A Multiscale Digital Twin-Driven Smart Manufacturing System for High Value-Added Products

由于对性能增强、轻量化和功能集成的需求不断增长，越来越多的下一代产品/组件被设计成具有3D自由形状（即非旋转对称），集成不同的形状/结构和/或由多种材料制成。例如，自由曲面透镜阵列光伏聚光器、改善道路安全的综合汽车平视显示器；用于自动驾驶汽车的激光雷达（光探测和测距）设备；微创手术工具，用于治疗与衰老有关的疾病，如白内障失明，骨关节炎，并挽救生命，仅举几例。在10e-6中，即在超精密制造领域，所需产品公差与其尺寸的比率小于1。这些产品的设计、制造组装和表征挑战是相当大的，需要对当前的制造系统进行逐步改变，以实现确保工业效率提高高达25%的雄心勃勃的目标（工业数字化中期报告，2017年），因为英国的生产率长期落后于其竞争对手。该项目将从最近完成的EPSRC项目（EP/K018345/1）开发的独特灵活可重构混合微制造系统的既定基线开始，并超越最先进的系统建模、数字、控制和自动化技术。它将研究和开发基础科学和技术，以创建新一代智能数字双驱动制造系统，该系统可以感知消费者需求，并积极自我优化定制下一代高性能3D产品，以可持续的方式提高生产力。它将通过一种新颖的产品/过程指纹方法，在理解产品设计、制造和计量之间的内在联系方面开辟新天地。将首次开发一种数字孪生驱动的自动化方法，该方法将反馈和前馈控制算法与机器级制造过程的高频数字孪生输入相结合，以架起真实系统和虚拟系统的桥梁，消除机器编码器无法测量的动态误差和热误差，即使机器在极高的工作频率下运行，也能通过预测控制满足所需的产品性能。因此，该项目将在制造自动化方面做出一步改变，该自动化基于线性控制理论，使用编码器的半闭环反馈。智能多感在线曲面测量和智能装配系统将作为智能制造系统的组成部分，用于测量复杂、高动态的曲面，实现以往难以实现的大种类零件的精密装配。还将开发一种新颖的多尺度业务建模和系统分析方法，以允许这些智能系统的集成，并采用实时数据，模型，预测产品质量，交货时间，成本，排放，浪费，并在不同的场景中优化未来的性能。SMART的有效性将通过制造包括微创手术工具、平视显示器、激光雷达和太阳能电池聚光器在内的选定演示品来证明。该联盟将通过知识交流、培训、工业示范和应用，将研究成果转化为产业和社会。在这个项目中建立的一个统一的智能制造专家库将成为英国工业的“一站式服务”，特别是中小企业，他们热衷于利用这个项目的好处。

Driven by the ever-increasing demand for performance enhancement, light weight and function integration, more and more next-generation products/components are designed to possess 3D freeform shapes (i.e. non-rotational symmetric), to integrate different shapes/structures and/or to be made of multi-materials. Examples are seen in freeform lens array photovoltaic concentrators, integrated car head-up displays for improving road safety; Lidar (light detection and range) devices for autonomous vehicle; minimal invasive surgery tools for curing aging related diseases such as cataract blindness, osteoarthritis, and saving lives, to name a few. The ratio of required product tolerance to its dimension is less than 1 part in 10e-6, i.e. in the ultra-precision manufacturing domain. The design, manufacture assembly and characterisation challenges for these products are considerable, requiring a step change in the current manufacturing system to achieve the ambitious target of securing industrial efficiency gains of up to 25% (Industrial Digitalisation Interim Report, 2017) as Britain's productivity has long lagged behind that of its competitors. The project will start from an established baseline in a unique flexible and reconfigurable hybrid micromanufacturing system developed from a recently completed EPSRC project (EP/K018345/1) and advance beyond state-of-the-art of system modelling, digital, control and automation technologies. It will research and develop the underlying science and technology for the creation of a new generation smart digital twin-driven manufacturing system that can sense consumer needs and actively self-optimise for customised next-generation high performance 3D products with enhanced productivity in a sustainable way. It will break new ground in understanding intrinsic links among product design, manufacturing and metrology with a novel product/process fingerprint approach. For the first time, a digital twin-driven automation approach which combines feedback and feed forward control algorithms with inputs from high-frequency digital twins of manufacturing process at machine level will be developed to bridge the real and virtual systems and eliminate dynamic errors and thermal errors which cannot be measured by machine encoders even the machine is running at an extremely high operational frequency to meet the required product performance through predictive control. As such, this project will make a step change in manufacturing automation which is based on linear control theory using semi-closed-looped feedback from encoders. As building blocks of the smart manufacturing system, smart multi-sense in-line surface metrology and smart assembly system will be developed to measure complex and high dynamic surface and to precision assemble large variety of parts that are difficulty to achieve before. A novel multiscale business modelling and system analysis approach will also be developed to allow integration of these smart systems and take the live data, model, predict product quality, delivery time, cost, emission, waste, and optimise the performance into the future in different scenarios. The effectiveness of the SMART will be demonstrated through manufacturing the selected demonstrators including minimal invasive surgery tools, Head-up displays, Lidar and solar cell concentrators. The consortium will transform the research outcome to industry and our society through knowledge exchange, training, industrial demonstration and deployment. A unified expertise pool in smart manufacturing established in this project will be a "one-stop-shop" for the UK industry, particularly SMEs, who are keen to exploit the benefit of the project.