GoFa and SWIFTI collaborative robot (cobot) families offer higher payloads and speeds to complement the YuMi and Single Arm YuMi cobot lineup. These stronger, faster, and more capable cobots meet the growing demand for automation across multiple industries. Users can operate the cobots within minutes of installation, straight out of the box, without specialized training. The portfolio expansion is engineered to help existing and new robot users accelerate automation amid four key megatrends transforming business, including individualized consumers, labor shortages, digitalization, and uncertainty.
The maXYmos TL ML process monitoring system for assembly and joining processes is compliant with FDA and EU MDR requirements.
PHOTO: KISTLER
Manufacturers need to address short-term measures to move forward with rapid, effective responses to changes in overall conditions and production chains. They also need to take strategic action to adapt to new challenges such as increasing requirements for production performance and product quality. Many manufacturers of disposable medical products, small devices, and plastic components depend on the injection molding process to achieve these goals. They should, as cavity pressure, or mold cavity pressure, is the most informative process variable. It allows total process transparency, enabling users to attain zero-defect production.
Cavity pressure provides a complete picture of the conditions under which a part is produced throughout the injection molding process and is an indicator of the quality of the part being produced. Quality-related characteristics such as dimensional accuracy, surface, weight, and degree of molding can be attributed to the cavity pressure profile during the injection, compression, and holding phases. The cavity pressure profile is the basis for precise statements about optimal process parameters throughout the entire production process. Good parts can already be distinguished from bad ones while production is still in progress.
Meeting demanding requirements
Sensors measuring cavity pressure must be dependable, accurate, and robust. Determining pressure and temperature requires reliable measuring technology with high resolution and no maintenance. Measuring chains must cover a melt temperature range up to 450°C and need to capture and resolve the smallest pressure fluctuations, even under pressure conditions of 2,000 bar. To meet these requirements, Kistler deploys piezoelectric sensors that are partially manufactured from special materials. Alongside the physical measurement principle, location is also a decisive factor, especially for process reliability. Kistler offers an extensive and varied portfolio of sensors to match every part geometry, installation position, injection molding process, and plastic material. The portfolio also encompasses direct and indirect measuring sensors, with diameters ranging from 1mm to 9mm, and sensors allowing the combined measurement of pressure and temperature. A third method besides direct and indirect measurement is contact-free measurement, where measuring pins capture the mold compression caused by the pressure. This portfolio brings benefits for users, such as having an alternative when lack of space in the mold makes direct measurement impossible or when the parts must be completely free of visible marks.
Intelligent process monitoring
Process monitoring systems independent of the machine control that are integrated into the production sequence allow optimal use of the information captured by piezoelectric sensors. This approach delivers a reliable, stable process combined with maximum transparency of the fundamental steps in the process. Suitable systems – such as ComoNeo – can track the progression of cavity pressure in real time. ComoNeo can also use adjustable evaluation objects (EOs) to assess part quality while the cycle is still running, giving users 100% in-process prediction of all quality features. As opposed to machine-integrated solutions, external process monitors can store complete curve profiles for the entire injection molding facility in one database. This way, manufacturers can compare past production runs with the target curve at any time, and the validated process profile can be proven in case of a complaint.
With the help of adjustable evaluation objects (EOs), the ComoNeo process monitoring system can assess a part’s quality while the cycle is still running.
PHOTO: KISTLER
One-stop solutions for medtech manufacturers
Alongside its process monitoring solutions for injection molding, Kistler offers a range of additional sensing and process monitoring solutions, including maXYmos systems for joining and assembly processes as well as testing manufactured parts. These solutions are based on acquisition and analysis of physical variables such as pressure, force, and torque. Integrating the maXYmos system into assembly processes makes process monitoring 100% transparent and reliable, so medtech device manufacturers can boost production efficiency from component design and part assembly through to final product testing. Medtech manufacturers can benefit from the maXYmos TL ML process monitoring system, the first monitoring system for assembly and joining processes that are FDA and EU MDR compliant.
A 10,000ft2 facility, equipped with CNC machines, automation systems, and advanced technologies, offers a real-world environment for students studying for careers in manufacturing.
A long-standing challenge the manufacturing industry has faced is filling the skills gap. While more jobs are being created due to advancing technology, there aren’t enough individuals trained for these positions. Deloitte and The Manufacturing Institute anticipate U.S. manufacturing will have 2 million unfilled jobs by 2028, a record-high.
Taking the concepts of lean manufacturing and 5s, Mississippi- based Meridian Community College (MCC) aims to close this gap. In the Gene Haas Advanced Manufacturing Center, located in the MCC Workforce Development Center, there are classrooms and fully equipped lab space featuring state-of-the-art computer-aided design (CAD) and machining equipment. Students gain hands-on training and learn highly technical skills to give them an edge as soon as they enter the workforce, ensuring they are qualified and ready to hit the floor running.
“We’re tracking time on jobs when they are assigned a project, and we try to incorporate all aspects of lean manufacturing into the curriculum,” says Brian Warren, program coordinator of Precision Machining and division chair of Industrial Technology at MCC. “Our goal is to provide them with an environment where they can get a real idea what it’s like to work for an advanced manufacturer.”
Meridian Community College (MCC) partners with suppliers such as Blaser Swisslube for their applications experience in the medical industry. Metalworking fluids from Blaser deliver the necessary process stability and tool life, as well as mirror-like surface finishes free of any residue.
PHOTO: BLASER SWISSLUBE
Building technical skills
Advanced automation and technologies are major driving forces behind manufacturing today, especially in the medical market. Designing products and components requires CAD, CNC machines, and inspection tools.
The lab allows students to learn these machining and CNC techniques by training on and operating various pieces of equipment, including a 5-axis Haas UMC500SS, a Haas ST-30Y turning center with Y-axis and live tooling, a Tsugami B0205 Swiss-style CNC lathe, a Zeiss coordinate measuring machine (CMM), and 11 additional CNC machines, along with a variety of manual lathes, mills, drill presses, and band saws.
A main focus of students working with the machines is operator setup and how to understand and correctly store information. Warren explains that students graduating from the program often start in positions as an operator or setup tech, so they need to know how to respond if a failure occurs. Working with these tools also allows the students to focus on efficiency and minimizing setup and changeover time in a production setting.
“It’s important they actually recognize what they’re doing and why, so they’re not just repeating a sequence,” Warren explains. “We’re making sure they understand what this offset means and why it’s crucial to have a setup. The students are also using the machines to design and build their own fixtures.”
Students also handle Blaser Swiss coolant, learning the proper way to mix and maintain machine coolant.
“I have worked for small shops where mixing coolant was as simple as pouring some soluble oil into a pail of water,” Warren explains. “We have now integrated coolant cleaning and mixing strategies into our daily routine with the students. When we change coolants, we flush the systems and clean the tanks. We use reverse- osmosis filtration for our tap water supply and precisely mix the Blaser to the proper concentration.”
Students check the concentration daily with refractometers using tank samples from all machines, and levels are adjusted as needed. Oil skimmers are also used to keep the machine coolant performing safely at optimal levels for all the students.
Rethinking our approach
Preparing for the future and being equipped to meet the increasing needs of the industry require an alternative approach to education. Warren emphasizes that to have enough skilled workers, it’s critical to build up support. MCC partners with several industry leaders – bringing in manufacturers and suppliers of tooling and machine tooling technology – who help train the students and allow them to run tests on software and various pieces of equipment.
“One of the main things we need right now in our industry is support, not only for training and to have more jobs available, but to provide the latest educational tools for our members.”
Students’ mindsets have also changed when it comes to selecting a school. More are turning toward community college programs, not because of proximity, but because they offer highly ranked curriculums that are best suited for their trade.
“It’s really interesting to watch these students grow because they start out kind of hesitant about it, but gradually, by the third semester they are walking and talking like experienced machinists,” Warrens adds. “I keep in touch with our graduates and one of my favorite things is getting a call from them and hearing about how well they’re doing out in the field, explaining recent scenarios, and talking about a run they just had. The graduates are happy and they love their jobs.”
This is an example of artificial intelligence (AI) training to locate defects on parts.
PHOTO CREDIT MITUTOYO AMERICA
There are three common types of vision systems: 1) CNC vision, 2) manual vision and 3) large field of view (FOV) vision. However, it’s important to note that there can be overlap across these categories (e.g., a large FOV machine can be a CNC machine or a manual machine).
While many facets of these technologies haven’t changed, during the past five years one development has emerged – stitching. Some vision technologies now generate large FOV images by stitching together multiple views of a part to see a greater overall image rather than importing the FOV all at once. This is a faster way to see and measure the part in total, and it’s also easier on the operator. And because high magnification is required to zoom in on small features, stitching combines speed and magnification to create a larger FOV than originally possible with the vision machine itself.
This is appealing for medical companies, given that large FOV machines on their own can detract from accuracy, making them less ideal where traceability and accuracy are crucial and where measurement is integral for U.S. Food and Drug Administration (FDA) approval.
As an alternative to costly large FOV vision machines with stitching capability, manual vision machines are also an option. Depending on the machine, exceptional optics can still measure the Z-axis with automatic focus – except the operator must manually move the stage.
Next-gen AI software
One exciting development in vision machine measurement is the recent arrival of artificial intelligence (AI)-based software. Used primarily for defect analysis and detection, and paired with a third-party camera, this software is teachable. Give the software good images and tell it why they’re good. Then supply the software with bad images and highlight the defects. Consistently increasing the number of images trains the software to automate defect analysis to separate good parts from bad.
Removing the operator from the analysis results in faster inspection of finished parts. This automatic, expedited defect detection capability is crucial for medical parts from needles and syringes to any part with zero tolerance for scratches, nicks, or molding defects.
Next-gen vision machines
The next generation of machines will be built for even greater measurement speed without sacrificing accuracy. They’ll be able to keep things flowing without interruption. Users will take a rapid succession of measurements because the machine will move across the features without stopping. In the near future, vision machines will allow traditional CNC machines to accelerate throughput with one continuous data stream.
An LED ring light surrounding a camera.
PHOTO CREDIT MITUTOYO AMERICA
Illuminating the future
Like a microscope, a vision machine requires a light source for proper measurement, and there are different ways to light a part. A stage light can illuminate a part from below to form a shadow, which produces contrast and is ideal for picking up outside edges and through-holes.
However, sometimes sensors measure a notch, a blind hole, or other internal feature. In this instance, illuminate the part from above using a coax light. This type of light shines straight down through the camera lens and uniformly illuminates the surface for measuring surface flatness.
Another near-universal lighting option is a ring light. This also illuminates the part from above, but instead of shining straight down, it shines at an angle. This works well for measuring the diameter of a cylinder. Don’t use a coax light because it will eliminate the top of the cylinder. However, a ring light will bring out its 3D features. More advanced vision machines allow changing the ring light angle, or use only certain quadrants of the light, depending on measuring needs.
Historically, vision machines used halogen lights for stage, coax, and ring lights until about a decade ago when manufacturers moved to LED lights. Before then, LED lights were either not bright enough or too expensive. They are now the lighting standard, because they last longer than halogen lights and their intensity can be set almost instantaneously.
The three main types of light sources are likely to become even more fine-tuned and powerful. Machines in the future will have greater sensitivity and the ability to manipulate lighting angles in a more sophisticated manner.
An example of image stitching where three camera fields of view (FOV) combine to create a single, measurable image.
PHOTO CREDIT MITUTOYO AMERICA
The future: CMOS
In the past, all vision machines used a charge coupled device (CCD) sensor or global shutter to capture frames and change the focused image into an electric signal the computer can understand. A CCD captures the whole frame simultaneously.
