Optimising food production in commercial kitchens through machine learning, reducing waste and increasing profits
Optimising food production in commercial kitchens through machine learning, reducing waste and increasing profits
批准号:
10032491
负责人:
金额:
$32.9万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2022
资助国家:
英国
项目状态:
已结题
起止时间:
2022 至 --
中文摘要
全球酒店业,特别是自助餐式环境,仍然缺乏一种工具来准确地帮助预测生产多少食物以及何时生产。这导致了相互关联的经济和环境挑战。粮食生产过剩导致巨大的财政和经济成本。仅在英国酒店和食品服务部门,2011年的食物浪费成本估计超过25亿英镑,其中75%是可以避免的。环境影响是巨大的;如果全球食物浪费是一个国家,它将是仅次于美国和中国的第三大温室气体排放国。生产过剩也会降低食品质量,损害客户满意度。为厨师提供一种工具,可以根据天气模式、历史废弃物、一天中的时间和客户人口统计等广泛因素,为他们提供可操作的生产预测,这将有助于他们优化生产,并允许改善成本控制,劳动力/人员配备,并增加对客户偏好的了解。该项目旨在利用Winnow在构建机器学习模型和向约1500个厨房的厨师提供可操作数据方面的经验,将我们目前的原型生产计划工具转变为测试版市场就绪工具。该项目和相关创新非常及时,特别是考虑到酒店业受到Covid-19的影响。该行业非常需要这种生产计划工具,以便更好地控制运营、利润和环境足迹。商业厨房在很大程度上被排除在数字革命之外,并将从帮助他们更好地管理运营的集成工具中受益匪浅。
英文摘要
The global hospitality industry, particularly buffet style environments, still lacks a tool to accurately help predict how much food to produce, and when. This results in interconnected economic and environmental challenges. Overproduction of food leads to vast financial and economic costs. In the UK Hospitality and Food Service Sector alone, food waste cost was estimated at over £2.5bn in 2011, with 75% of it recorded as avoidable. The environmental impact is monumental; if global food waste were a country, it would be the third largest emitter of greenhouse gases after the USA & China. Overproduction also lowers food quality, harming client satisfaction. Underproduction causes its own issues; hurting customer satisfaction and margins.Providing chefs with a tool which can give them actionable production predictions based on a wide range of factors including weather patterns, historic waste, time of day and demographic of customers would help them optimise their production, and allow for improved control of costs, labour / staffing, and increased understanding of customer preference. This project aims to build on Winnow's experience of building machine learning models and presenting actionable data to chefs in around 1500 kitchens to turn our current prototype production planning tool into a beta market ready tool.This project and associated innovation are extremely well-timed, especially regarding the impact felt by the hospitality industry from Covid-19\. The industry is in great need of this production planning tool to give it more control over operations, margins and environmental footprint. Commercial kitchens have been largely left out of the digital revolution, and stand to benefit greatly from integrated tools that help them to manage their operations better.
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