As medical device manufacturers (MDMs) continue to make smaller and more complex products, often from challenging advanced or sensitive materials, machining equipment companies must improve their machines to reliably make these new designs, some of which push the limits of what machining can do—all while speeding up production and keeping costs down.

“The payoff is big if you can solve a problem that others can’t, but the level of difficulty is at another level now as ophthalmic, neurovascular, and cardiovascular devices push the limits of micro-machining metals and polymers,” said John Shegda, CEO for KMM Group, a Hatboro, Pa.-based contract manufacturer of high-precision components for several industries, including medical devices.

Internet of Things (IoT) and Industry 4.0 technologies—especially automation and robotics—are critical for improving efficiency, quality, tolerance control, and speed of production. Boosting these capabilities also helps computer numerical control (CNC) machines stay competitive with additive manufacturing (AM) and injection molding processes, especially for making small, complex shapes with extremely tight tolerances. CNC machines can produce machine parts as small as 0.01 inches in diameter, with tolerances as tight as 0.0002 inches. With the ongoing shortage of skilled labor, there is even greater interest in using IoT to stay operational and competitive, especially by using automation and robotics to create fully automatic “lights-out” manufacturing cells that do not require a human attendant.

Current Trends

Minimally invasive (MI) procedures and related implants, instruments, and other tools are a hot medical-device market. MI procedures typically rely on robotic processes and, as these components and devices get smaller, with tighter tolerances, manufacturers need more capable machining equipment. For example, micro machining is often needed to make tiny, high-precision, intricate parts and/or features. As manufacturing becomes more complicated, MDMs are increasingly turning to their contract manufacturers (CMs) for design for manufacturability (DFM) sessions to streamline the design and production process. MDMs are especially hopeful for more automation (improved quality, faster production, lower costs), as well as tighter tolerances and better surface finishes to eliminate as much of the post-machining hand work as possible.

MDMs often request specialized or custom materials in their machining projects. “Materials range from specialty plastics such as medical-grade PEEK [polyetheretherketone] and Ultem [polyetherimide] to specialty stainless steel and titanium alloys,” said Greg Paulsen, director of applications for engineering and marketing for Xometry, a Rockville, Md.-based manufacturing marketplace that provides an AI-based platform for connecting potential buyers and sellers in the medical machining market. “The ability for virtually any material to be processed with machining is a big reason why so many engineers still favor a machining approach.”

Medical device manufacturing requires both precision capabilities and auditable quality controls. Traditionally, qualified shops are difficult to seek and source. New marketplace platforms like Xometry can help stabilize supply chains or find skilled back-up suppliers to draw on when needed. “Xometry allows customers to specify their technical requirements with the assurance that their project is paired with a capable manufacturer—all while using Xometry’s platform for a digital chain of accountability,” said Paulsen.

Advancements in computer-aided design (CAD) and computer-aided manufacturing (CAM) platforms continue to enhance designs and manufacturability. For example, generative design can create custom products using software versus typical human-directed design. These designs can generate specific processes, like 2.5-axis machining, fifth-axis machining, and more. Artificial intelligence (AI), for example, can generate hundreds or thousands of design options for a particular project far more quickly than engineers can accomplish at their desks. Once the key design and performance parameters are imported into the generative design software, it generates all possible outcomes—giving designers and engineers a head start on developing and prototyping a new medical device.

MDMs are constantly looking for ways to hold tighter tolerances in material dimensions and surface characteristics. This caries over into the finishing process. Being able to control how bright/shiny, dull/matte, and smooth/rough a component can be has become increasingly important to MDMs. For example, the ability to have sections of titanium parts stand out with color, or using color to differentiate between similar components, is in high demand. “This emphasis on the finish can be functional—such as avoiding glare in the surgery field, allowing for a friction fit or smooth movement, avoiding mix-up, or providing a rougher surface to aid in bone growth,” said Kevin Ford, general manager for American Bright Works, a Fridley, Minn.-based provider of surface finishing for metal components used in the medical device, surgical, and dental industries. “But finish is also important for identification and cosmetic or marketing purposes.”

Technology Advancements

Overall, machining technologies have not changed greatly in the last few years—however, they are being combined in various ways to create single hybrid machines. Converging multiple operations into a single process on a single machine reduces handling, eliminates steps, and saves time. This makes operations more efficient, improves production speed, and gets products to markets faster.

“Examples of hybrid equipment are Swiss screw machines that incorporate laser technology, five-axis mills that can incorporate some grinding, and guidewire grinding machines that have alternate axes to generate non-round features,” said Shegda. “This trend of converging the different disciplines of manufacturing will definitely continue.”

For example, additive manufacturing, micro machining, laser cutting, bar-fed multi-axis machining, AI, machine learning, and automation are all processes that can be added to a hybrid machine. Hybrid equipment drives costs down by shortening lead times for prototyping and production volumes. Hybrid machines can be customized so the entire production process occurs on a single machine—such as insertion of material, which is then fully machined, marked, and verified in a single operation. This is also hugely beneficial when it comes to part traceability.

