Pharmaceutical manufacturing has never been an easy process.
Everything from raw materials and inventory to cleanrooms, machinery, people, batching, quality systems, and the final products generates a vast quantity of operational data in today’s manufacturing facilities.
Collecting this data has never been a problem.
The difficulty is in making sense of all this data.
This is when the combination of Artificial Intelligence with Internet of Things becomes very appealing for pharmaceutical manufacturing.
From Connected Machines to Connected Operations
Traditionally, manufacturing automation was all about machines and processes.
Yet, there is far more to pharmaceutical manufacturing than machines.
A single production environment needs to coordinate:
People
Manufacturing machinery
Laboratory instruments
Raw materials
Inventory
Cleanrooms
Production batches
Quality systems
Environmental factors
Enterprise software solutions
When such systems operate individually, valuable information gets dispersed across various platforms.
The integration provided by AIoT provides an opportunity to connect those operations to get a more complete picture of what happens at the manufacturing site.
Such technologies as RFID can provide tracking of materials or assets. BLE can help with location intelligence. Environmental sensors will keep on capturing the data, and edge computing will enable processing this information where it happens.
Artificial intelligence can then analyze all these streams and detect patterns, anomalies, bottlenecks, and other operational information.
The Importance of Visibility in Pharmaceuticals
Pharmaceutical manufacturing is a highly regulated activity.
Visibility is required into processes, materials, people, equipment, documents, and traceability.
Think about an obvious question:
Where is an important piece of equipment currently?
Answering that question in a non-connected environment may require manual searches, phone calls, Excel sheets, or separate systems.
In a connected AIoT world, it is possible to have access to information about the location and usage status in real time.
It can be applied to inventory, people movements, production stages, and other operational events.
For instance, the PharmaFlux AI solution concentrates on pharmaceutical manufacturing intelligence in terms of workforce visibility, asset tracking, inventory management, batch traceability, cleanrooms operations, and GMP operations.
AI + IoT = A New Level of Manufacturing Intelligence
IoT provides the eyes and ears.
AI gives you an analytical level.
Together, they can provide a much more intelligent manufacturing environment.
Imagine a pharmaceutical facility where:
Sensors constantly check the environment.
RFID identifies materials and assets.
BLE gives the location information.
Edge systems process the operational events.
Enterprise systems integrate manufacturing and business systems.
AI analyses the information and uncovers the relevant patterns.
Instead of asking people to manually search for disconnected information, companies can move towards systems that will surface relevant information at the right moment.
This shift from data collection to manufacturing intelligence could become a major hallmark of next-generation pharmaceutical manufacturing.
Batch Traceability
Traceability is another area that could be significantly improved with the help of connected technologies.
The pharmaceutical industry relies on various interconnections between raw materials, manufacturing processes, equipment, people, batches, packaging, and final products.
It is crucial to understand the nature of these interconnections for operational purposes and regulatory readiness.
AIoT technologies could help build digital connections between physical events and production records.
RFID, serialization, sensors, enterprise systems, manufacturing data, and other elements can be used to build a more comprehensive picture of material flow and production history.
This could contribute to the following applications:
• Batch genealogy
• Lot traceability
• Serialization visibility
• Chain-of-custody tracking
• Material lineage
• Production history analysis
The point here is clear — you need to know what was done, where it was done and how one event is related to another.
Human Factor in Intelligent Manufacturing of Pharmaceuticals
There is a common misconception regarding intelligent manufacturing.
AIoT does not mean automation of production process and replacement of humans.
AIoT can provide people with more information.
In the course of the manufacturing process, production operators, quality departments, laboratories, maintenance workers, warehouse workers, and management all make decisions.
Visibility could give these teams more information about what is going on around them.
For instance, workforce intelligence could offer more information on personnel location, clean room occupancy, access governance, training compliance, etc.
Integration May Be the Biggest Challenge
Installation of another technology platform is not the solution.
Pharmaceutical manufacturing organizations already have several systems such as MES, ERP, LIMS, QMS, environmental monitoring system, tracking technology, and others operational systems.
True value lies in connecting all of these.
Therefore, edge integration and industrial connectivity become increasingly relevant today.
Connected pharmaceutical environment allows unification of manufacturing systems information, enterprise applications information, sensors information, RFID information, BLE information, and AI analytics.
PharmaFlux AI refers to this concept as pharmaceutical edge integration and it connects MES, ERP, LIMS, QMS, RFID, BLE, environmental monitoring, and AIoT.
What’s Next?
Probably, the future of pharmaceutical manufacturing won’t be about single technology.
It will be about technologies connection and integration.
Neither AI alone can deliver physical visibility in real-time.
Nor can IoT alone analyze complicated manufacturing processes.
Neither RFID alone can deliver manufacturing intelligence.
Neither BLE alone can change pharmaceutical production.
However, these technologies, along with sensors, edge computing, enterprise systems and intelligent analytics can deliver a much bigger ecosystem.
This is the true potential of pharmaceutical AIoT.
Automation is only a part of the solution.
Connecting information between systems, analysing it and using data to understand operations is another.
This way, manufacturing operations become visible.
Problems can be found at early stage.
Information can be combined into one ecosystem.
And this will eventually lead to better decisions based on information.
The factory of the future may become intelligent and constantly aware about its own operations.
For those organizations which take the same direction, (pharmafluxai.com) can serve as a good example of how AI, IoT, RFID, BLE, environmental monitoring, edge computing, and enterprise integration can be combined for pharmaceutical manufacturing intelligence.
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