The Corona pandemic created a huge demand in the Life Science sector for Covid testing equipment. The ramp-up of such a production volume can only be realized through the use of automation. Most components for laboratory analysis are also produced automatically.
Automated production processes ensure greater efficiency and reliability. This applies to the production of devices for blood analysis or in the diagnosis of tissue samples. Also, automation plays an important role in the assembly of other medical devices and for analysis processes in laboratory diagnostics.
The producers of such automation machines typically have their roots in classical factory automation. Historically, often with the focus on automotive production, as the economies of scales are highly relevant in automotive production. In addition, however, many of these manufacturers have also acquired know-how in mechanical engineering in the Life Science sector.
Sensors with switching output
Automation equipment producers are creative builders of specialized machines as each project at least somehow differs from previous ones. When it comes to automated processes in the lab and healthcare sectors, miniaturization plays a significant role in the automation task, as the objects which are processed or assembled become even smaller. Weight reduction also plays an important role in this. According to the formula “force = mass * acceleration”, the dynamics of the actuator movements can be increased. A reduction in mass will lead to a lower force. This is necessary for acceleration and movement of objects. So when reducing the weight of grippers and of the sensors used on grippers, the force will be reduced accordingly.
Photoelectric sensors are quite common in automated production. Their advantage is to detect statuses from a distance. In production of lab equipment in the Life Science sector, miniaturized photoelectric sensors offer advantages:
A common challenge in lab technology is to detect clear liquids in clear vessels. This blog post describes that task. Specialized photoelectric sensors face this challenge.
Position Sensing and Image Processing
In the automation sector, axis positioning is a highly relevant topic.
To find suitable position sensors, linear magnetic encoder systems are a good choice. They require very little space and provide adequate position accuracy for most applications.
Within the last years, camera systems have come up in the production of lab equipment. They are also fast enough for high-speed production processes and support the use of artificial intelligence through interfaces to machine learning systems.
Identification
In the life science sector, a wide variety of objects must be identified and tracked. Both optical methods and RFID technology are suitable for this purpose.
Optical identification systems automatically identify objects such as components, products or production resources. They read one-dimensional barcodes or, increasingly, two-dimensional data matrix or QR codes and transmit the object information centrally to a database. The identification cost per object is pretty low when using a printed label or lasermarking on the object. The content of the optical code attached to the object refers to the object information available there.
When data shall be stored directly at or with the object itself (when data may be changed or added during a production process) RFID (Radio Frequency Identification) is the best choice. This decentralized data storage has advantages in fast production processes when there is a need for real-time data storage concepts in contrast to cloud solutions with significant communicating time delays.
Conclusion:
There are numerous parallels between automation in the life science sector and general factory automation. Differences, however, lie in the cleanliness requirements of the ambient conditions or in the size of the objects. As a result, the manufacturing systems to be designed also differ. This will also allow to increase the usage of cobots in life sciences’ production equipment.
