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.

Collaborative Automation…It’s Not Just for Robots

Manufacturing is made up of hundreds of discrete operations. Some are repetitive, while others are more diverse. Repetitive tasks are ideal for automation while diverse tasks require more flexibility. And while automation can be extremely flexible, that comes with a high initial investment costs and significant deployment time. The alternative? People!

Humans have the unrivaled ability to adapt to a diverse and flexible manufacturing environment. They can be productive relatively quickly with proper guidance without high initial cost investments.

But as we all know, “to err is human” and this is one of the biggest issues with manual operations. People need a little guidance from time to time. Collaboration is not just for robots; It’s for complete automation systems as well.

Collaborative automation is most important at the point-of-use, where humans are performing critical operations. Some of those common operations include:

  • Manual assembly for low volume or highly flexible operations
  • Delivery of raw materials to the point-of-use
  • Kit assembly for down-stream operation
  • Machine setup and change-over
  • Machine maintenance and calibration

All of these functions can be done error-free and with little training by simply guiding people within their current work envelope, also referred to as their point-of-use. This type of a lean function provides hands-free guidance in the form of indication devices connected directly to your automation system allowing workers to stay focused on the task at hand instead of looking elsewhere for instructions.

With the technology of IO-Link, smart indication devices can now show much more information to all the people involved in specific manufacturing tasks. Automation has an immediate and direct connection to the people that are so vital.

For example, in a manually-fed weld-cell, the smart indicators are capable of not only signaling that the part is loaded correctly, but also whether the part is out of alignment (shown here by the red indicator) or that something wrong with one of the automation components such as a stuck pneumatic clamp.

Figure 1
A manually-fed weld-cell with smart indicators is capable of not only signaling that the part is loaded correctly, but also if the part is out of alignment (shown by the red indicator) or that there is something wrong with one of the automation components such as a stuck pneumatic clamp.

Even better, with IIoT technology, trends can be analyzed to determine if the fixture/tool could be optimized for production or to identify common failure points. This all leads to tighter collaboration with operations, maintenance personnel and production supervisors.

A traditional kitting station, sometimes referred to as a supermarket, is another ideal application for smart indicators. Not only can they guide a single operator to the intended part to pull, they can guide multiple operators at the same time.  Also, smart indicators can inform of incorrect pulls, potential bin options (a physically closure bin), directional information, and inventory levels. And again, with IIoT technology, trends can be analyzed to determine proper layout, individual personnel performance and system throughput. The automation system collaborates with operations, forklift drivers and production supervisors.

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A traditional kitting station, sometimes referred to as a supermarket, with smart indicators to guide operators to the intended part to pull.

So, take a look and see what a collaborative automation system utilizing smart indicators can do for your manual operations. You might be surprised.