October 2015

October 27, 2015June 28, 2019

PTFE Heat Shrink Tubing: Wall Thickness After Recovery

Recently a customer wanted to use some PTFE shrink tubing to cover the shoulder of a bolt as a slip surface and had questions about the wall thickness of shrink tubing. In this customer’s application they were starting with a 0.140” mandrel (the shoulder of the bolt), and the tubing they were considering had a nominal recovered wall thickness of 0.010” with a tolerance of +/-0.003”.

The customer’s main question was: “After going through the heat shrink process, what would you estimate the wall thickness to be and how uniform is it?”

We frequently receive questions like this about estimating wall thickness. In this case, our customer was trying to work out if he would be dealing with a finished outside diameter on the low end of 0.154” (the mandrel plus the two walls, 0.140”+0.007”+ 0.007”) or on the high end of 0.166” (the mandrel plus the two walls, 0.140”+0.013”+ 0.013”). From the highest possible outside diameter to the lowest, a 0.012” swing can make a big difference so the concern is valid and raises two other questions. First, what is allowed in order for the product to be considered within specifications? Second, what do users need to make the product work for their application?

For this post, we are going to make the assumption that the products are going to be in spec because at Component Supply, we distribute quality products and, honestly, we are awesome pretty much all of the time. So, let’s go over the aspect of making the product work for the application. In general, we have found that the wall thickness is fairly true to the nominal or within +/-0.001”. So, for the typical application you can plan on that being the case. In the example we have been using, this would yield an overall outside diameter between 0.158” (the mandrel plus the two walls, 0.140”+0.009”+ 0.009”) or on the high end of 0.162” (the mandrel plus the two walls, 0.140”+0.011”+ 0.011”).

Just a side note: we would not suggest that you do something like design a product with tighter specifications than what is called out in our charts. That’s just a good way to disappoint a lot of people.

October 15, 2015June 28, 2019

Understanding Nylon and Polyester Mesh Properties

Introduction

Component Supply’s stock of filter mesh is a versatile material used in multiple industries and in a variety of applications. To assist researchers and product designers in choosing the best mesh for their applications, we want to define and explain the different properties of our mesh and how they impact each other.

There are seven major attributes of mesh: 1) mesh opening, 2) open area, 3) mesh count, 4) thread diameter, 5) weight, 6) thickness and 7) air permeability. At Component Supply, we don’t list weight, thickness or air permeability in our product information because, unlike the first four specifications, these three are not typically relevant in determining mesh use most applications. However, to give you a full picture of mesh properties, we will provide a simple definition for those terms as well.

Mesh Attributes

1) Mesh Opening refers to the actual size of the opening. In the charts on our site, this is measured in microns. Mesh opening is typically the most critical attribute because it determines the size of the particles it will capture and the size of the particles it allows to pass through. This attribute is specified in microns, which is a metric measurement equaling one thousandth of a millimeter.

2) Open area indicates the percentage of a specified area that is open. Open area can help determine what sort of flow restrictions might occur because of the filter. If we take a square piece of mesh screening that is exactly one inch by one inch and move all the lateral and horizontal fibers (warp and weft – we will cover this in another post or video) up and to one side we will be left with some part of the square that is solid (covered by the threads) and some part that is now open. With a mesh that has a 25% open area the square inch will be segmented into four parts, three (75%) will be covered by the threads and one (25%) will be open.

3) Mesh count is the number of threads in a linear inch and is fairly easy to determine. For example, if you were to lay out a piece of mesh and place a ruler on top, then count the horizontal threads from the beginning of the ruler to the one inch mark that would give you the mesh count. Of course, this is a simple task for mesh sizes like 1000 microns, which has 19 threads per inch. But it is daunting or even flat out impossible for some of the smaller mesh sizes. For mesh sizes down to about 200 microns you can count, or at least count one quarter of an inch and multiply. For sizes much smaller than that, it becomes difficult without some magnifications and a good bit of patience.

4) Thread diameter is the diameter of the thread measured in microns.

5) Weight is the weight of the material typically measured in ounces per square inch.

6) Thickness is the overall thickness of the mesh and measured in microns.

7) Air permeability measures the rate of air flow passing perpendicularly through the mesh and, for our mesh, is measured liters (l)/square meter (sq. m.)/second (s).

The Relationship between Mesh Attributes

When selecting the appropriate mesh for an application it is important to know how these attributes are related to each other. Let’s use an example of mesh that has a 500 micron mesh opening, a 50% open area, a thread count of 20 and a thread diameter of 250 microns. If we were to change just one of these attributes, it would completely alter the product you’d be using. For example, if we decreased the thread diameter but left the mesh count constant, we would wind up with a larger mesh opening and open area. If we needed to capture smaller particles with a smaller mesh size, but wanted a similar open area for flow restriction reasons you could find a mesh that has the same thread diameter and a higher mesh count, or you could find a mesh that has an increased thread diameter and keep the thread count constant.

Conclusion

Understanding the attributes of mesh and how they relate, makes selecting it for a specific application less daunting. That being said there are not an infinite number of possibilities available. This mesh is woven on looms that produce as much as 10,000 meters at a time, so only very large filtration and screen printing applications get to “choose” what they really want in terms of mesh properties. While there may be other sizes, and we encourage you to ask about them, the specifications on our site represent most of what is available. Understanding the properties of mesh and how they are related and then purchasing based on that information is more effective and realistic than trying to customize your own mesh.

October 9, 2015June 28, 2019

Researcher Spotlight: David A. Brown, PT, Ph.D., FAPTA University of Alabama at Birmingham

In August, Component Supply attended the FIME show in Miami, Fla., where we were able to see a demonstration of the KineAssist-MX. This month, we had the opportunity to speak with one of the collaborators in its development and hear his insights on multidisciplinary research.

When it comes to research, University of Alabama at Birmingham (UAB) Professor David Brown finds the multidisciplinary, collaborative approach both rewarding and effective.

“There’s some risk involved when someone who is an expert in their field crosses over into another field, but the shared expertise is invaluable,” Brown said.

One of the greatest examples of his multidisciplinary approach is the development of the KineAssist-MX, a device providing unobtrusive support to patients relearning how to balance and walk, particularly after a stroke.

The collaboration on this project started back in 2002 when Brown and two mechanical engineers at Northwestern University, Ed Colgate, Ph.D. and Michael Peshkin, Ph.D., worked on a research proposal for funding that would be given for developing technology considered too risky for investors.

After visiting high-profile clinics in Chicago, observing their practices and trying to determine what technology was needed most, Brown discovered the clinicians preferred co-robotics. They wanted mechanisms that not only move based on the intent of the patient but also the intent of the clinician.

Brown said co-robotics is particularly effective for people recovering from stroke who are basically learning how to walk again.

“The brain learns best when challenged to do tasks slightly higher than ability level,” Brown said.

With the KineAssist-MX, patients can work with physical therapists to challenge themselves in a safe environment.

Unlike typical treadmills, which move at a constant speed, the KineAssist picks up on patients’ intentions, errors and the expected consequences while allowing opportunities to practice movement and retry.

The device not only moves based on the intended movement of the user, it also simulates various environmental factors through variable speeds, disturbed surfaces and force fields.

“It’s a multi-purpose playground where people can try different real-life situations, make mistakes and get right back up and keep trying,” Brown said.

Along with Brown’s work with this device, his continued work in The UAB Locomotor Control and Rehabilitation Robotics Laboratory, better known as the LocoLab, is based on collaboration with scientists and clinicians.

“Our work is very multidisciplinary,” he said.

In Brown’s lab, there are more than 10 students from different backgrounds: Ph.D. candidates, occupational therapy and physical therapy graduate students, an engineering student and even high school students. The variation of backgrounds and ages is beneficial in collaborative work and Brown said he finds joy in inspiring the youngest students.

“We want the high school students to connect and find the aspects of their projects that really excite them,” Brown said. “We want them to come away passionate and more mature in their thinking.”

Brown and his students focus on three aspects of study: basic mechanistic studies, effective exercise-based interventions and development of new technology. They are studying how the brain controls movement, particularly after a stroke, developing clinical interventions and applying the interventions with new technology in a way that gives patients the opportunity to practice movements in a safe environment.

For more information about Brown and his research in the LocoLab at UAB, visit: https://www.uab.edu/shp/pt/locolab/locolab-kineassist.

Oct 9, 2015