MDMs are designing smaller parts with numerous intricate and high-precision features, especially for MI procedures. Even though these components are smaller and harder to make, with tolerances in the 0.001 inch range (roughly half the width of a human hair), MDMs want them made faster and at lower cost. Micro machining is typically required to produce the tiny components that fit into these devices, especially for medical robots, which depend on highly precise and compact moving parts.

“We are working with parts that have diameters down to 0.007 inches in machining and 0.0017 inches [45 microns] in grinding,” said Shegda. “Parts that to the naked eye look like a tiny metal shaving are actually complex, tightly toleranced device components.”

Sometimes an engineer will design a part that theoretically looks promising, but when it is modeled and it is determined what the actual tools are that would be required to produce it, it becomes unmanufacturable and some features become unmeasurable.

“This is where DFM can make a huge difference,” said Shegda. “This is also where hybrid equipment can allow for the manufacture of parts that could never before be produced. Guidewire grinding is an excellent example of this—a combination of a Swiss screw machine and a centerless grinder. Here, extremely specialized hybrid centerless grinding allows grinding a 6.0-mm diameter stainless steel component for heart valve transplants to a 0.002-inch wall thickness with perfect concentricity.”

Some manufacturers are discovering that supercritical CO₂ provides the same lubrication effects as traditional cutting fluids, with some extra benefits. Supercritical CO₂ is a fluid state of CO₂ and can also carry and disperse chilled nanodroplets of oil for even better lubrication during machining—decreasing cycle time, improving cut quality, and extending tool life.

GF Machining Solutions, a Lincolnshire, Ill.-based manufacturer of CNC machining centers, EDM machines, and lasers for micro machining, has developed a high-speed milling application with supercritical CO₂ + MQL (minimal quantity lubrication) to replace traditional flood coolant. “This new system is drastically improving the machinability and cleanliness aspects when machining titanium, which is especially useful when manufacturing implanted medical devices,” said Donald Wuestenberg, business development manager of medical for GF Machining Solutions. “Additionally, we have found when using supercritical CO₂ to machine UHMWPE [ultra-high-molecular-weight polyethylene], we almost completely eliminate burrs, which currently requires tedious hand work to remove.”

Lasers continue to be used in creative ways to make tiny, high-precision features for medical devices. Laser micromachining can remove material in nearly any shape or pattern, creating features as small as 10 to 20 microns in diameter, with submicron tolerances. Ultrafast laser machining is especially useful for the production of precision components with complex patterns. These lasers also enable very small, high-resolution black marking for medical devices and instruments; anti-counterfeit laser marks can even be applied that are invisible to the naked eye and only picked up by machine vision.

Precision cutting of stents and drilling of catheter tips is readily achieved with lasers. “Ultrafast lasers, with pulse duration in the femtosecond regime, can ablate many different materials with no heat-affected-zone, burr free,” said Wuestenberg. “This cold ablation can also protect the base material from subsurface micro-cracking and reduction in fatigue strength.”

Femtosecond lasers are the fastest lasers available. With femtosecond (1 fs = 10-15 s) pulses of laser light that are extremely well focused, they can cut complex shapes with high dimensional accuracy. “Because of their superior peak power, femtosecond lasers can process nearly any type of solid material, including layered, mixed, laminated, or coated materials, with the highest quality and precision,” said Blake Winkelmann, technical solutions manager for Spectrum Plastics Group, an Alpharetta, Ga.-based provider of critical polymer-based components and devices for medical and other demanding markets.

Lasers can also be used for surface texturing instead of media blasting prior to coating on titanium implants. “We use a full 5-axis machining center to create a rough surface for adhesion using either nanosecond or femtosecond laser blasts,” said Wuestenberg. “The advantages here include elimination of masking operations, a 100% digital process, reproducible surface texture, and a clean process that may even eliminate the need for a post-cleaning stage.”

“One of the greatest benefits of femtosecond lasers is the reliability/repeatability of the micromachining of complex features and patterns with great accuracy,” added Winkelmann. “In fact, some features can only be cut with femtosecond lasers, expanding design options for engineers and designers.”

Subtractive Machining Versus Additive Manufacturing

The medical device market is one of the fastest-growing industries for additive manufacturing. AM is suitable for complex parts, internal features, and low-volume components. However, AM is a slower process compared to CNC machining, as the various layers of material require time to heat and solidify, making it too slow for large-scale production.

Both AM and subtractive manufacturing (SM) have their place in the manufacturing world. Currently AM cannot produce the tight tolerances or high-volume parts that CNC machines can make. In addition, subtractive machining has established known performance standards—these are still being developed for AM. That said, subtractive machining and AM can also complement each other—for example, machining is often needed as a secondary operation to finish AM-made products. In fact, equipment manufacturers will create dual machines that incorporate both processes—for example, feeding in a semi-finished component and then performing both subtractive and additive manufacturing to create the final product.

