Quality via a system intelligence methodology


Quality via a system intelligence methodology


In the industry there is a need for guaranteed quality under all conditions. Both in mechatronic products, in production processes as in assembly lines. Unfortunately, failures happen and pre-established requirements are not met as a consequence of:

  • Yet undiscovered intra cycle conditions (e.g. environmental conditions);
  • A sequence of inter cycle conditions (e.g. accumulation of errors);
  • Time degradation of the system over cycles.

The technological barriers we encounter are:

  • Detect: The difficulty of obtaining the relevant data of scarce events with numerous and various inputs/parameters;
  • Predict: The absence of a framework to understand and quantify how conditions lead up to a quality degradation (e.g. failure event);
  • Mitigate: The absence of an explainable decision support tool to define and evaluate on-and offline mitigation strategies.

Project goals

With this project we want to deliver:

  • A strategy to collect relevant data and information available on the machine or production/assembly system affecting quality;
  • A hybrid probabilistic representation based on physical knowledge/models, product/production specific knowledge, and data-driven models;
  • An intelligent and efficient probing strategy on both the virtual and actual machine or production/assembly system;
  • An explainable decision support tool that is actionable, answering to the barriers by defining detect, predict and mitigation strategies to increase quality.


QUASMO is a Strategic Basic Research (SBO) project. We are looking for companies to join the User Group and work with us on the valorisation of the project.

Interested? Complete the form below and we will contact you as soon as possible.