Smart Tools’ Target: Data Analysis, Not Paralysis

The road to manufacturing success today runs through the mountain of data that tools are generating in metal cutting applications, and most importantly communicating and reacting to in real-time on the shop floor.

Keys to collecting data include: sensor technology, that is built into tools and tool networks; software that can seamlessly collect, organize, and analyze data; and machine tools that can be networked into a source of factory intelligence. The elements that lead to effective “smart” tool applications can be intimidating unless you engage with companies that can sort out exactly what is needed, what should be avoided, and what else is coming down the pike.

Market Demand Catches Up with Technology

Technology to successfully collect, distribute, and analyze data for adaptive control of machining processes has been available long before the current interest in things Industry 4.0 and IIoT. For some time, attendees at major trade shows have had the opportunity to witness cells put together by Caron Engineering Inc. (Wells, ME) featuring the key factors for successful, adaptive machining, through data collection and analysis. “Sophisticated shops are really beginning to accept the idea that the more you know about the machining process, the better off your production, quality, and efficiency are going to be,” said Rob Caron, president.

The emergence of the MTConnect standard, the emphasis on digital connectivity and better and less expensive sensor technology, are making it easier to justify the additional investment required to gather data about every aspect of the machining process. “At current customers, for example, we usually start with RFID tool presetting off-line in the tool crib,” he said. “All parameters are embedded in the RFID tag and transferred to the machine control, where we monitor all the tools through power, vibration, strain, and other parameters. We do some adaptive cutting, modify the feed rate to maintain constant power, and measure the part with electronic devices before sending the data upstream for analysis.”

The reality, Caron added, is that everyone wants the magic bullet that will tell them everything that’s going on in their process. “In that regard, everyone is working on better sensor technology—and better analytics through self-learning and artificial intelligence in software,” he said. Key considerations for sensor development include higher resolution for vibration, power, and coolant flow for high-pressure systems, and better technology for characterizing coolant concentration.

“Most of our products are at the machine level,” Caron pointed out, “where they collect a huge amount of data.” These products include DTect-IT, a Windows application that communicates with Caron Engineering USB sensors to monitor any area of concern on the machine tool or fixture, using custom sensors for vibration, strain, and analog applications.

Caron’s Tool Monitoring Adaptive Control (TMAC) system protects CNC machines by reducing the high costs associated with broken tools, lost production, and rejected parts, by measuring tool wear in real time. The “adaptive” control feature of TMAC reduces cycle time and optimizes cutting time under changing conditions to improve tool life.

Tool Connect automates the transfer of tool presetter data from RFID tags in toolholders to a machine control. AutoComp software uses any electronic gaging device to provide the dimensional measurements and processes gage data to update tool offsets automatically, providing error-free tool offset control.

How Good Can Data Connected Machining Be?

For Wolfram Manufacturing, an Austin, TX-based contract manufacturer, Caron Engineering’s products worked so effectively in the shop that company President, Nathan Byman, decided to become a distributor for Caron products. Wolfram Manufacturing specializes in medium to high-volume production, manufacturing parts from start to finish, including material sourcing, machining, specialty coating, and specialized packaging.

Wolfram produces parts up to 24″ (609 mm) in diameter, 60″ (1524 mm) in length and weighing 500 lbs (226 kg). Because accuracy is a key part of machining, typical tolerances are down to ±0.001″ (0.03 mm) with special features down to ±0.0001″ (0.003 mm).

Byman had experience with Caron Engineering’s TMAC system in large contract machine shops he ran before starting Wolfram, which uses highly flexible machining cells in its production. “At Wolfram, every machine we buy has probing, high-pressure coolant, and is a multifunction mill/turn—machines that are optimized using the TMAC system. TMAC introduces feedback to our processes which lets us automate and made them repeatable.” Wolfram runs Okuma machine tools. “We like the Okuma support structure and the THINC control allows us to get a lot of information in and out of the control, a capability that is especially important for data-generated adaptive machining,” Byman added.

