Ambient Intelligence in Product Life-cycle Management

Kovács, George L.; Kopácsi, Sándor; Haidegger, Géza; Michelini, Rinaldo C.

doi:10.1016/j.engappai.2006.01.017

Cited by 20 publications

(7 citation statements)

References 6 publications

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“…Life Cycle Management (LCM) has been developed as a business approach for managing the total life cycle of products and services (Garetti 2004;Kovacs et al 2006). It has been discussed and applied widely in the manufacturing industry (Hayes and Wheelwright 1979a,b;Labuschagne and Brent 2005).…”

Section: Lcm Of Construction Projectsmentioning

confidence: 99%

Life-Cycle Management of Construction Projects Based on Virtual Prototyping Technology

Guo

Skitmore

2010

J. Manage. Eng.

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Life Cycle Management (LCM) has been employed in the management of construction projects for many years in order to reduce whole life cost, time, risk and improve the service to owners. However, owing to lack of an effective information sharing platform, the current LCM of construction projects is not effectively used in the construction industry. Based upon the analysis of the information flow of LCM, a Virtual Prototyping (VP)-based communication and collaboration information platform is proposed. Following this, the platform is customized using DASSAULT software. The whole process of implementing the VP-based LCM of projects is analyzed via the application to a real life construction project. The advantages of implementing a VP-based LCM are also discussed and, from a simple case study, it is demonstrated that the VP-based communication and collaboration information platform is an effective tool to support the LCM of construction projects.

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Section: Lcm Of Construction Projectsmentioning

confidence: 99%

Life-Cycle Management of Construction Projects Based on Virtual Prototyping Technology

Guo

Skitmore

2010

J. Manage. Eng.

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“…For example, externalities of openness may arise from extensive knowledge diffusion in sectors in which technology has some of the characteristics of a public good, and/or sectors which are more densely networked (Kovacs et al 2006). Knowledge diffusion may also be greater where spatially bounded or concentrated networks facilitate 'buzz' , or intensive face-to-face interaction between network members (Storper and Venables 2004).…”

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confidence: 99%

Knowledge context, learning and innovation: an integrating framework

Roper

Love

2017

Industry and Innovation

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In this conceptual paper, we develop a framework which identifies those elements of firms' knowledge context which are important for innovation, and the mechanisms through which that knowledge impacts on firms' innovation performance. We make four main contributions to the existing literature. First, our characterisation of knowledge context provides the basis for a more specific identification of which elements of firms' knowledge environment are important for innovation, discriminating between spatial, sectoral and network influences. Second, we reflect the role of innovation ambition in shaping firms' knowledge search strategies. Third, we differentiate between firms' interactive and non-interactive knowledge search activities and recognise that these may be complemented by unanticipated and serendipitous knowledge spillovers. Finally, we employ the notion of encoding capacity to reflect firms' internal ability to assimilate and apply external knowledge, and clarify its distinctiveness from the more general concept of absorptive capacity. Our framework provides an integrating mechanism for existing empirical studies, and suggests a number of new research directions related to the determinants of innovation performance and the heterogeneity of innovation outcomes.

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“…Model D is different from the other models in so far as it proposes three types of activity classes, i.e. engineering, operation and support [16]. Because of the three activity classes labeled as "chains", there is a similarity of the concept with Porter's traditional value chain concept characterizing an organization's activities [17].…”

Section: Review Of Lifecycle Modelsmentioning

confidence: 99%

Considerations on a Lifecycle Model for Cyber-Physical System Platforms

Thoben

Pöppelbuß

Wellsandt

et al. 2014

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

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Part 1: Knowledge Discovery and SharingInternational audienceCyber-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

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Ambient Intelligence in Product Life-cycle Management

Cited by 20 publications

References 6 publications

Life-Cycle Management of Construction Projects Based on Virtual Prototyping Technology

Life-Cycle Management of Construction Projects Based on Virtual Prototyping Technology

Knowledge context, learning and innovation: an integrating framework

Considerations on a Lifecycle Model for Cyber-Physical System Platforms

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