Error-Free Assembly of Medical Components

A SUV and a medical device used in a lab aren’t very similar in their looks, but when it comes to manufacturing them, they have a lot in common. For both, factory automation is used to increase production volume while also making sure that production steps are completed precisely. Read on to learn about some ways that sensors are used in life science manufacturing.

Sensors with switching output

Automation equipment producers are creative builders of specialized machines, as each project differs somehow from previous ones. When it comes to automated processes in the lab and healthcare sectors where objects being processed or assembled are small, miniaturization is required for manufacturing equipment as well.  Weight reduction also plays an important role in this, since objects with a lower mass can be moved quickly with a smaller amount of force. By using light-weight sensors on automated grippers, they can increase the speed of actuator movements.

Conveyor system using photoelectric sensors for object detection

Photoelectric sensors are quite common in automated production because they can detect objects from a distance. Miniaturized photoelectric sensors are more easily placed in a production process that works with small parts. And photoelectric sensors can be used to detect objects that are made of many different types of material.

A common challenge for lab equipment is to detect clear liquids in clear vessels. Click here for a description of how specialized photoelectric sensors face this challenge.

Specialized photoelectric sensors for clear water detection

Image Processing

Within the last several years, camera systems have been used more frequently in the production of lab equipment. They are fast enough for high-speed production processes and support the use of artificial intelligence through interfaces to machine learning systems.

Identification

In any production setting, products, components and materials must be identified and tracked. Both optical identification and RFID technology are suitable for this purpose.

Sample analysis with industrial camera

Optical identification systems use a scanner to read one-dimensional barcodes or two-dimensional data matrix or QR codes and transmit the object information centrally to a database, which then identifies the object. The identification cost per object is pretty low when using a printed label or laser marking on the object.

When data must be stored directly on or with the object itself, often because the data needs to be changed or added to during the production process, RFID (Radio Frequency Identification) is the best choice. Data storage tags come in many different sizes and can store different amounts of data and have other features to meet specific needs. This decentralized data storage has advantages in fast production processes when there is a need for real-time data storage.

Data of RFID tag at pallet are read and written with RFID read/write head and transferred via bus module

There are numerous parallels between automation in the life science sector and general factory automation. While these manufacturing environments both have their own challenges, the primary automation task is the same: find the best sensor for your application requirements. Being able to choose from many types of sensors, with different sizes and characteristics, can make that job a lot easier. For more information about the life sciences industries, visit https://www.balluff.com/en-us/industries/life-science.

Basic Sensors for Robot Grippers

Robot gripper with inductive proximity sensors mounted
Robot gripper with inductive proximity sensors mounted

Typically when we talk about end-of-arm tooling we are discussing how to make robot grippers smarter and more efficient. We addressed this topic in a previous blog post, 5 Tips on Making End-of-Arm Tooling Smarter. In this post, though, we are going to get back to the basics and talk about two options for robot grippers: magnetic field sensors, and inductive proximity sensors.

One of the basic differences is that detection method that each solution utilizes. Magnetic field sensors use an indirect method by monitoring the mechanism that moves the jaws, not the jaws themselves. Magnetic field sensors sense magnets internally mounted on the gripper mechanism to indicate the open or closed position. On the other hand, inductive proximity sensors use a direct method that monitors the jaws by detecting targets placed directly in the jaws. Proximity sensors sense tabs on moving the gripper jaw mechanism to indicate a fully open or closed position.

BMF_Grippers
Robot gripper with magnetic field sensors mounted

Additionally, each solution offers its own advantages and disadvantages. Magnetic field sensors, for example, install directly into extruded slots on the outside of the cylinder, can detect an extremely short piston stroke, and offer wear-free position detection. On the other side of the coin, the disadvantages of magnetic field sensors for this application are the necessity of a magnet to be installed in the piston which also requires that the cylinder walls not be magnetic. Inductive proximity sensors allow the cylinder to be made of any material and do not require magnets to be installed. However, proximity sensors do require more installation space, longer setup time, and have other variables to consider.

Sensor Based Error Proofing – As easy as 1, 2, 3

Error proofing your manufacturing processes can be as easy as 1, 2, 3. You should be able to freely deploy error proofing in all appropriate locations in your plants without concerns regarding costs and long-term support or stability. It all starts by first identifying your trouble spots, then implementing a detection method, and finally establishing a process to handle the discrepancy. Let’s discuss the detection methods using sensors, as well as the process, for handling discrepancies.

By utilizing sensors as opposed to vision systems or other passive approaches, the cost of implementation and maintenance is reduced. With the new generation of low-cost lasers, sensors are now more affordable and easier to implement.  Radio Frequency Identification (RFID) brings new opportunities for handling non-conforming products. By tagging the individual part, assembly, or lot, products can be directed to the appropriate rework or scrap area.

These methods will allow you to implement more error proofing in your manufacturing lines to save thousand of dollars in scrap or rework and avoid the potential for costly containment.

Top 5 questions regarding error proofing…

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