“Today’s sensor technology is better than ever,” said Byman. “The trend in cost of sensors, vibration sensors for example, is coming down and their resolution is getting higher. These systems might add 5–10% to the cost of a mid-size machine tool, or 3–5% for a larger machine, but they can unlock productivity improvement of 20–40%,” he said.

“Our customers for Caron’s products are typically OEMs, who have a deep focus on their machining processes and a heavy commitment to manufacturing engineering. As a result they are more likely to be prepared for what Caron products have to offer. For those that are less sophisticated, education is the first step,” said Byman. “Our approach in dealing with any customer is to recommend working with them to bring their first parts on line and showing them a path to success. We find this works best since most organizations need some help to absorb the thought process and power these tools provide.” To do that, Wolfram has a full engineering capability.

Byman believes that continued sensor development will produce even better resolution, horsepower transducer range, and better response time. “On the software side, TMAC already has a lot going on under the hood in terms of processing algorithms, but there is still a lot to be gained by leveraging the data for trend evaluation and visualization. Right now you program knowledge into the system. It will mature into a place where you are taking knowledge out of the system for use in other places,” he explained. 

‘The Nervous System of the Machine’

“Studies indicate that 40% of manufacturers have little-to-no visibility into their production processes, even to knowing how many parts are being produced during a shift,” said Will Healy III, Marketing Management Director, Balluff Inc. (Florence, KY). Balluff is a leading manufacturer of a wide range of sensor technologies including: inductive, photoelectric, vision, capacitive and magnetic, as well as linear position transducers, RFID systems, and networking products. These technologies are used to control, regulate, automate, assemble, position, and monitor manufacturing, assembly, and packaging for OEM and factory-floor solutions in a wide variety of industries.

“There are three factors that are energizing the Industry 4.0 drive toward smart manufacturing,” Healy said. “The key motivations are efficient production, flexible manufacturing, and visibility at the machine operator, supervisor, and plant management levels. Efficient production results in reduced downtime and changeover time, and improved quality. Flexible production could achieve small batch or small lot production, even to a lot size of one. Flexible production increases the value of investments in capital equipment with significant returns from faster format changes, tooling changes, and setup changeovers. Smart devices are now enabling predictive maintenance to reduce unplanned downtime,” Healy explained.

“In the machine tool market, we see ourselves as the nervous system of the machine, generating data and transporting data to the controller, and making data available in the Cloud for monitoring and analysis,” said Healy. He noted that the standard inductive sensor is the workhorse of the industry, providing visibility into machine tools and processes. Smart sensors, for example, enhance hydraulic power units where there is a lot of pressure, load, and coolant flow levels to measure and trend. “In addition, when you are chucking or clamping in a CNC machine, a proximity sensor in the collar clamp indicates if it’s closed,” he said. “Put two or three sensors in the clamp and you can see if it’s open, closed, or closed empty. An interesting trend we are seeing is putting an analog measurement inductive sensor or a smart measurement sensor into the clamp; you can also now indicate if the clamp is closed properly, closed on the right toolholder, or even if it’s the right toolholder for this machine.”

However, with smart sensors, it doesn’t always make a lot of sense to get the data over Ethernet with a few bits of information, said Healy. The IO-Link open communications protocol was developed to make it easy to connect smart devices into the controller without all of the overhead that Ethernet typically requires, such as managed switches, IP addresses, and the need to get power and Ethernet to the sensor. Since IO-Link is an open standard, most, if not all, of the automation companies are providing products with IO-Link, including Allen-Bradley, Siemens, Balluff, and Festo, among others. One of the key benefits of IO-Link for automation is the possibility to “hot swap” devices since all the settings can be saved in the controller or the IO-Link master. When a new sensor is detected, all the settings are automatically downloaded to the new sensor, simplifying maintenance and dramatically shortening downtime,” Healy explained.

Translating Big Data into Smart Data

According to Jorge Pena, Product Manager, Marposs Monitoring Solutions (MMS), Marposs Corp. (Auburn Hills, MI), “it is essential to carry out real-time monitoring of machine parameters, part or tool variations, and unexpected events in order to optimize the process and limit quality risks or unplanned costs.” Marposs Monitoring Solutions monitors the key factors influencing machining processes, including all metal cutting processes, with the objective of optimizing the processes.

