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Sharareh Taghipour
Researcher at Ryerson University
Publications - 95
Citations - 1669
Sharareh Taghipour is an academic researcher from Ryerson University. The author has contributed to research in topics: Computer science & Scheduling (production processes). The author has an hindex of 19, co-authored 70 publications receiving 1092 citations. Previous affiliations of Sharareh Taghipour include University of Toronto.
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Periodic inspection optimization model for a complex repairable system
TL;DR: This paper proposes a model to find the optimal periodic inspection interval on a finite time horizon for a complex repairable system where soft failures are detected and fixed only at planned inspections, but not at moments of hard failures.
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Prioritization of medical equipment for maintenance decisions
TL;DR: A multi-criteria decision-making model to prioritize medical devices according to their criticality is presented and how individual score values obtained for each criterion can be used to establish guidelines for appropriate maintenance strategies for different classes of devices is described.
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Periodic Inspection Optimization Models for a Repairable System Subject to Hidden Failures
TL;DR: A model to find an optimal periodic inspection interval over finite and infinite time horizons for a multi-component repairable system subject to hidden failures is proposed.
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Real-time production scheduling in the Industry-4.0 context: Addressing uncertainties in job arrivals and machine breakdowns
TL;DR: This paper investigates how real-time updates on unexpected arrivals, the availability of machines, and the completion times of operations can be utilized to generate new schedules (i.e., rescheduling) in complex manufacturing systems, such as flexible job shops.
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Integrated production and maintenance scheduling for a single degrading machine with deterioration-based failures
TL;DR: A stochastic mixed-integer programming model is developed which jointly optimizes production scheduling and maintenance planning in a single-machine production environment and shows that making decisions according to the deterioration level of the machine results in more integrated and cost-effective plans compared to the current method of repairing the machine only once it has reached its failure state.