Improving Product-Service Systems by Exploiting Information From The Usage Phase. A Case Study

Lützenberger, Johannes; Klein, Patrick; Hribernik, Karl; Thoben, Klaus‐Dieter

doi:10.1016/j.procir.2016.03.064

Cited by 33 publications

(25 citation statements)

References 6 publications

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“…In the platform this is supported by a business logic module ( Figure 2). Established statistical functions have been incorporated for such a filtering and chosen with respect to needs of the designers and product developers (Lützenberger et al, 2016). Afterwards the outcome of aggregation and filtering can be mapped to the design parameters of the product or to be more precise to the affected component.…”

Section: Data Analytics In Falconmentioning

confidence: 99%

“…Tools and applications covering the functions typically requested by stakeholders are provided within a browser-based collaborative environment, which facilitates a synchronised, common view for multiple users working at different locations, who can filter, visualise and analyse PUI via an intuitive GUI. A dedicated modelling language called KbeML has been defined as an extension of SysML, which supports experts in modelling, communicating and documenting information flows and transformations related to their PUI-based development activities, allowing tracking and documenting PUI transformation and analysis operations (Lützenberger et al, 2016).…”

Section: Iced19mentioning

confidence: 99%

“…Further data and information may become relevant to other components than the ones related to which they are acquired. (Lützenberger et al, 2016). For instance temperature monitoring used to control a fridge can be used as input for the design of insulation of a sibling fridge model and analytic functions will provide max and average temperature values typically used for dimensioning the insulation layer.…”

Section: Introductionmentioning

confidence: 99%

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Towards an Approach Integrating Various Levels of Data Analytics to Exploit Product-Usage Information in Product Development

Klein

Vegte

Hribernik³

et al. 2019

Proc. Int. Conf. Eng. Des.

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By applying data analytics to product usage information (PUI) from combinations of different channels, companies can get a more complete picture of their products’ and services’ Mid-Of-Life. All data, which is gathered within the usage phase of a product and which relates to a more comprehensive understanding of the usability of the product itself, can become valuable input. Nevertheless, an efficient use of such knowledge requires to setup related analysis capabilities enabling users not only to visualize relevant data, but providing development related knowledge e.g. to predict product behaviours not yet reflected by initial requirements.The paper elaborates on explorations to support product development with analytics to improve anticipation of future usage of products and related services. The discussed descriptive, predictive and prescriptive analytics in given research context share the idea and overarching process of getting knowledge out of PUI data. By implementation of corresponding features into an open software platform, the application of advanced analytics for white goods product development has been explored as a reference scenario for PUI exploitation.

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Section: Data Analytics In Falconmentioning

confidence: 99%

Section: Iced19mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Towards an Approach Integrating Various Levels of Data Analytics to Exploit Product-Usage Information in Product Development

Klein

Vegte

Hribernik³

et al. 2019

Proc. Int. Conf. Eng. Des.

Self Cite

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“…Moreover, this can help schedule maintenance, diagnose problems, and serve as a great indicator for future developments. Product Usage Information (PUI) can also be key in developing future products as they assist in the development of PSS directly from customer feedback (Lutzenberger et al, 2016). Knowing how a customer uses its product, service, or PSS allows to understand the true, often implicit, requirements better.…”

Section: Product Usage Information (Pui)mentioning

confidence: 99%

Identifying Key Aspects of Success for Product Service Systems

Smith¹,

Wuest²

2017

Advances in Production Management Systems. The Path to Intelligent, Collaborative and Sustainable Manufacturing

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As companies struggle with the various challenges of their PSS, identification and elimination of possible errors and potential challenges early in the design phase is crucial. This paper aims to identify the universal key aspects of success for a PSS; thus, providing a general foundation for many companies within the industry to focus their initial efforts. Utilizing historical and contemporary literature within the PSS field, one central aspect was identified with three additional aspects serving to support the core aspect that all PSS are centered around-creating customer value. Standardization, product usage information (PUI), and environmental sustainability all support the goal of ultimately adding customer value. While there is a potentially unlimited number of additional individual supporting aspects that are important and contribute to this objective, these do not apply to all PSS universally. As a combinational effort, the three supporting aspects help to ensure that value is added to the customer in different, but related routes. These aspects involved may be utilized to allow companies to examine and analyze their current PSS and implement these aspects into their PSS operations and/or, ideally, reflecting on them during the PSS design phase. A limitation of this study is, that the universal nature of the 4 identified key aspects reflects only the PSS cases within the literature reviewed.

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“…This initially supports the development and integration of technical systems, such as Internet-of-Things technologies and socalled condition monitoring technologies. The collection of technical data on complex systems leads to the overall operational use of the system during the operating and maintenance phase and to optimise new product generations from the derived information [7]. As an overarching model for solving these challenges, different aspects must be taken into account in project development.…”

Section: General Conceptmentioning

confidence: 99%

Deriving Information from Sensor Data

Lewandowski

Thoben

2017

Product Lifecycle Management and the Industry of the Future

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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Improving Product-Service Systems by Exploiting Information From The Usage Phase. A Case Study

Cited by 33 publications

References 6 publications

Towards an Approach Integrating Various Levels of Data Analytics to Exploit Product-Usage Information in Product Development

Towards an Approach Integrating Various Levels of Data Analytics to Exploit Product-Usage Information in Product Development

Identifying Key Aspects of Success for Product Service Systems

Deriving Information from Sensor Data

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