Productive Machines enables machining companies to reach to the best part, faster and first time.
By applying scientific methods such as simulations in machining processes, time it takes to produce parts can be reduced considerably, i.e. by 50% as published in an AMRC case study (https://bit.ly/3fxAbDQ ). However, many manufacturers don’t have access to such simulation techniques and use an experimental trial and error approach instead. This cannot guarantee utilization of the full potential of the machine tools, results in in waste, inefficient use of resources and low OEE (Overall Equipment Effectiveness). Moreover, invaluable process data is wasted in the machining industry every second because most businesses don’t have the capability to turn this data into value.
Our product is a digital twin based learning platform. It is composed of three modules, namely, learning system, process planning and process monitoring and control tool. The learning system includes key information such as tool, work piece and process knowledge. The process planning tool is integrated into existing CAM software, i.e. Siemens NX. It hosts an offline digital twin of the machining process. Process planners can use it to identify potential problems in advance and can take counter measures to avoid them while optimizing the process. The process monitoring and control tool includes an online digital twin. It monitors anomalies such as tool wear and chatter and adapts key parameters to control them to optimize productivity and avoid waste. All 3 modules are linked to each other. One unique capability of the software is that machine tools will be able to learn from each other to optimize machining processes.
Productive Machines is a spin out company from AMRC (Advanced Manufacturing Research Centre at the University of Sheffield). Boeing HorizonX is the first investor of Productive Machines.
