Responsive Manufacturing: Maximising Value Through Life

响应式制造：一生价值最大化

• 批准号: EP/V05127X/1
• 负责人: Linda Newnes
• 金额: $ 66.7万
• 依托单位: University of Bath
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FV05127X%2F1
• 关键词: Responsive; Manufacturing; Maximising; Value; Through

Imagine you are responsible for the operation of a manufacturing system that is producing the next generation of electric cars. The manufacturing system is streamlined and producing leading-edge innovative cars just in time to meet the consumer needs, has minimum waste, the supply chain providing materials and products to the manufacturing line is green and quality of production is high. Everyone is happy. However, suddenly the supply of a core material used in the manufacture of the car is now quite scarce i.e. there is limited availability. Unfortunately, our manufacturing system is no longer working as it should! The manufacturing system is not producing enough cars and the productivity has hit rock bottom. Sadly, there were indications that the material was becoming scarce - the supplier had been issuing warnings, but the warnings were missed and no-one realised the impact this would have. So, we now have a manufacturing system that is not efficient, the cars can no longer be manufactured at an appropriate rate, and the manufacturer is about to be bankrupt! This could have all been avoided if we had a manufacturing system that was responsive i.e. adapt to change, be sustainable and resilient. The outputs from this research are geared to avoid such occurrences by providing the information to enable the manufacturing system to adapt to both internal and external factors i.e. enable the manufacturing system to be responsive.Our research will use Data, Information and Knowledge, automatically accessed via digital methods to enable the brain (the control centre) of the manufacturing system to continually assess its current status and predict future states. We will facilitate the ability of a manufacturing system to be truly responsive, whilst sustaining its whole life value. Although easy to say - achieving this is extremely challenging. However, with the current impacts of major disruptions such as COVID-19 on manufacturing there is a strong desire and willingness from manufacturers to ensure their systems can be responsive. Hence, the call and our proposed solution is very timely. In parallel to this need, the advancements in the technology and processes, such as digitalisation, 5G and Industry 4.0 have reached the stage that we can create a means by which a manufacturing system can automatically assess whether it needs to change and predict the most appropriate action.Our proposed solution has its foundations in value modelling (a value model is used to assess the impact of any proposed solution in terms of e.g. cost, quality, delivery, environment) to evaluate and assess the impact of any proposed response to changes within/external to the manufacturing system. We will achieve this via the investigation and analysis of a number of real-life manufacturing case studies to identify the level of autonomy that is appropriate in relation to the characteristics of the manufacturing system. We will identify the core Data Information and Knowledge required to create the value model, use data analytic techniques such as clustering/network modelling to automatically analyse the manufacturing system and create a pragmatic and useable step-by-step process to ensure impact from the outputs of the research.In summary, our Vision is to create an automated real-time manufacturing system support toolkit to achieve whole life value from current and future Manufacturing Systems, maximising value through their lifetime i.e. being responsive, sustainable, adaptable and resilient.

想象一下，您负责生产下一代电动汽车的制造系统的运行。制造系统是精简的，并在满足消费者需求的情况下及时生产前沿创新汽车，最小的废物，为制造业线提供材料和产品的供应链是绿色的，生产质量很高。每个人都很高兴。但是，突然之间，汽车制造中使用的核心材料的供应现在很少，即供应有限。不幸的是，我们的制造系统不再按照应有的方式工作！制造系统没有生产足够的汽车，生产力已经达到了岩石底部。可悲的是，有迹象表明材料变得稀缺 - 供应商一直在发出警告，但没有错过警告，没有人意识到这将产生的影响。因此，我们现在拥有一个不高效的制造系统，汽车不再以适当的速度制造，制造商即将破产！如果我们拥有响应迅速的制造系统，即适应变化，可持续和弹性，则可以避免所有这些。这项研究的输出旨在通过提供信息来避免发生这种情况，以使制造系统能够适应内部和外部因素，即使制造系统能够响应措施。您的研究将使用数据，信息和知识，通过数字方法自动访问，从而使制造系统的大脑（控制中心）能够持续评估其当前状态和未来状态。我们将促进制造系统真正响应迅速的能力，同时维持其整个生命价值。虽然很容易说 - 实现这一目标极具挑战性。但是，随着当前重大干扰（例如Covid-19）对制造公司的影响，制造商的愿望和意愿强烈，以确保其系统能够响应迅速。因此，呼叫和我们提议的解决方案非常及时。按照这种需求，技术和过程的进步（例如数字化，5G和行业4.0）达到了我们可以创建一种手段的阶段，通过该阶段，制造系统可以自动可以自动更改和预测最适当的行动。所提出的解决方案是否在价值模型中评估其基础，以评估任何提议的响应（评估E.G的质量，质量，质量，质量），以评估任何响应，以评估任何响应，并评估其质量，质量，质量，质量，质量，质量，质量，质量，质量，质量，并评估其质量，质量，并评估其质量，并评估其质量，并评估其质量的影响。制造系统内部/外部的变化。我们将通过对许多现实生活中的制造案例研究进行调查和分析来实现这一目标，以确定与制造系统特征相关的自主权水平。我们将确定创建价值模型所需的核心数据信息和知识，使用数据分析技术（例如聚类/网络建模）自动分析制造系统，并创建一个务实且可逐步的逐步逐步过程来确保研究的产出对总结的影响。在总结上，我们的愿景将创建一个自动化的实时制造系统，以实现自动化的实时制造系统，以实现当前和未来的生命值I.响应迅速，可持续，适应性和弹性。