“Right now, the engineers who are designing components are largely not thinking to leverage the real strength of AM,” said Shegda. “They are only looking at whether AM can make a design faster than SM, or maybe can make a component that they tried to have made through SM but found it to be impossible. They are not truly designing for AM. When they begin to do that, we will see component configurations that absolutely cannot be made through SM.”

An example from the heavy equipment industry is Caterpillar. In December 2015, Caterpillar opened its “Additive Manufacturing Factory” in Mossville, Ill. Stocked with all the latest AM technologies and related gear, the facility serves as a lab for engineers to learn how to design products specifically for AM technologies on production-capable AM.

When the medical device industry starts to seriously design for AM, “assemblies and multiple components, for example, will be combined into a single unit and printed,” said Shegda. “No longer bound by what can be made by subtractive methods, the designs will be like nothing we have seen to this point. Where subtractive holds its value is in the requirement for accuracy and speed. Both methodologies will be relevant and viable in the future.”

Additive manufacturing will eventually become a practical, reliable manufacturing tool. “However, there are hurdles it needs to overcome for the medical device industry—for example, how to qualify the parts, surface finish, and material availability,” said Paulsen. “With CNC machining, you can source qualified materials, and since you are cutting them, you do not have to re-qualify the material, only the geometry.”

For additive, however, the raw material is manipulated during the printing process, which can yield different results per print, often requiring further testing. Additive also leaves a rougher surface, which typically requires additional post-processing such as chemical vapor smoothing, which enhances AM finishes without introducing a new coating.

“Material availability is also limited in AM compared to CNC machining raw stock,” said Paulsen. “Uncertain variables can limit how and where additive can be practical for medical devices beyond rapid prototyping. The advance of digital tools and in-situ manufacturing controls, however, will help narrow this gap, putting additive manufacturing side by side with subtractive machining in many applications.”

Moving Forward

Machining technologies will continue to evolve. CAD and CAM improvements have enhanced CNC programming, expanding the limits of what can be machined. On the machining side, newer machines have more CAD-assisted tools and integrations for training and operation. Materials are also becoming more specialized for certain types of machining.

Software advancements are improving the efficiency of manufacturing operations, including assembly, inspection, and packaging. Automation is in hot demand—not just to help bridge the labor shortage but to create completely automatic, unattended manufacturing cells. Using sensors, AI, robotics, cloud-based big data analytics, and other IoT technologies typically result in higher production rates, compliance with quality standards, and higher overall equipment effectiveness (OEE). Manufacturing software programs can also be accessed in real time through mobile applications, allowing for real-time decision making.

Some companies—KMM Group is one—have dedicated R&D centers that focus only on pushing the limits of machining and grinding and are “staffed with creative thinkers who come up with amazing ideas that push the industry forward,” said Shegda. “This is not necessarily a profit-center for us—we are simply focused on coming up with a solution to something that others struggle with. This contributes to our industry and moves us forward as company.”

IoT and Industry 4.0 technologies will quickly evolve to make operations incredibly lean, fast, and mistake-free as possible. One of these tools is AI, which probably has the greatest potential to transform CNC machining processes in a continuous process of improvement.

According to Christine Evans, director of product marketing at Fictiv, a San Francisco, Calif.-based on-demand manufacturing company, a strong move toward AI in manufacturing operations is under way.1

“Over the next several years, CNC machining could see something of a revolution that includes machines that respond to Alexa-like voice commands, predictive learning and machine scheduling for optimized performance and down time, and better data analysis, programming, and testing,” she said. “Where AI comes in is in taking the numbers, relaying them directly to machine operators and the machines themselves, and automatically suggesting performance changes, timing changes, and production changes to ultimately increase total throughput.”

Further, artificial intelligence can predict when machines need to be serviced and gauge the optimal time to do so. By working with a set of data that is connected to production runs, run times, machine productivity, and tool life, AI can predict optimal times for servicing and machine tune-ups. “Figuring out optimal servicing and downtime slots is crucial to keep shops running at peak performance,” said Evans. “AI data will also provide information on how long a machine can run before it needs to be serviced. Predictive data such as this means less tool failure, prolonged tool life, less downtime, and saved time and money.”

The most rapid positive changes will come when AI is combined with digital twins of either products or processes, all in one system. AI can create an almost unlimited range of test conditions to quickly test various combinations of variables to see which ones result in the most efficient improvements. High-performance digital twins can even have their own AI engines for regression testing new product designs. AI functionality then automates test processes based on what it discovers and predicts actions that might be needed.2

“IoT will continue to grow in importance in machining as we progress through this decade,” said Shegda. “Big data and connectivity requirements of OEMs will drive these exciting technologies to the forefront in the medical device industries. Digital twins, AI, machine learning—it is all happening now, and will become much more mainstream in the years ahead.”

Article source: MPO