Today, digital transformation in pharmaceutical manufacturing goes beyond automating manufacturing processes or digitizing documents. Modern plants collect massive amounts of operational data using manufacturing equipment, lab systems, warehouse processes, environmental sensors, and enterprise software. However, the problem remains how to convert these data into useful intelligence.
In this regard, Artificial Intelligence of Things (AIoT) is a solution that merges artificial intelligence and connectivity in industrial technologies to ensure real-time operational visibility across pharmaceutical manufacturing.
In this article, we discuss the key technologies of AIoT and how they contribute to the development of more connected and data-driven pharmaceutical operations.
The Challenge: Data Are Everywhere
Today, most pharmaceutical manufacturing facilities operate state-of-the-art digital systems.
Common environments include:
Manufacturing Execution Systems (MES);
Enterprise Resource Planning (ERP);
Laboratory Information Management Systems (LIMS);
Quality Management Systems (QMS);
Environmental Monitoring Systems;
Warehouse management systems;
Production equipment.
Each system performs its functions but often operates independently. As a consequence, valuable operational data become fragmented, and it becomes difficult to see the full picture of operations.
The integration of AIoT allows pharmaceutical manufacturers to analyse operational events for people, assets, materials, and manufacturing processes.
Key Technologies of AIoT
AIoT leverages several mature technologies to create an operational ecosystem
Artificial Intelligence
AI analyses vast amounts of operational data in order to uncover patterns, detect anomalies and generate insights to help drive manufacturing decisions.
As opposed to only using historical reports, organizations gain operational awareness in real time.
Internet of Things (IoT)
Devices that constitute Industrial Internet of Things (IIOT) constantly collect operational data from manufacturing equipment, warehouses, laboratories and environmental monitoring systems.
Those connected devices lay the foundation of operational visibility.
RFID
Radio Frequency Identification (RFID) allows automatic identification and tracking of:
Manufacturing assets
Inventory
Materials
Equipment
People
Reducing manual collection of data, RFID allows gaining better inventory accuracy and operational visibility.
Bluetooth Low Energy (BLE)
BLE technology allows indoors location awareness of people and mobile assets.
Use cases include:
Visibility of workforce
Location of equipment
Monitoring of mobile assets
Presence in cleanrooms
Access to controlled areas
Edge Computing
Edge computing allows analysing of operational data closer to the manufacturing facility rather than reporting every event to the cloud infrastructure directly.
Such approach helps reduce latency while making it possible to respond to operational events faster.
Practical Applications in Pharmaceutical Manufacturing
AIoT technologies are applicable to many different operational areas in regulated pharmaceutical facilities.
Workforce Intelligence
Connected identification technologies facilitate improved workforce visibility as well as:
Shift management
Cleanroom occupancy
Authorized access
Workforce planning
Audit preparation
The goal is increased operational awareness, not simply personnel monitoring.
Asset Intelligence
Critical assets are needed in order to manufacture successfully.
AIoT allows for:
Equipment tracking
Utilization tracking
Maintenance scheduling
Calibration tracking
Mobile asset tracking
This increases equipment availability while decreasing time spent locating critical assets.
Inventory Intelligence
Inventory management involves more than just counting your stock.
Connected technologies increase visibility into:
Raw materials
Active pharmaceutical ingredients (APIs)
Packaging materials
Controlled substances
Finished goods
Continuous inventory intelligence ensures operational continuity and aids in regulatory documentation.
Digital Traceability
Traceability remains essential in pharmaceutical manufacturing.
AIoT facilitates digital connections between materials, equipment, workforce, production process, and finished product.
This provides a more robust batch history while facilitating quality investigations and regulatory documentation.
Integration Benefits
One of the biggest strengths of AIoT is that it works alongside your manufacturing process rather than competing against it.
Today's AIoT platforms interface with legacy enterprise systems such as MES, ERP, LIMS and QMS, which enables manufacturers to interconnect their operational data across the departments without impacting their existing processes.
Such an integrated approach helps reduce information silos and gives a more holistic insight into the performance of the manufacturing process.
Looking Ahead
With the rise of the connected manufacturing, the concept of operational intelligence is gaining as much importance as operational automation.
The future of digital manufacturing is about collecting data from people, machines, materials and manufacturing processes and putting it all together in an operational environment to give insights into what is happening there at any moment.
Such a technological shift is enabled by AIoT technology, which combines artificial intelligence, Internet of Things, RFID, BLE and edge computing to create a connected environment that allows for better visibility, traceability and operational decision-making based on collected data.
If readers want to get more details about the application of AIoT technologies in the context of pharmaceutical manufacturing facilities, this overview published by PharmaFlux AI is recommended: [https://pharmafluxai.com/]
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