ISAMOD – In-Situ Machine Axis Error Monitoring
Project Summary
Laser interferometry is commonly used to measure machine axis accuracy but has one major flaw in that it cannot be used to monitor axis dynamic performance while the machine is cutting. The result of this is that machine accuracy measurements can only be guaranteed when the machine isn’t doing the work it is designed to do. We propose a relatively low cost in-situ laser monitoring system that will measure axis position, velocity, acceleration and angle at all times even when the machine is cutting. With this system the axis dynamic performance can be monitored even during the cutting process allowing a more accurate assessment of the machine accuracy and it will be possible to measure the machine dynamic performance over time allowing degradation of performance to also be measured.
The key objectives of this project are to develop a prototype system, both hardware and software and fit it to a production machine to allow a full evaluation of the technology with a view to producing a production version that can be offered as a dynamic machine monitoring system. This system is not available anywhere else as far as we know – laser scales are available for high accuracy machines but they are expensive and designed to be incorporated into a machine control loop for position feedback. This innovative proposal allows much more dynamic data to be captured, processed and monitored which can form the basis of an advanced condition monitoring system.
Project Scope
The project scope targets significant improvements in productivity through direct time savings associated with machine performance enhancement and predictive maintenance strategies from rich performance data, further exploited using industrial data analytics to improve accuracy of maintenance and end-of-life predictions. It will also provide an enabling technology for the machine servitisation models, the outcomes of which are significant for production companies where the elimination of very high capital investment will facilitate the development of new processes, greater agility to satisfy customer demands and the manufacturing readiness of growing sectors such as civil nuclear and aerospace. The servitisation of machine tools is new and part of ongoing research but this novel business model requires technology that enables the service provider to monitor the machine in much greater detail, including performance metrics, but equally its condition and how they are being used. Because the project involves innovation that is specifically targeting key measurands, identified over decades of machine service experience at MTT and the University research group, the impact on the aforementioned methods of achieving growth will be more profound than typical or generic IoT sensors or NC information.
This project will enable MTT to diversify its key existing services (MPEOM), because it provides a strategy for monitoring customer machines as part of a service or maintenance contract as well as a method for resolving accuracy problems (or optimising performance) that may be identified during the detailed analysis of the customer machine. A common approach to reduce machine error is to periodically calibrate an axis using standard pseudo static measurements, typical with a Laser interferometry, in accordance with ISO230 series of standards, and using the data to update error compensation data in the NC system. However, it is well known that on machine tools, the variability due to temperature, Workpiece mass, wear, change in preload, that data is out-of-date almost by the time the calibration is finished. The in-situ error monitoring system presents a novel service opportunity where such data can be updated whenever necessary or provide degradation information for a more informed calibration strategy. New service options open new sources of revenue, and in the longer term MTT intend to remote monitor (part of the aforementioned Servitisation model) machines enabling management of the customer asset at an appropriate regular payment.
