Programming (MATLAB, VB, etc..), Dashboard Design, all engineering majors are welcome to apply; computer science, computer engineering, mechanical or industrial engineering students are preferred.
Aeronautic industries have limited resources to optimize surveillance of suppliers. As a result of that constraint, they can only audit a limited amount of suppliers during certain periods of time. The problem with choosing audits’ frequency in this manner is that those risks that the company takes with the material/parts they supply are not taken into account. They neither combine such risks with quality ratings, compliance with standards such as ISO, corrective actions request, etc. Therefore, a methodology that will take into account and combine all these factors was needed in order to allocate enough future resources to audit each supplier. Such methodology is called as “Predictive Quality Management Approach.” The main objective of the “Predictive Quality Management Approach” project is to develop a data-driven risk assessment of suppliers and to determine surveillance frequencies based on computational intelligence. Deliverables will be focused on a recommendation of set surveillance frequencies for each supplier based on risk and the approach for future resource allocation.
The main objective of this proposed project is to be able to develop an effective predictive quality management approach to evaluate supplier’s performance particularly to significantly reduce the cost of poor quality related to suppliers in aeronautic industry. The proposed approach will conduct a risk assessment of current suppliers and determine surveillance frequencies.
The approach that will be used during the research is: