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，你负责生产下一代电动汽车的制造系统的运作。制造系统是流线型的，及时生产出领先的创新汽车，以满足消费者的需求，浪费最少，为生产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。然而，突然之间，用于制造汽车的核心材料的供应现在非常稀缺，即可用性有限。不幸的是，我们的制造系统不再像它应该的那样工作了！制造系统生产不出足够的汽车，生产率已经降到了最低点。可悲的是，有迹象表明，这种材料正在变得稀缺-供应商一直在发出警告，但警告被错过了，没有人意识到这将产生的影响。所以，我们现在有一个没有效率的制造系统，汽车不再能以适当的速度制造，制造商即将破产！如果我们有一个快速响应的制造系统，即适应变化，可持续和弹性，这一切都可以避免。本研究的结果旨在通过提供信息，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，从而避免此类事件的发生。我们的研究将使用数据，信息和知识，通过数字方式自动访问，制造系统（控制中心）不断评估其当前状态并预测未来状态。我们将促进制造系统的能力，使其真正响应，同时维持其整个生命价值。虽然说起来容易，但实现这一目标是非常具有挑战性的。然而，鉴于目前COVID-19等重大中断对制造业的影响，制造商强烈希望并愿意确保其系统能够响应。因此，我们的呼吁和提出的解决方案是非常及时的。与此同时，技术和流程的进步，如数字化，5G和工业4.0已经发展到这样一个阶段，我们可以创建一种方法，使制造系统可以自动评估是否需要改变并预测最合适的行动。我们提出的解决方案以价值建模为基础。（价值模型用于评估任何提议的解决方案在成本、质量、交付、环境等方面的影响），以评价和评估任何提议的对制造系统内部/外部变化的响应的影响。我们将通过调查和分析一些现实生活中的制造业案例研究，以确定与制造系统的特征相关的适当的自治水平来实现这一目标。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（如聚类/网络建模）自动分析制造系统，并创建实用且可用的分步流程，以确保研究结果的影响。我们的愿景是创建一个自动化的实时制造系统支持工具包，以实现当前和未来制造系统的全生命周期价值，在其生命周期中实现价值最大化，即响应性、可持续性、适应性和弹性。