Abstract

Nowadays achieving overall sustainability in industrial activities is the natural consequence of diminishing non-renewable resources and stricter regulations related to environment and occupational safety/health.In industrial sector, CO2 emissions derive both from direct and indirect emissions. The second type is due to the use of electricity and currently represents more than thirty percent of global amount. For this reason energy consumption reduction is critical aspect in several industrial environments. Power consumption reduction is possible by modifying manufacturing conditions, utilizing alternative technologies and increasing resource utilization rate.The current market demand is characterized by request of small lots with different characteristics, which requires a complex management of the manufacturing production flow.Production planning and scheduling models, arising in flexible manufacturing environments, allows to combine several aspects such as: technological questions (e.g.: minimize manufacturing times and costs) economic criteria (e.g.: maximize production rate) and environmental prospective (e.g.: emissions reduction). A good manufacturing scheduling allows to saturate the system, avoiding bottlenecks, by means of the adaptation of the plant productivity to the request one.In this paper, authors describe an optimization framework focused on the minimization of energy and production costs by means of an intelligent production scheduling. In order to assess the performances, different real case production scenarios, in which the manufacturing activity is mainly based on machining operations, have been analyzed. In this work, several technologies, with various capabilities, have been taken into account in order to perform production activities. In addition, the scheduling has the possibility of using production technologies with low environmental impact and lower productivity, where the increase of the activity duration does not deteriorate the system performance. In this way several production schedules are feasible and the main scheduling aim focuses in obtaining the required productivity to fulfill demand and minimize energy consumption.

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