MACHINUM
Open shop approach Machinum from Siemens is an open, modular digitalisation portfolio based on Siemens Xcelerator for the machine tool industry that can benefit small and medium-sized companies and large enterprises. “In the development of Machinum we look at all elements of the machine shop: the machines, the virtual machine and the shop-floor processes,” explains Mr Meltzer. “Also, we focus on making the solution control-agnostic. As a result, I’m not aware of another portfolio with such a breadth of capabilities.” Adds Mr Coombes: “The portfolio dovetails with sustainability initiatives, an example being using virtual machines to simulate and verify NC programs rather than consuming energy and material by running actual machine tools. In fact, the fourth performance goal of Machinum will be sustainability, arriving in 2025.” Fighting fit “A digitalisation transformation project is like going to the gym,” concludes Marketing Communications Manager Bozena Immonen. “You don’t run a marathon on the first day; you build steadily towards goals like more speed, agility or endurance. And although every machine shop is different, the ambitions are the same: you want to be better than before. You’ll need certain things, namely a personal trainer [Siemens], a workout plan [use case clusters] and equipment [Machinum apps]. The time to start is now because what will happen if you don’t? You’ll continue suffering flabby production processes, dispiriting setbacks and poor recovery times.” Siemens offers a shop-floor check-up tool to see where machine shops can make savings. This informative tool also compares resource management – including tools, NC programs and machine data – against industry standards. Now is the time to get fit. n siemens.com/machinum
also reduce cycle times, as adaptive feed control is able to minimise machining times and detect tool breakage at an early stage. Machine tool manufacturer Grob was able to reduce its cycle times by 18% using this solution. The ability of agility If companies want to produce small batch sizes and complex geometries quickly and cost- effectively, they need to make their processes more flexible. Before starting the job, the user can employ the machine’s digital twin to check whether efficient component manufacture is possible using that specific machine. He or she can also calculate the run time. In addition, users can develop virtual prototypes in the model to map new requirements. It is then possible to allocate corresponding production resources via digital resource management. Efficient and targeted re-tooling on the machine allows companies to take production plan changes into account and implement them more quickly, as confirmed by Andreas Pfeiffer. The company is using digital resource management to achieve set-up time savings of around 50%. Machine endurance Digital solutions also help companies to extend the service life of their machines and tools. Special apps use machine data to enable predictive maintenance and prevent unplanned downtime. Digital solutions can detect tool wear and excess stress to avoid tool breakage. Alongside information from the digital twin, data from cameras and sensors helps to detect collision risks, signs of wear and errors in advance. Tool manufacturer Emuge-Franken is able to carry out around 95% of measurements without investing in an expensive tool external measuring system thanks to in-process monitoring of high- frequency data.
Machinery & Manufacturing 18
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