2017
DOI: 10.1007/978-3-319-67633-3_7
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Towards Developing Dependable Systems Suitable for Crisis Management Applications

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Cited by 3 publications
(1 citation statement)
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“…These methods have been proved to be adequate in static production lines however, the necessity of I4.0 to maintain flexible productivity that emerges the continuous shop-floor transformations, does not allow traditional safety analysis to perform well since they are typically demand a large amount of performance data for an adequate operation. The necessity of on-the-fly predictive maintenance emerges the adoption of more flexible and holistic methods for hazard analysis defined from the design phase of complex systems in shop-floor environments such as STPA [37], RiskSOAP [23], Decision Making Grids and Jack Knife Diagrams [38] tools that endorse synchronous automated systems with the necessitated dependability [39], [40]; that will eventually allow predictive maintenance. Such methods integrated with artificial intelligence, big data and visual analytics constitute powerful tools that strengthen the prediction of hazard situations in production lines, preventing excessive down time, decreasing thus the excessive maintenance costs.…”
Section: Lean Productionmentioning
confidence: 99%
“…These methods have been proved to be adequate in static production lines however, the necessity of I4.0 to maintain flexible productivity that emerges the continuous shop-floor transformations, does not allow traditional safety analysis to perform well since they are typically demand a large amount of performance data for an adequate operation. The necessity of on-the-fly predictive maintenance emerges the adoption of more flexible and holistic methods for hazard analysis defined from the design phase of complex systems in shop-floor environments such as STPA [37], RiskSOAP [23], Decision Making Grids and Jack Knife Diagrams [38] tools that endorse synchronous automated systems with the necessitated dependability [39], [40]; that will eventually allow predictive maintenance. Such methods integrated with artificial intelligence, big data and visual analytics constitute powerful tools that strengthen the prediction of hazard situations in production lines, preventing excessive down time, decreasing thus the excessive maintenance costs.…”
Section: Lean Productionmentioning
confidence: 99%