• Written by Sonali Subhadarsini, Product Manager

This week, the quality manager at a manufacturing plant must decide whether to accept a shipment of components from a new supplier, and she currently bases her decision on a combination of the supplier's reputation, the results of a few trial runs, and her team's capacity to inspect the components on arrival, a process that is closely tied to production planning and control.

Enforcing permission at retrieval

Most people get wrong the idea that instructing the model to only return certain types of information is sufficient to control who can see what, but this approach is flawed because it relies on the model being correctly configured and maintained over time, which can be difficult to ensure, especially when the system is used by people who did not build it. A better approach is to enforce permission at the point of retrieval, so that even if someone tries to access information they should not see, the system will prevent them from doing so. This requires a robust system of permissions and access controls, which can be complex to set up and maintain.

The shift supervisor, for example, should only be able to see the quality control data for the shifts they are responsible for, and not for other shifts or areas of the plant. This requires a system that can dynamically adjust the permissions based on the user's role and responsibilities, which can be a challenge to implement and maintain.

Auditability

Auditability is critical for ensuring that the system is being used correctly and that any issues or errors can be quickly identified and addressed. This means keeping a record of what was asked, what was returned, and on what data, so that it is possible to track back and understand what happened if something goes wrong. This can be a significant challenge, especially in a system that is handling a large volume of requests and data, but it is essential for maintaining trust and confidence in the system.

The category manager, for example, may want to know what data was used to generate a particular report, so that they can understand the basis for the recommendations and make informed decisions. This requires a system that can provide a clear and transparent audit trail, which can be used to investigate any issues or errors that arise.

Quality data

The system depends on high-quality data to function effectively, including inspection records, non-conformance reports, batch genealogy, and customer complaints. This data must be accurate, complete, and up-to-date, which can be a challenge to ensure, especially in a large and complex organization. The data must also be properly structured and formatted, so that it can be easily accessed and analyzed by the system.

The quality control team, for example, may use the system to analyze the inspection records and identify trends or patterns that could indicate a problem with the production process. This requires a system that can handle large volumes of data and provide fast and accurate analysis, which can be a significant challenge to implement and maintain.

Changes to defect tracing and CAPA records

The system can significantly change the way that defects are traced and CAPA records are maintained, by providing fast and accurate analysis of the data and identifying the root cause of problems. This can help to reduce the time and effort required to investigate and resolve issues, and improve the overall quality and reliability of the products. The system can also help to identify potential problems before they occur, by analyzing the data and identifying trends or patterns that could indicate a problem.

The quality manager, for example, may use the system to analyze the data and identify the root cause of a particular defect, and then use that information to update the CAPA records and implement corrective actions. This requires a system that can provide fast and accurate analysis, and integrate with the existing quality management systems and processes.

Measurement and evaluation

The effectiveness of the system can be measured and evaluated using a range of metrics, including first pass yield, defects per unit, and time to root cause. These metrics can provide a clear and objective measure of the system's performance, and help to identify areas for improvement. The metrics can also be used to compare the performance of different production lines or areas of the plant, and identify best practices and areas for improvement.

The quality control team, for example, may use these metrics to evaluate the effectiveness of the system and identify areas for improvement, and then use that information to implement changes and improvements to the production process. This requires a system that can provide fast and accurate analysis, and integrate with the existing quality management systems and processes, and if you need help with implementing such a system, you can contact us for more information.

Limitations and exceptions

The system is not a panacea, and there are certain limitations and exceptions that must be understood and taken into account. For example, the system may not be suitable for very small or simple production processes, where the costs and complexity of the system may outweigh the benefits. Additionally, the system may require significant changes to the existing quality management systems and processes, which can be difficult to implement and maintain.

In these cases, a more traditional approach to quality management may be more suitable, and the system may not be the best choice. It is therefore important to carefully evaluate the needs and requirements of the organization, and consider the potential benefits and limitations of the system before making a decision.