7 research outputs found

    Self-Aware Smart Products: Systematic Literature Review, Conceptual Design and Prototype Implementation

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    Abstract The fourth industrial revolution makes more effective use of data generated during manufacturing processes and creates a more interconnected manufacturing network. The data stored inside a product can be updated, analyzed and protected throughout its life cycle. It is currently becoming a reality to speed up the modern mass-customization. The aim of this paper is firstly to explore the state of art about smart products through a systematic literature review. Second, to design a self-aware smart product in a smart factory production environment based on the review findings. Finally, to turn the conceptual design into a prototype implementation

    Smart dust in the industrial economic sector : on application cases in product lifecycle management

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    Smart dust is an autonomous sensing, computing, and communication system that can be packed into a cubic-millimeter mote to form the basis of integrated, massively distributed sensor networks. The purpose of this manuscript is to identify potential applications of smart dust in product lifecycle management with a focus on the industrial economic sector. Resting upon empirical data from the European DACH region, we describe six applications: (1) Advancement of requirements engineering, (2) Improvement of manufacturing processes, (3) Enhancement of logistics monitoring, (4) Optimization of operations, (5) Ameliorated maintenance and repair processes, and (6) Augmented retirement planning. Bearing the exploratory, qualitative approach and early-stage character of applications in mind, we can reason that smart dust offers great potentials to both product lifecycle management and research on it

    Applying the Analytic Hierarchy Process to Oil Sands Environmental Compliance Risk Management

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    Oil companies in Alberta, Canada, invested $32 billion on new oil sands projects in 2013. Despite the size of this investment, there is a demonstrable deficiency in the uniformity and understanding of environmental legislation requirements that manifest into increased project compliance risks. This descriptive study developed 2 prioritized lists of environmental regulatory compliance risks and mitigation strategies and used multi-criteria decision theory for its theoretical framework. Information from compiled lists of environmental compliance risks and mitigation strategies was used to generate a specialized pairwise survey, which was piloted by 5 subject matter experts (SMEs). The survey was validated by a sample of 16 SMEs, after which the Analytic Hierarchy Process (AHP) was used to rank a total of 33 compliance risks and 12 mitigation strategy criteria. A key finding was that the AHP is a suitable tool for ranking of compliance risks and mitigation strategies. Several working hypotheses were also tested regarding how SMEs prioritized 1 compliance risk or mitigation strategy compared to another. The AHP showed that regulatory compliance, company reputation, environmental compliance, and economics ranked the highest and that a multi criteria mitigation strategy for environmental compliance ranked the highest. The study results will inform Alberta oil sands industry leaders about the ranking and utility of specific compliance risks and mitigations strategies, enabling them to focus on actions that will generate legislative and public trust. Oil sands leaders implementing a risk management program using the risks and mitigation strategies identified in this study will contribute to environmental conservation, economic growth, and positive social change
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