Fadi Shrouf

TL;DR: This paper presents a reference architecture for IoT-based smart factories, defines the main characteristics of such factories with a focus on the sustainability perspectives, and proposes an approach for energy management in smart factories based on the IoT paradigm.

TL;DR: Considering variable energy prices during one day, a mathematical model to minimize energy consumption costs for single machine production scheduling during production processes was proposed in this paper, where genetic algorithm technology has been utilized.

TL;DR: In this paper, the authors present a framework to support the integration of gathered energy data into a company's information technology tools and platforms with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage on such data in order to improve energy efficiency, and therefore competitiveness, of manufacturing companies.

TL;DR: In this article, a pilot study was carried out to integrate electrical energy data, production data and scheduling data in real time to achieve the multi-level awareness of energy used in production.

TL;DR: In this article, the authors proposed a methodology for determining the load-shifting potential of small and medium-sized manufacturing companies based on technical, organizational, and economic criteria, which was tested and refined in a large-scale manufacturing company specializing in metal processing in Germany.