Manufacturing techniques based on networkable intelligent control systems and sensors
Manufacturing techniques based on networkable intelligent control systems and sensors
批准号:
103756
负责人:
金额:
$63.29万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --
中文摘要
在生产过程中对食品质量和安全的控制是食品生产中关键的技术和商业挑战之一,直接关系到生产力和竞争力。该项目旨在为食品行业引入创新的新制造解决方案。高一致性、高质量、高速度和大产量自动化、多节点、多模式质量传感与控制的关键是保障制造过程的效率和质量这两个方面的新技术。我们将利用新的光子传感技术来发展灵活和快速的质量控制,使制造过程更加高效。提出的新型光子制造控制技术需要数字信号处理和数据分析,这是该项目的重要组成部分。建议的方法适用于食品的制造过程,如面粉、面包和乳制品,以及处理粉状产品的工业部门,如聚合物。这是一个很有前途的商业机会,项目负责人- Branscan有限公司有能力抓住这个机会,通过提高食品质量和安全,使食品工业的生产力和竞争力发生重大变化,并对公众产生明显的影响。
英文摘要
Control of the quality and safety of the food during manufacturing processes is one of the key technical and commercial challenges in food manufacturing, directly related to productivity and competitiveness. The project aims to introduce innovative new manufacturing solutions in the food industry. Key for high consistency, high quality, high speed and large yield automation, multiple node, multi-mode quality sensing and controlling is the novel technique for safe-guarding the efficiency and quality of manufacturing processes, two facets of the process. We will use new photonic sensing technologies to develop flexible and fast quality control, making the manufacturing processes more efficient. The proposed novel photonic manufacturing control techniques require digital signal processing and data analysis, which is important part of the project. The proposed approach is applicable to manufacturing processes for foodstuffs, such as flour, bread and dairy and to industrial sectors handling powdered products, such as polymers. There is a promising business opportunity and the project leader – Branscan Ltd is well positioned to take this opportunity and enable a step change in productivity and com-petitiveness of food industry with a clear public impact due to improved food quality and safety.
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国内基金
海外基金
EstimatingLarge Demand Systems with MachineLearning Techniques
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批准号:--
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项目类别:外国学者研究基金
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资助金额:--
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批准年份:2024
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负责人:IoshuaAlex
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依托单位:
计算电磁学高稳定度辛算法研究
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批准号:60931002
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项目类别:重点项目
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资助金额:200.0万元
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批准年份:2009
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负责人:吴先良
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依托单位: