Manufacturing operations within pharmaceuticals produce data virtually at all steps of production. Batch records, machine activities, material handling, quality management and production schedules all contribute to a broader perspective.
The question is how to turn all of this data into something that teams could actually use.
With manufacturing data distributed between MES, ERP, LIMS, QMS, spreadsheets and other disconnected systems, it may become hard to track where potential delays or inefficiencies appear.
AI and IoT technologies can be used to link these separate pieces of data. With production data combined with tracking and analytics capabilities, manufacturers will be able to get more visibility about batch status, work-in-progress, material movement and process performance.
This will allow to detect bottlenecks, follow production stages, look into deviations and understand the relationship between machines, materials, people and processes involved.
The purpose of this is not to accumulate more manufacturing data. This is to draw better operational insight out of the data that is already produced by manufacturing processes.
Process intelligence can help pharmaceutical manufacturers to make smart decisions based on this data.
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