However, CCD is an old technology with limitations. That’s why many current and future vision machines will use a complementary metal oxide semiconductor (CMOS) image sensor instead. CMOS has abundantly more pixels compared to CCD, which increases accuracy. And while previous CMOS sensors would output too much noise to be useful for vision machines, sensors have recently improved signal-to-noise ratio to where they can now be used in vision machines. Sharper images and a higher pixel count increase measurement accuracy, crucial for measuring any products, but especially those in the medical field.
A mix of manual and automatic will remain
Despite innovation and newer advancements in next-generation vision machines, the future will always hold manual vision machines because of their lower cost and familiarity factor.
Every shop has likely used a profile projector, and it’s a small learning curve to go from a profile projector to a manual vision machine. And, for smaller shops, cost is a significant consideration. If a shop can only afford one vision machine, it’s likely to choose a manual machine rather than a CNC machine.
However, for those less constrained by budget, the future will be automatic, with larger FOVs and greater measurement accuracy. That’s a good thing for all fields, including medical.
Manufactured medical devices prolong and preserve the quality of life, and the ability of a component to function throughout a long lifespan depends greatly on accurately specifying, measuring, and controlling surface finish. Most surface finish specifications are limited to one or two general parameters, but these parameters typically cannot discern texture aspects that directly impact functionality and wear.
Below are some categories of medical devices and some of the parameters that can be used to specify and control aspects of surface texture that are critical to the parts’ functionality and durability.
Surface texture is more than roughness
Surface roughness is often used to refer to surface texture. That term can be misleading, however, as it tends to suggest a consistent, unchanging profile across the part. In practice this isn’t often what we see at the microscopic level. The texture will often consist of a combination of flat regions, sharp and rounded peaks, valleys, porosity, tool marks, scratches, etc.
Most surface finish specifications consist of only a single roughness parameter, such as average roughness (Ra) or average maximum height (Rz). These parameters are derived from two-dimensional measurement data often obtained from a stylus profilometer. For areal (3D) measurements, such as those made by optical profilers, the parameters Sa and Sz are used.
Roughness parameters can be useful for monitoring changes in processes, but they only provide general information about the nature of a surface. Tracking a process based on Ra or Rz alone is like trying to diagnose a person’s health only by measuring their temperature. A fever may indicate a simple infection, or it could point to a serious disease.
Figure 1 shows three optical profiler surface measurements with nearly identical average roughness values. If we measure only Ra, these surfaces are virtually indistinguishable. However, the top surface, with strong texture in one direction, may provide consistent fluid flow over the surface. The polished sample in the center has a deep notch which could lead to fatigue failure. The bottom surface shows non-directional texture that may be best suited for coating adhesion. None of these differences are detectable by average roughness alone.
Figure 1. Three surfaces with similar average roughness but very different actual texture.
PHOTO: MICHIGAN METROLOGY
How well medical devices will perform depends on particular aspects of their surface texture. Cardiac and arterial devices, for example, require smooth surfaces to avoid turbulent blood flow and prevent thrombosis and hemolysis. In an artificial joint, the bonding area may need to be rough while the bearing areas may need smooth surfaces for good wear and valleys to retain lubricating fluid.
Most measurement instruments and software report a range of surface texture parameters that are suited for specifying and controlling particular aspects of texture. It’s up to a component’s designer to determine which aspects matter most for functionality, and then specify parameters that’ll help production and quality teams control conditions.
Bearing surfaces
Replacement hips, knees, and other joints are designed to last more than 20 years, without the benefit of periodic lubrication or resurfacing. In these joints, metal components are bonded to the bones on either side of the joint. These components are separated by (and continuously rub against) bearing surfaces which accommodate the joint load while enabling smooth movement.
Metal bearing surfaces are often polished to the highest level of smoothness to minimize friction and wear. In the implant shown in Figure 2, for example, the bearing surface has a small Sa value of 0.10µm – a mirror finish. Some implant devices may be held to Angstrom-level Ra, which is an equivalent finish to high-performance optical surfaces.
Figure 2. The surface of this implant has been polished to a mirror finish. But is this the best surface for the component?
