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Digital Twins (DTs) are a core enabler of Industry 4.0 in manufacturing. Cognitive Digital Twins (CDTs), as an evolution, utilize services and tools towards enabling human-like cognitive capabilities in DTs. This paper proposes a conceptual framework for implementing CDTs to support resilience in production, i.e., to enable manufacturing systems to...
Manufacturing companies are forced to become energy-aware under the pressure of energy costs, legislation and consumers’ environmental awareness. Production scheduling remains a critical decision making process, although demanding in computational terms and sensitive on data availability and credibility. Hence the interest in incorporating energy-r...
Environmental concerns, stricter legislation and inflated energy costs, together yield energy efficiency as an important pillar for virtually every industrial sector. Mindful of this challenge, ISs can act as enablers of energy-based management and intelligent decision support. Based on empirical evidence through two case studies combined with the...
Although the manufacturing sector has made continuous improvements towards sustainability performance measurement, it is not yet fully exploited. In view of its premature level, the issue of understanding how to integrate sustainability performance measurement has become a matter of considerable concern for both practitioners and academics. Within...
In this paper we investigate the problem of efficiently evaluating XPath queries over large XML data stored in a distributed manner. We propose a MapReduce algorithm based on a query decomposition which computes all expected answers in one MapReduce step. The algorithm can be applied over large XML data which is given either as a single distributed...