AI-Powered Quality Assurance
Those who digitize the quality assurance process in the first step can subsequently save time, money, and patience with the help of artificial intelligence.
In regulated production processes, it is essential to ensure complete and legally compliant documentation of all production steps, as well as any errors and disturbances. This often incurs multiple work steps, personnel costs, and even more paper documents.
- 17. October. 2024
Step 1: Digitization
The problem can be illustrated through a use case in the pharmaceutical sector. For instance, if a deviation occurs, such as the overfilling of a vial, it often takes several hours to days between the initial recording and the completion of the documentation process. In this case, a quality assurance employee must repeatedly request information from the production team that was lost during the initial recording. However, the quality manager needs the details to adequately assess the incident.
Delays of this nature have several consequences. Either the employees who initially recorded the incident are no longer available, or they have already forgotten the information—the operation continues, after all. This not only has process-related implications but could also have legal consequences in the worst-case scenario. Costs inevitably arise to retrospectively address the disruption.
How can companies avoid this tailspin of time, money, and effort?
An automated solution is needed to speed up communication between the various stakeholders. The first step requires digitizing the entire process documentation. Tablets are particularly suitable for this due to their ease of use. With the integrated camera, scanning QR codes or barcodes is effortless, and employees can attach photos to the report if needed.
A small bonus: Since the vast majority of production employees are already familiar with mobile operating systems like iOS and Android in their personal lives, the usability entry barrier is low—there are no additional training costs.
Digitization? Check!
Now, artificial intelligence comes into play: Based on the captured information, the responsible employee receives an AI-assisted suggestion before saving. This suggestion indicates how critical or non-critical a particular incident is and how likely the suggestion is to be accurate. If the AI is unsure due to insufficient information, the user is given a warning.
Benefits
After saving, the incident is immediately sent to the next—human—instance (Quality Assurance) for verification. Therefore, a person always performs the final control function, known as the “human-in-the-loop.” This individual can request additional or missing information digitally, accept the assessment suggestion, or overwrite it again.
Depending on the evaluation, the incident is not only automatically entered into a quality management system, but the actual assessment is also recorded.
Additionally, the system stores requested missing information in a way that allows the AI model to learn from this entry. As a result, future inquiries will be generated automatically rather than manually.
Ultimately, companies benefit not only from a more sustainable paper consumption but also save time, money, and their personnel’s patience due to the AI-optimized process.
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