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  • 标题:EIT Food - EU PRO4BAKE project: Improve artigianal bakeries performances considering both demand forecast and process optimisation: the EIT FOOD Pro4Bake approac
  • 本地全文:下载
  • 作者:Remigio Berruto ; Remigio Berruto ; Sara Beduschi
  • 期刊名称:Proceedings in Food System Dynamics
  • 印刷版ISSN:2194-511X
  • 出版年度:2021
  • 卷号:2021
  • 页码:126-132
  • DOI:10.18461/pfsd.2021.2115
  • 语种:English
  • 出版社:Proceedings in Food System Dynamics
  • 摘要:The bakery products subsector has the largest number of companies, value added, employees and number of companies in Europe (Food and Drinks, 2011). Over-consumption of energy in bakeries due to inefficient scheduling and production planning together with high shares of unsold bread waste (5-10% in Europe) is a big issue. Not only avoidable CO2 emissions affecting climate change and society, but also excessive costs for SME bakeries are severe consequences. Recently, the EU has identified the bakery sector as one of the target sectors to apply best environmental practices. The aim of the envisaged project is in line with the goals of the EU (Regulation (EC) No 1221/2009, 2017/1508 of 28 August 2017 EU): minimising food waste and reducing energy consumption. The Pro4Bake project aims to provide tools that could improve the bakery situation. A prospective production-planning tool for bakeries is being developed in this trans- and interdisciplinary project. Present machinery in bakeries is used to optimise the production process. The reduction of make span and idle time of machines, but also combinations thereof will lead to a higher economic and ecologic efficiency, thus, lower production costs for bakeries and lower climate change impact for society. The tool is developed using a flow-shop model, optimised by evolutionary algorithms, digital twins and artificial intelligence procedures. Adaptation to consumers’ preferences will minimise food waste; hence, ecological footprint in bakeries, and lead to further optimisation of the baking process, product range and amount. Consumers’ demands and expectations related to e.g. weather or holidays, and their acceptance of changes in product availability will play a significant role in the analysis. In the end, a computational application will help SME bakeries as users to adapt their production planning and processes to best practice. Subsequently, its potential in practical application will be examined and its impact broadened to the rest of Europe and beyond. Dissemination through technology transfer to users by involving professionals, students and learning videos will be performed. The product will be commercialised in the end to make it possible for bakeries to adapt to the truly needed amount and product range with optimised baking schedules to reduce energy consumption. The multidisciplinary approach, combining research optimisation methods and demand forecast approach used could be easily transferred to other agri-food sectors.
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