Four Key Technology Trends in Pharmaceutical Production

Driven by consumer demand, regulation, skills availability and digital transformation, the pharmaceutical production sector adapts quickly to change. In this blog article, we take a look at Four Key Technology Trends in Pharmaceutical Production.

Michael Suer of Mitsubishi Electric Europe considers the four key technology trends having the greatest impact. They are collaborative robots, cooperative robots, artificial intelligence, and edge computing technologies.

Pharmaceutical Production

One clear trend in pharmaceutical production is the increased demand for collaborative robots (cobots). Tasks include dosing, mixing, counting, dispensing, inspecting, and marking medications in pharmaceutical laboratories. Their cost-effectiveness and ease of programming means cobots are at home in both large and small facilities and multi-labs.


Working alongside humans cobots can relieve people of monotonous, tiring, and stressful tasks. They are more reliable and consistent and complete repetitive tasks with complete accuracy. They increase the efficiency and quality of human work and help protect sterile environments from contamination.

For example, Mitsubishi Electric’s cobot, the MEFLA ASSISTA, has a surface that prevents dirt traps and is easy to clean. It also achieves a repeat accuracy of ±0.03 mm, close to that of the company’s industrial robots (±0.02mm).

Cobots are simple to control and programme by the operator and are also portable for quick redeployment. By changing the hand/actuator they can move between different tasks, and their inherent safety features, mean they work alongside human operators without danger.


Some applications mean production robots operate at high speed. But stopping them can impact productivity, as the robot must stop before an operator approaches. Furthermore, after an emergency stop or if a protective barrier opens, it may need a complex restart procedure.

To protect humans without stopping production line robots, optical safety systems replace physical barriers. For example, laser scanners watch defined zones around the robots. If a human enters the outer zone, a speed reduction function slows the robot down. If they continue into the area where there is a danger of direct contact with the robot, it stops immediately. Once the area is clear, the robot automatically resumes its tasks at normal speed.

Mitsubishi Electric offers a solution with its MELFA SafePlus technology. Safety activated sensors limit the speed, range of movement or torque of the robot. This allows operators to work in safety near a moving robot.


Artificial intelligence (AI) is another trend impacting the pharmaceutical sector. In robotics, AI ensures a safe response to unforeseen and non-programmed situations. It also provides predictive and preventative maintenance information on the robot’s condition to the operators. 

AI technology is also offered within Mitsubishi Electric’s MELIPC edge computing solution. They act as a gateway between the plant floor and the higher-level systems to monitor and analyse data from the shop floor level (data mining).


The data mining of production data helps producers improve their overall equipment effectiveness (OEE). It provides them with real-time data for improving their processes. But when it is also business-sensitive data needing secure handling, edge computing provides a local solution. It enables prompt internal evaluation of sensitive batch and production data within pharmaceutical manufacturing.

OEE is also affected by the efficiency of the production line itself, which is reliant on the condition and operating profile of devices. Edge computing solutions like MELIPC provide valuable information for analysis. Extracting this provides the basis of predictive maintenance strategies for reducing service costs and unplanned downtime.

Adopting these technologies benefits the pharmaceutical production sector, boosting output and efficiency. They are available, accessible, and economic to adopt.

Notify of
Inline Feedbacks
View all comments