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Wasting less food: smart mass customisation of food provision

机译：浪费减少食物：智能大规模定制食品拨备

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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 - 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.
机译：由于所有食物中的三分之一浪费了，全球粮食供应的高度报道的环境足迹为粮食提供和消费的变化提供了紧急驾驶员。在发达国家中，废物产生的主要观点是消费水平（通常超过一半的浪费），但它太容易将问题归因于消费者行为 - 这是整个供应链的系统问题。本研究通过开发产品服务系统（PSS）来解决供应和需求平衡，降低消费者水平的问题，使消费者能够更好地计划和购买消费物品。作为PSS的一部分，库存管理系统允许基于可用食物的智能和高度方便的采购（例如，前一周的剩余库存）以及消费者偏好和要求。这种敏捷规划基于人工智能驱动系统。在这方面，智能平台被概念化，以通过机器学习将来自现有数据库的配方与可用的成分自动匹配，目的是在下周的购物订单建议方面提供解决方案。这种粮食供应的大规模定制进一步使生产者和提供商能够通过促进或限制供应量或有限的食物来管理需求。因此，平台允许在消费水平降低食物垃圾，并进一步向供应链。本文展示了对食品供应链内供需匹配更好的需求，描述了食品提供的PSS的基础，包括优化配方选择。开发了一个案例研究，以举例说明所提出的平台如何在现代商业系统中实现。

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