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

机译:通过在使用阶段利用信息来改善产品服务系统。案例研究

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摘要

Nowadays the relevance of Product-Service-Systems (PSS) is increasing. Providing customers with products and supporting services suiting the customer expectations becomes a key-factor for being successful in the market. Contemporarily, a huge amount of data such as usage-data from sensors or Product Embedded Information Devices as well as customer feedback from social media, forums or blogs is already available for manufacturers of PSS. These data sources provide valuable knowledge about the customer's usage of products and their expectations and complaints. The successful exploitation of PUI - Product Usage Information (such as sensor data or user feedback) becomes a key success factor for future product developments as they aid the development of PSS directly deriving from costumer requirements. But an efficient use of such knowledge requires the setup of PUI related analysis, filters and the identification of dependencies between PUI and design parameters or component attributes. Thus, transferring the usage information to design requirements is currently the major challenge in the process of developing successful PSS. Currently, there is a lack of research for a systematic transfer of PUI into product design requirements. A basic pre-condition for a knowledge transfer is a formal and neutral representation of both sides, usage data on the one hand and design parameters on the other. An approach for such a neutral representation is KbeML, which is specified as a formal extension of the established SysML standard, enabling a linkage of PUI and formalized KBE models. This paper provides a case study regarding the connection of PUI and KBE models in the branch of White Goods. The information gathered from sensors embedded in washing machines will be considered in order to retrieve improved design requirements for next generation washing machines. In a first step the product structure of a washing machine will be represented in a formal and neutral manner by using KbeML. This way the washing machine is formally described in terms of an assembly structure, and broken down into subsystems and eventually individual parts, which are defined by their relevant core parameters. In addition, the derived sensor data will be formalized as a SysML extension. The linkage between both sides (product structure data and PUI) can be achieved by mapping design parameters directly to parameters and values provided by sensors. To enable an analysis of these parameters the modelling language will provide statistical elements (e.g. median) allowing the extraction of critical values (information) from data streams. This way a comprehensive modelling environment can be provided to corresponding stakeholders, supporting an effective and efficient application of usage data for the development of new or the improvement of existing PSS.
机译:如今,产品服务系统(PSS)的相关性正在增加。为客户提供适合客户期望的产品和支持服务,成为在市场上取得成功的关键因素。同时,PSS制造商已经可以获取大量数据,例如来自传感器或产品嵌入式信息设备的使用情况数据,以及来自社交媒体,论坛或博客的客户反馈。这些数据源提供有关客户使用产品及其期望和投诉的宝贵知识。 PUI的成功开发-产品使用信息(例如传感器数据或用户反馈)成为未来产品开发的关键成功因素,因为它们可以直接从客户的需求中帮助PSS的开发。但是,有效利用这些知识需要建立PUI相关的分析,过滤器,并确定PUI与设计参数或组件属性之间的依存关系。因此,将使用信息转移到设计需求是当前成功开发PSS的主要挑战。当前,缺乏将PUI系统转移到产品设计需求中的研究。知识转移的基本前提是双方的形式化和中立表示,一方面是使用数据,另一方面是设计参数。这种中立表示的方法是KbeML,它被指定为已建立的SysML标准的形式扩展,可以实现PUI和形式化KBE模型的链接。本文提供了有关White Goods分支中PUI和KBE模型的连接的案例研究。将考虑从嵌入在洗衣机中的传感器收集的信息,以检索对下一代洗衣机的改进设计要求。第一步,将使用KbeML以正式和中立的方式表示洗衣机的产品结构。这样,洗衣机就以组装结构的形式进行了正式描述,并细分为子系统和最终的单个零件,这些零件由它们的相关核心参数定义。此外,派生的传感器数据将形式化为SysML扩展。可以通过将设计参数直接映射到传感器提供的参数和值来实现双方(产品结构数据和PUI)之间的联系。为了能够分析这些参数,建模语言将提供统计元素(例如中值),从而允许从数据流中提取临界值(信息)。这样,可以向相应的涉众提供全面的建模环境,从而支持有效而高效地使用使用数据来开发新的PSS或改进现有的PSS。

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