M
Marco Bortolini
Researcher at University of Bologna
Publications - 127
Citations - 2692
Marco Bortolini is an academic researcher from University of Bologna. The author has contributed to research in topics: Supply chain & Computer science. The author has an hindex of 23, co-authored 118 publications receiving 1927 citations. Previous affiliations of Marco Bortolini include University of Padua & University of Trento.
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Reconfigurable manufacturing systems: Literature review and research trend
TL;DR: This paper presents a structured and updated systematic review of the literature about RMSs, highlighting the application areas as well as the key methodologies and tools and links reconfigurable manufacturing to the upcoming Industry 4.0 environment.
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Technical and economic design of photovoltaic and battery energy storage system
TL;DR: In this paper, the authors presented a technical and economic model for the design of a grid connected PV plant with battery energy storage (BES) system, in which the electricity demand is satisfied through the PV-BES system and the national grid, as the backup source.
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Assembly system design in the Industry 4.0 era: a general framework
TL;DR: In this article, the impact of Industry 4.0 principles on assembly system design has been investigated, where the authors propose an original framework which investigates the impact on assembly line balancing and scheduling, several other dimensions of this problem have to be considered.
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Fresh food sustainable distribution: cost, delivery time and carbon footprint three-objective optimization
TL;DR: In this article, a three-objective distribution planner is presented to tackle the tactical optimization of fresh food distribution networks considering operating cost, carbon footprint and delivery time goals, and the most effective distribution network is studied best balancing the economic, environmental and delivery times objective functions.
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Artificial neural network optimisation for monthly average daily global solar radiation prediction
TL;DR: In this article, the authors used ANNs to predict the monthly average daily Global Solar Radiation (MADGSR) over Italy using data from 45 locations composed the multi-location ANN training and testing sets.