EPSRC Fellowship in Manufacturing: Collaborative Metrology Systems for High Value Manufacturing

为了支持具有挑战性的、难以制造的产品的开发，越来越多地依赖于能够对零部件进行精确尺寸测量的技术。需要新的测量系统，以比目前可能的更高水平的准确度和精确度快速提供数据。目前，高精度测量是在温度控制实验室中使用专用的昂贵仪器进行的。广泛的测量挑战意味着没有单一的仪器可以满足所有需求。事实上，满足工业测量需求所需的实验室仪器系统的范围不断增长。它包括从使用机械探针进行的接触式测量到使用基于光、激光或X射线的测量方法的非接触式测量的技术。这些系统的主要缺点是它们通常设置缓慢，并且需要大量时间进行测量。这意味着，尽管它们非常准确，但它们对于控制和改进具有挑战性的制造过程的用处不大，因为必须快速收集和分析数据。需要改进的测量系统，其以较低的成本提供较高速度的测量，而不损害精度。目前有两种方法可以满足这一需求。一种方法是使用机器上的传感器来提供高速测量，而另一种方法是将仪器放置在更靠近制造环境的位置，以减少将工作转移到测量实验室所需的时间。这两种方法都有明显的优点，因为它们提供更快的数据;然而，由于在工厂车间经历了不必要的干扰，它们也不太准确。这些限制导致了一个折衷：用户可以获得高精度或高速测量，但不能同时获得两者。在该奖学金内进行的研究将开发一种收集和有效处理关键测量数据的新方法。这种方法将为测量系统的设计和实施提供一种新的思路，而不是依赖于高精度仪器。目标是允许以有益的方式组合不同类型的较低精度数据。例如，机器、产品和过程的计算机模拟将与监测环境条件的传感器相结合。此外，将使用用于在制造过程中对零件进行高速测量的传感器。通过一个协作过程，这些数据将被合并，以提供快速的高质量数据。为了验证和进一步改进该系统，将使用来自温控实验室的高精度仪器的少量准确反馈数据。实际上，该方法将是将缓慢准确的数据与快速不太可靠的数据相结合，以产生增强的准确性快速测量。例如，如果必须生产一批高精度部件，则部件还必须在需要时对其几何形状进行验证和校正。机器上的传感器可用于验证几何形状，但由于温度和湿度等环境影响，精度有限。为了补偿这些误差，协作测量系统最初将使用机器上的传感器以及机器外的实验室仪器进行测量。它将把这些数据集与来自机器上环境监测传感器的数据和计算机模拟相结合，以纠正错误，从而提高测量的准确性。该系统将通过触发对更多基于实验室的数据的需求来自动适应不断变化的环境条件，这将允许进行改进的纠错。通过这种方式，系统将调整和优化测量过程，以适应当前的制造条件。

To support the development of challenging, difficult to manufacture products, increased reliance is placed on techniques to allow accurate dimensional measurement of parts and components. New measurement systems are needed that provide data quickly with higher levels of accuracy and precision than is currently possible. Currently high accuracy measurements are made using dedicated expensive instrumentation in temperature controlled labs. The wide range of measurement challenges mean there is no single instrument available to suit all needs. In fact, the range of lab based instrument systems required to meet the measurement needs of industry continues to grow. It includes techniques ranging from contact measurements made using a mechanical probe, to non-contact measurements which use light, lasers, or X-ray based measurement methods. The main drawback of these systems is that they are usually slow to set-up, and significant time is required to take measurements. This means that although they are very accurate they are less useful for the control and improvement of challenging manufacturing processes, where data must be collected and analysed quickly. Improved measurement systems are required which provide higher speed measurements, at lower cost, without compromising accuracy. Currently two approaches address this need. One approach uses on machine sensors to provide high-speed measurements, while the other approach is to position instruments closer to the manufacturing environment to reduce the time required to transfer work to the measurement lab. Both approaches have obvious benefits as they provide faster data; however, they are also less accurate as a result of the unwanted disturbances experienced on the factory floor. These limitations result in a trade-off: the user can either have high accuracy, or high speed measurement, but not both at once. The research undertaken within this Fellowship will develop a new way of collecting and effectively processing critical measurement data. Instead of a reliance on high accuracy instruments, this approach will provide a new way of thinking with respect to how measurement systems are designed and implemented. The goal will be to allow different types of lower accuracy data to be combined in a beneficial way. For example, computer simulations of a machine, product, and process will be combined with sensors that monitor environmental conditions. In addition sensors used to take high speed measurements of parts during the manufacturing process itself will be used. Through a collaborative process these data will be combined to provide fast high quality data. To verify and further improve the system a small quantity of accurate feedback data from high accuracy instruments in temperature controlled labs will be used. In effect the approach will be to combine slow accurate data, with fast less reliable data, to produce enhanced accuracy fast measurements. For example, if a batch of high precision components must be produced, the components must also have their geometry verified and corrected if required. On machine sensors may be used to verify geometry, but accuracy is limited due to environmental effects such as temperature and humidity. To compensate for these errors a collaborative measurement system will initially make measurements using both on-machine sensors as well as off-machine lab instruments. It will blend these data sets in addition to data from on-machine environmental monitoring sensors, and computer simulations to correct for errors and therefor enhance the accuracy of the measurements. The system will automatically adapt to changing environmental conditions by triggering the need for more lab-based data which will allow an improved error correction to be made. In this way the system will adapt and optimise the measurement process to suit the current manufacturing conditions.