PHOTO: MICHIGAN METROLOGY
Instinctually, it seems that a polished surface would provide the least friction and the best wear characteristics. This is very much application-dependent. When a joint retains sufficient synovial fluid, then the smoothest possible bearing surfaces are best. If components are rubbing directly against each other, however, with little lubrication, then the bearing surfaces must have some degree of texture to reduce the real area of contact and to retain the small amount of available lubricant.
The nature of the texture also matters. Surface texture parameters such as Mean Summit Curvature (Ssc) and Summit Density (Sds), have been developed to provide a much clearer prediction of friction and wear than an average roughness value alone. Parameters derived from the bearing area curve, and tribology parameters, are also good predictors of friction and wear.
It’s also important to note that a surface manufactured with a mirror finish will not look that way for long. Peaks in the texture will wear quickly during the initial use period. After this wear-in period, the surface will reach a steady state that will, hopefully, change slowly throughout the component’s life. A product designer can’t only focus on making a joint that functions optimally at time-zero but must also determine the characteristics of an initial finish that’ll wear into a long-lasting bearing surface.
Bonding surfaces
While the mating surfaces of a replacement joint typically need to be smooth, the bonding areas of these components must instead be very rough to provide sufficient surface area for a good bond. In the hip implant shown in Figure 3, the femoral stem (which bonds to the femur bone) has an average roughness value of approximately 7µm. These components undergo aggressive processes such as shot blasting to create finishes with Sa values as high as 20µm – texture that’s visible to the eye.
Figure 3. The bonding areas of a hip implant have much higher roughness than the bearing areas.
PHOTO: MICHIGAN METROLOGY
However, it’s not sufficient to simply roughen up the surface: the nature of the texture matters. Typically, these surfaces are designed with isotropic (uniform, non-directional) texture, as any directionality could lead to slipping or swiveling of the joint.
Additionally, particular amplitudes and spacings of texture features have been found to promote bone growth. The Developed Interfacial Area Ratio (Sdr) parameter provides information about the texture amplitude and spacing that can lead to better adhesion control.
Measuring finish on complex surfaces
Complex surface shapes are very difficult or impossible to measure with many standard instruments. For example, measuring the small, highly curved features of a spinal implant may be extremely challenging with a traditional stylus profiler because these instruments typically lack the vertical range needed to track the highly curved surface.
Non-contact, 3D optical profilers, such as the one shown in Figure 4, are well-suited to these kinds of measurements. The long working distance and large vertical range of an optical profiler enable measurement of highly curved surfaces. Fixtures and mirrors give access to otherwise inaccessible features.
Figure 4. An optical profiler provides high resolution, 3D measurement of complex surface shapes.
PHOTO: MICHIGAN METROLOGY
Surface finish for flow
The surface finish for components involved with fluid flow must meet a dramatically different set of functional requirements. Surfaces over which blood flows, for example, must remain extremely smooth throughout their lifetimes to prevent clot formation.
The scale of the texture that matters in this case, however, may not be the scale of the blood cells; it may be the more finely spaced and lowered amplitude texture that the proteins produced by the cells could interact with to initiate the clotting mechanism.
In devices that contact blood, manufacturers aim for the smoothest finishes, often less than 100nm average roughness (Sa), as in Figure 5. Smooth finishes also prevent damage to blood cells from processes such as hemolysis as the cells are forced through constrictions.
Figure 5. The texture of a device associated with blood flow is extremely smooth to inhibit clotting processes.
PHOTO: MICHIGAN METROLOGY
The surface texture of a medical device is fundamental to its function. Today’s 2D and 3D measurement systems provide an array of targeted parameters that are excellent controls for many different medical device functionalities. By specifying and controlling these parameters we can optimize the component’s surface to increase performance, wear life, and safety.
About the authors: Donald Cohen, Ph.D., is the founder of Michigan Metrology and Mike Zecchino is the technical communications manager with the company. Inquiries can be directed to 866.953.5030 or info@michmet.com.
