Artificial Intelligence and Quality: the value in business processes

The Artificial Intelligence applied to Quality is transforming the way companies manage information, complaints and Non-Conformities. In manufacturing contexts, many reports still arrive as unstructured data, such as emails or informal communications, which require time to be analysed and integrated into company systems.

The introduction of AI in Quality Processes makes it possible to rapidly transform this information into structured data, making Problem Solving more efficient and facilitating access to historical data. In this way, organisations can improve control of the Quality System and respond more quickly to the root causes of anomalies.

Artificial Intelligence applied to Quality in complaint management

One of the areas in which Artificial Intelligence applied to Quality finds application is complaint management. When a report arrives via email or informal communication, the information it contains is often incomplete or unstructured.

AI makes it possible to automatically analyse the content of the report and generate a complaint in the system. In parallel, the system can consult available historical data to identify any precedents related to the same item or the same customer.

This approach makes it possible to reduce manual data entry activities and gain a more complete picture of the situation from the earliest stages of analysis. The Quality team can therefore start investigation activities more quickly, reducing the time needed to understand the context of the problem.

Support for root cause analysis with Artificial Intelligence applied to Quality

After the complaint has been recorded, the next step is to identify the root cause of the Non-Conformity. This phase often requires analysis of data from multiple sources and the comparison of different pieces of information.

The Artificial Intelligence applied to Quality can support this process through intelligent systems capable of guiding the user throughout the investigation. By analysing historical data and available information, the system can suggest useful insights and help narrow down the origin of the problem.

In some cases it is possible to determine whether the Non-Conformity is related to an internal process or to Supplier Qualification, helping the user in classifying the event and collecting the information necessary for managing Corrective Actions. This support makes the analysis more structured and facilitates the decision-making process in Quality Processes.

Artificial Intelligence applied to Quality and process digitalisation

The Artificial Intelligence applied to Quality represents an important step in the journey towards the Digitalisation of Business Processes. Beyond data analysis, AI can also support operational activities such as the automatic generation of control plans from technical drawings or the collection of data directly in Production.

In production and Testing contexts, for example, the use of voice commands makes it possible to record a Non-Conformity without interrupting operational activities. At the same time, rapid access to data makes it possible to consult information on items, suppliers or Testing units in real time.

In this scenario, the ability to integrate data, documents and Processes becomes increasingly strategic in reducing the Costs of Non-Quality and increasing efficiency of the Quality System.

This journey also includes the experience of Impresoft, a group that accelerates the digital transformation of companies through four specialised competence centres. Among the group’s companies is Blulink, which develops solutions for the management of Business and Quality Processes, including the platform Quarta EVO, designed to support the Digitalisation of the Quality System and the integrated control of Processes.