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Wasting less food: smart mass customisation of food provision

With as much as one third of all food wasted, the highly reported environmental footprint of global food supply provides an urgent driver for changes to be made to food provision and consumption. In developed countries the main point of waste generation is at the consumption level (typically over half of the waste by mass), but it is too easy to attribute the problem to consumer behavior \x96 it is a systematic problem of the entire supply chain. This current research addresses the issues of supply and demand balancing, down to the consumer level, through the development of a product service system (PSS) that enables consumers to better plan and purchase items for consumption. As part of the PSS, an inventory management system allows intelligent and highly convenient purchasing based on available food (e.g. leftover inventory from the previous week) and on consumer preferences and requirements. This agile planning is based on an artificial intelligence driven system. In this respect, a smart platform is conceptualized to automatically match recipes from an existing database with available ingredients via machine learning, with the aim of providing solutions in terms of shopping order recommendations for the following week. This mass customization of food supply further enables producers and providers to manage demand by promoting or restricting foodstuffs that are in excess or limited supply, respectively. The platform thus allows reduction of food waste at the consumer level and further up the supply chain. This paper demonstrates the need for better matching of supply and demand within the food supply chain, describes the basis for a PSS for food provision including optimization of recipe selection. A case study is developed to exemplify how the proposed platform could be implemented within modern commerce systems.

ریخته‌گری کم‌تر مواد غذایی: سفارشی سازی انبوه هوشمند مواد غذایی

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