Steed Webzell scrutinises the technologies currently available to assist those wanting to digitise their machining processes

Heller has adopted the name Heller4Industry for the suite of Industry 4.0 modules it offersMajor machine tool OEMs are upping their game when it comes to digitalisation. “Industry 4.0 (I4.0) is not just a gimmick, as some would have you believe, but a cornerstone of advanced manufacturing,” states Matthias Meyer, managing director in charge of Heller’s subsidiary in Redditch, UK. “It allows the last few percent of productivity to be extracted from an already efficient process, and results in considerably more benefits in the case of less well optimised manufacturing environments.”

Some 75% of Heller Group’s business comes from the automotive industry, and the company has adopted the name Heller4Industry for the suite of related modules it offers. Within the portfolio, Heller4Performance, includes workpiece-specific analysis for the optimisation of a process and extraction of real-time data over the internet, plus evaluation and graphical display in the Cloud. In practice, the module could, for example, map tool paths and workpiece tolerances in parts of a cycle where tool wear is expected. That section of the sequence would be simulated on the machine without cutting metal, so the paths actually traversed by the tool could be recorded and compared with the workpiece design. The ability of the machine to produce the part to the required accuracy could then be determined.

Fewer sensors, more dataAnother module, Heller4Services, focuses on the transparency of digital manufacturing and maintenance. The module forms the basis for evaluating machine data and statistics, which in turn can help to reduce downtime.

This raises the question of the need for additional sensors in the machine. Heller says it is minimising their inclusion, as each additional sensor poses a potential risk of failure and compromising machine availability. The company says its approach to improving production processes is based on the possibilities for extracting and evaluating more data from existing sensors and making better use of it through additional computing power in the control, and Siemens’ Sinumerik-Edge technology.

Sinumerik-Edge, designed to improve production processes, is claimed to have new developments in four interrelated areas: the amount of high-frequency data that can be collected during machining; the architecture to process terabytes of that data in minutes; the semantic data model that defines how the information relates to the actual machining process; and the applications available for analysis, optimisation and feeding back meaningful results to the control.

Makino is another machine tool OEM with its own solution for I4.0 strategies. Its ProNetConneX is an interface that connects, collects and analyses machine data. The system is intended to provide manufacturers with a built-in, instant on-ramp to the IoT, with secure connectivity to software management systems via the MTConnect standard.

With support for fog-level computing over local networks, and Cloud accessibility, this interface is claimed to enable customised and secure transmission of machine information across connected devices on the factory floor. The system can be integrated into Makino’s machine controls to enable full MTConnect v1.3-compliant data collection. Additional machine sensors can be installed and added to ProNetConneX, thus expanding real-time manufacturing data collection capabilities based on customer requirements.

Creating a connected factoryAt Mazak, recent focus has been on iSmart - a factory-based concept that utilises the company’s I4.0 infrastructure to help machine users make the step up from automated cell manufacturing to a completely connected I4.0 ‘factory of the future’.

Mazak’s iSmart Factory is centred on three key pillars, namely the company’s proprietary Smooth Technology, the new SmartBox, which is said to provide fast data analysis with increased security, and the MTConnect standard communications protocol. All elements combine to facilitate the real-time sharing of manufacturing data between the production floor and offices.

Smooth Technology, incorporating CNC and ‘Smooth Process Support’ factory management software, sits at the heart of Mazak’s I4.0 infrastructure, from where it connects entire machine shops and provides real-time monitoring and analysis capability. Newly introduced programs include ‘Smooth Spindle Analytics’ software, which provides instant spindle vibration reporting and analysis.

Over 60 sensors are fitted to the DMG Mori machine at Schaeffler's Höchstadt plant

Over 60 sensors are fitted to the DMG Mori machine at Schaeffler’s Höchstadt plant

Data processing is made possible by Mazak’s SmartBox, which, utilising Cisco’s fog-computing concept, effectively extends Cloud computing closer to where the data is produced. This enables sensitive data to be analysed and acted upon securely, with only selected data sent to the Cloud for historical analysis and long-term storage. The company says the SmartBox can interface with any machine featuring an MTConnect adaptor and older legacy machines can also be connected to SmartBox with the addition of its new SensorBox.

Richard Smith, European group managing director at Yamazaki Mazak, says: “We can demonstrate that the connected factory of the future is here today. Ultimately, I4.0 is only going to become an ever-more critical element of modern manufacturing and Mazak is determined to ensure its customers embrace the opportunity and realise the full potential of their manufacturing capabilities.”