“Basically, Marposs Monitoring Solutions offers autonomous, modular, electronic, plug-in technology, and self-adjusted monitoring solutions for the automotive, molding, power generation, oil/gas, and aerospace industries,” said Pena. “Smart monitoring solutions can capture all data utilizing a multi-sensor and multi-visualization criteria for real-time tool and process monitoring, adaptive control, and crash mitigation with a very fast processing and sampling time.”

The big data captured by the processing unit can be converted and downloaded as smart data easy to understand by the user. Data recorded include specific indicators, traces reporting, alarm reporting, tool trending, and condition-based monitoring (CBM) with fingerprint statistical data of every single point. All information is transmitted to the computer which visualizes, analyzes, and documents the entire process and creates a comprehensive database with a history of every tool and projects tool life for each tool, according to Pena.

“In production areas, there are a wide variety of machine tool types and designs that are used. Modes of operation can be manual or automatic loading/unloading, and machine controls are different according to brand, age, and CNC or non-CNC. Marposs Monitoring Solutions are selected based on the information available from the machine and/or through various methods of capturing data, either with or without sensors,” Pena said. “Digital torque adapters (DTA) provide sensor-less selection of drive data captured by the machine’s CNC, which can be used for tool, process, and machine condition monitoring,” he added.

Additional multi-external sensors are available for monitoring machine conditions and/or to elaborate abnormal machining processes from vibration, force (load cells), torque, motor current, spindle noises, displacement, tool runout, acoustic emission, axial-bending forces, and coolant flow.

According to Pena, the approach used depends on the application, process, machine, and type of CNC controller. “We can use a different sensor if it’s a machining center, turn broaching, a lathe with three turrets, or a multi-spindle lathe. Depending on the type of the CNC, the monitoring solution is flexible enough to monitor the tool and cutting process in real-time, completely sensorless. If we want to monitor a lathe, we could use a force sensor to monitor the load on the tool when it’s cutting. Other sensors, like strain, MEMs, ceramic, or piezo sensors, either custom or standard versions, are applied on the machine body, workholder, or spindle turret to detect very small changes of cutting forces to identify errors in the cutting process, providing a lights-out operation.”

Powerful Millturn Features Smart Boring Bar

At EMO 2017, WFL Millturn Technologies Inc. (Wixom, MI) presented a diverse range of technologies with a focus on smart internal machining technologies. For example, in collaboration with Sandvik Coromant (Fair Lawn, NJ), WFL demonstrated how an “intelligent tool” could be used on the powerful M120 Millturn. The functionality of the intelligent 18xD CoroPlus boring bar demonstrated the effectiveness of networking with smart tooling. The boring bar was integrated into a special WFL prismatic toolholder, which includes a data interface.

CoroPlus technology allows machining information and tool status to be transmitted to the control system or a tablet. During processing, the machine operator is provided with information regarding temperature, deflection, background noises, vibration, and the load on the tool. In this way, the chip removal process can be optimized, protecting both tool and workpiece from damage. In addition, the complete process can be logged in full.

Typical applications in the aviation industry include landing gear, and jet engine and turbine drive shafts, as well as oil field applications for machining long bores in complex workpieces.

In addition, the WFL M120 Millturn / 3000 mm was equipped with new measuring and testing technology from Blum-Novotest Inc. (Erlanger, KY). The machining of large, heavy, and complex workpieces poses significant challenges for measuring systems. With the integrated TC63-DIGILOG measuring probe, digital measurements and analog scanning processes can be carried out directly on the machine. Analog measurements are especially useful for the evaluation of surfaces or contours (e.g. checking of the surface of a workpiece for machining errors). With a switching digital probe, on the other hand, a large number of points would need to be measured in such cases to ensure that adequate resolution is achieved.

However, the new analog probe makes use of scanning to generate thousands of measurement values in a fraction of the time. With the TC63-DIGILOG, quick, accurate measurements of up to 2 m/min are possible for features like fully-automated roundness, run-out, and axial run-out measurements.

Written by:  Jim Lorincz, Senior Editor, for AdvancedManufacturing.org.