Pharmaceutical manufacturing is all about precision. Any little problem in the area of equipment, materials, environment, and processes can create problems that are costly and hard to solve.
However, many manufacturing settings still use information spread out across multiple platforms.
While production data might be in one platform, equipment data might be somewhere else. Inventory data, labor information, quality data, and batch data may also be on different platforms.
This is referred to as visibility gap.
There could be too much data available for the manufacturer, yet he/she will still have trouble understanding what is going on in the facility in real time.
The Visibility Gap in Pharma Manufacturing
For instance, a production batch is delayed.
The problem may be due to any of the following reasons: equipment availability, material flow, maintenance, labor allocation, or process deviation.
Given that data is spread out across various disconnected platforms, identifying connections between events will take some time.
A connected operation will offer a different perspective.
It will be more focused on connecting events.
For instance:
Material flow + equipment status + workforce activities + batch data = expanded operational context.
However, it will not replace human knowledge. It simply provides more information for the investigation of the issue.
The Value of Real-Time Data
Historical data may be beneficial, but manufacturing teams sometimes require real-time information.
Real-time visibility can help them understand:
The location of critical assets
The working condition of equipment — working or idle state
The location of materials flow
Active production areas
Correlation between operational events and production activities
Potential bottlenecks
The goal is not to monitor all aspects just because it is technically feasible.
The goal is to get the necessary information at the moment when it matters.
Integration of Physical Assets and Digital Technologies
Such technologies as RFID, BLE, IoT sensors, GPS, and other connected devices may provide information about the physical world.
For instance, RFID can assist with material identification. BLE can help create proximity and location applications. IoT sensors can gather information about the equipment and its environment.
But the true value comes from tying these events to digital systems.
A material movement event is more significant when there is a way to tie it back to a particular batch, production area, or planned activity.
An equipment event is more valuable when it becomes clear that a certain production process relies on the particular equipment.
This is what distinguishes data collection from operational intelligence.
Where Can AI Help?
AI can provide help with analysing high volumes of operational data and identifying trends which may not be easy to notice otherwise.
Some potential use cases for AI are anomaly detection, predictive maintenance, process analysis, resource optimization, and operational forecasting.
So, for example, equipment usage patterns can reveal conditions requiring maintenance.
Or, a repeated pattern of material movement delays can indicate a bottleneck in a production process.
AI does not have to make the final decisions.
Many times, all that is required from AI is to bring to light some crucial information in a timely manner.
Role of AIoT
Integration of AI and IoT allows tying physical manufacturing processes to intelligent analytics.
One possible AIoT architecture can include:
Connectable devices → Edge computing → Data integration → Analytics → Operational insights
This structure may help companies evolve into a more connected manufacturing setup.
(pharmafluxai.com) concentrates on an approach to intelligent and connected pharmaceutical manufacturing that integrates such technologies as AI, IoT, RFID, BLE, and edge intelligence.
The idea behind the approach is quite clear: connect the necessary data first and then try to automate the decision.
Better Visibility Does Not Mean Increased Complexity
There are worries that introduction of more connected technologies may add extra complexity to digital transformation.
This is why the implementation process should start with a certain operational problem.
“What do we lack visibility in at the moment?”
The answer may be material traceability, equipment efficiency, cleanroom operations, asset management, or production monitoring.
After identifying the problem, it becomes possible to select the appropriate technology.
How to Build a More Connected Pharma Facility
Digital transformation can take place step by step.
Organizations can start with one valuable use case, set the goals, connect the necessary data sources, and analyse the results.
Then other systems can be connected.
It also makes it easier to prove business value.
Potentially useful metrics may include:
Equipment downtime reduction
Accelerated material search
Asset optimization
Manual tracking reduction
Accelerated investigation times
Production visibility improvement
Workflow efficiency enhancement
The Future of Pharmaceutical Manufacturing Operations
The future of pharmaceutical production will probably not be characterized by one technology.
Rather, it will be determined by the ability of various technologies to work in tandem with each other.
Sensors will gather events.
RFID will assist in better identifying and tracking products.
IoT will enable connections between equipment and the physical space.
Edge computing will allow information processing closer to the data sources.
AI will help detect patterns and provide insights.
Experts will make decisions based on these insights.
This synergy allows building operational intelligence that goes beyond isolated automation.
For pharmaceutical companies, the aim of implementation should be not only collecting information but gaining more clarity into what is going on in the production environment and using it for improving its performance.
A smart factory does not mean a factory equipped with the most advanced technologies.