Constant status monitoring projectDMG Mori says it recently equipped one of its DMC 80 FD duoBLOCK machining centres with more than 60 sensors that transmitted digitised information on components to the Cloud for the purposes of data collection, storage and analysis. Constant status monitoring within the machine was the ultimate objective. Putting the theory to the test, a major supplier of bearings to the automotive industry, Schaeffler, is working out how to convert the data into practical machining knowledge (the aforementioned DMG Mori DMC 80 FD duoBLOCK pilot machine is in operation at the site). Schaeffler considers the opportunities to be highly diverse, ranging from improved management of the machining process, with greater focus on tool wear, for example, to lower energy and/or coolant consumption.

Likewise, on the basis of empirically determined ‘behaviour patterns’, the transferred status data can be used to make qualified predictions about potential damage to the spindle.

“With this project, we want to demonstrate that Industry 4.0 is not an abstract, remote vision but that it can make a contribution to added-value today,” says Martin Schreiber, president of the production machinery business unit at Schaeffler Technologies.

The DMG Mori machine at Schaeffler is equipped with sensors that can record the measurement values for pressure, vibration or force. Most are integrated in motion components such as bearings and linear guidance systems. Valuable data generated at these points is not only saved in the machine itself but also, in pre-analysed form, in the Cloud. Communication with central servers takes place via a secured gateway, which aims to protect against hackers. The condition of individual components can be viewed at any time, either using the operating terminal on the machine or via an Internet-connected device, such as a tablet.

Only when they are linked together can valuable information be derived from large pools of data, which can then contribute towards ensuring manufacturing processes are organised more efficiently. In order to clearly categorise the measured data, each component manufactured on the machine receives its own ID. All data generated during milling or in the subsequent machining processes can subsequently be assigned to a specific component. It is hoped that by comparing the data for individual components it will be possible to quickly recognise deviations, correct them, and in turn continuously optimise the manufacturing process.

Ronny Hüttner, who is responsible for the introduction of new technologies at Schaeffler’s Höchstadt plant, sees the machine as an opportunity: “With this project we are taking a clear step towards the digital value-added chain,” he says. “The decisive question will ultimately be, how significantly can we increase productivity in practice?”

The answer will soon be known as the machine is already being used by Schaeffler in the volume production of precision bearings. Machine condition is transparent at any time, helping production processes become more efficient and easier to plan.

Removing the guessworkAvoiding machine downtime makes a big difference to efficiency. Evaluating the data from the DMG Mori machine and its 60 sensors, it is possible to accurately schedule a machine bearing replacement, avoiding a breakdown situation.

“Recording load data, particularly for the main spindle, allows potential overloads to be made transparent,” says Hüttner. “The combination of data recorded by force sensors on the spindle bearings, and by speed sensors on the feed screw, allows us to calculate the remaining useful life of the bearings. We can choose when to carry out the necessary replacements based on the selected level of capacity utilisation.”

“Setting and inspecting the precise machine loads used to be a very complex task,” adds the machine’s operator Gezim Feta. “However, I can select the correct spindle operating mode and monitor the loads whenever needed via the control panel. If a load limit is exceeded, I receive an active warning and can therefore respond immediately. This also covers vibration on the machine components. Moreover, I can check for temperature fluctuations and view the effect on forces using the operating panel.”

Benjamin Wirth, quality manager, is also impressed with the potential of the machine. “The machine allows all process and quality data for manufactured parts to be traced,” he says. “In the future, data analysers will even make it possible to predict quality results. In other words, machine operators should be able to proactively influence the manufacturing process.”

The final word goes to Oliver Jung, COO at the Höchstadt plant: “We want to optimise existing processes digitally, to create new service-oriented processes and consistently promote the digital interaction of people and IT systems. The clearly defined goal is the permanent optimisation of production and the supply chain.”

A meeting of minds

At the EMO exhibition in Hanover towards the end of last year, Siemens demonstrated the various connection and installation options of its MindSphere open Cloud-based IoT operating system for applications in the machine tool sector. In fact, Siemens managed to connect over 240 different machine tools from over 140 manufacturers across the whole exhibition site using its ‘Manage MyMachines’ app on MindSphere.

“The overwhelming willingness of machine tool manufacturers at EMO to connect their machines to MindSphere shows the potential that the sector sees in cloud-based digitalisation solutions,” says Wolfgang Heuring, CEO of the Siemens Motion Control Business Unit.

Digitalising machine tool operations by connecting to MindSphere allows machine manufacturers and operators to analyse and use large volumes of machine data, thus helping improve machine efficiency and productivity. The open access of the operating system is particularly important, such as the use of open interfaces (APIs) to produce OEM and customer specific apps, as well as open standards for connectivity, like OPC UA.