenszyklen von Smart Services

Smart Services sind ein Ansatz fur die IT-gestutzte Erbringung von Dienstleistungen auf Basis vernetzter Produkte. Sie schaffen eine neue Grundlage fur die Gestaltung der Beziehung zwischen Hersteller und Endnutzer sowie die Auspragung neuer Wertschopfungsstrukturen. Den damit verbundenen Potenzialen steht ein hoher Anspruch an die Konzeption und das Management von Smart Services entgegen. Dieser entsteht unter anderem durch die Komplexitat des zugrundeliegenden Cyber-Physischen Systems (CPS) und den individuellen Lebenszyklen der einzelnen Bestandteile. Zudem sind verschiedene Akteure und ihre Aufgaben in der Dienstleistungserbringung sowie verschiedene materielle und immaterielle Leistungen sowie Material-, Informations- und Geldflusse zu beachten. In diesem Beitrag untersuchen wir das Unterstutzungspotenzial der Modellierung von Smart Services mit der Lifecycle Modeling Language (LML). Am Beispiel der automatisierten Nachlieferung von Verbrauchsmaterial fur einen 3D-Drucker wird beurteilt, welche Vorteile mit der Modellierung der Lebenszyklen von Smart Services verbunden sind.

Considerations on a Lifecycle Model for Cyber-Physical System Platforms

Cyber-physical system platforms are information infrastructures connecting different cyber-physical systems and other information systems. This infrastructure is the base for realizing the “Industrie 4.0” paradigm aiming for collaborative industrial processes involving smart objects and smart factories. In inter-organizational value networks, a cyber-physical system platform becomes a shared resource that has to be managed cooperatively along its lifecycle. This paper looks at cyber-physical system platforms from a lifecycle perspective. It describes the complexity of networks of cyber-physical systems and cyber-physical system platforms within value networks and the resulting restrictions influencing their various lifecycles. A selection of different lifecycle models from literature is reviewed to extract aspects that provide a promising basis for the development of a specific lifecycle model of cyber-physical system platforms.

Content analysis of product usage information from embedded sensors and web 2.0 sources: A first analysis of practical examples

The middle of a products life is when the product is with the user. During the middle of life (MOL) phase, useful product information is created (usage information). In the past, research in engineering focused on the transformation of this information into engineering knowledge - for this purpose, demonstrators were developed and described in literature. Apart from demonstrating the feasibility of the approach, little is known about the vast body of usage information. This research is based on the analysis of real information manually extracted from a small selection of contents. Selected contents have been taken from a product embedded sensor device, a shopping website (Amazon.com), a review website (Engadget.com) and a media platform (Youtube.com). Based on the discussion of the findings, a tree-like structure is proposed, summarizing the preliminary content-related characteristics of usage information identified in this paper. Among these characteristics are the originators, sources, lifecycle activities covered, formats and the scope of information from the middle of life.

The Internet of Experiences – Towards an Experience-Centred Innovation Approach

The paper depicts an experience-centred approach for innovation enabled by the Internet of Experiences. Based on findings from innovation research as well as the internet-based approaches of the web 2.0 and the Internet of Things, it is argued that artificial systems, e.g. intelligent products, are capable to make experience on their own out of interactions, similar to user-experience today. After an introduction into the field of “experience” from a knowledge management perspective, a broad definition for experience is suggested. According to this definition, the experience-making possibility of artificial conscious systems is substantiated. Based on these findings, an experience-centred innovation approach, utilizing experience from intelligent objects and human users, is argued. The main outcome of this section is a depiction of the Internet of Experiences.

Life Cycle Management for Product-Service Systems

Product-Service Systems (PSS) and the Internet of Things (IoT) are two related concepts. This chapter describes an approach to manage PSS along its life cycle. It includes a design methodology for PSS and a systems modelling method. The former supports designers in defining PSSs that incorporate monitoring, control, optimization or autonomy. It includes a new method to assess a product’s functionality in terms of the data needed for its realization. The latter adopts life cycle thinking and employs a modelling language to outline the PSS and its various components and actors. A life cycle performance analysis could benefit from the model by extracting cost information from it for further analysis. This chapter highlights challenges related to PSS life cycle management observed during the Manutelligence project. They concern the design methodology and the applied life cycle modelling method.

Modelling of a Smart Service for Consumables Replenishment

Smart services are an approach for the IT-supported provision of services based on networked products. They enable new relationships between manufacturers and end users, as well as the establishment of new value-creation networks. To gain benefits from these potentials, service providers face the challenges of designing and managing smart services. This is mainly due to the complexity of the underlying cyber-physical system (CPS) as well as the individual life cycles of components and third-party services it consists of. Additionally, a number of actors and their tasks, various tangible and intangible benefits, as well as flows of material, information and money need to be considered during the planning and provisioning of the service. In this paper, we investigate the potential of modelling smart services with the Lifecycle Modeling Language (LML). To this end, we analyse the fulfillment of information need of different stakeholders based on a consumable material replenishment service for 3D printers.