Bachelor and Master Theses

Problem description:

To the trained eye gear measurements give, in addition to numerical measurements relating to specific tolerances, a rich amount of information about the condition of the workpiece and process. However, the qualitative and highly experience-based nature of the measurements make analyses of trends and patterns difficult. The vision of this study is to bridge this competence gap and, crucially, enable further exploration of statistical phenomena in the quality of the produced parts.

Overall objective:

Provide the Quality Department with advanced statistical analysis of gear measurement data to enhance quality control, identify key deviations, and improve overall production standards.

Research questions:

-Is the current PDF format of the gear measurement protocol adequate for a thorough analysis?

-If the data is insufficient, what additional formats or data sources are required?

-Can deviations in gear quality be effectively classified and categorized to improve quality control?

Evaluation metrics:

-Accuracy and completeness of extracted data from gear  measurement protocols.

-Effectiveness in identifying and classifying deviations in gear quality.

-Improved decision-making for quality control based on statistical findings.

-Time efficiency in automating data extraction and summarization.

Envisaged solution:

Develop a script capable of automating the extraction of key data from gear measurement protocols, summarizing critical quality factors (such as tolerances and deviations) to streamline quality assessments and reporting. 

Some experience with data analysis software.

Students are expected to work both remotely and on site at Leax facility in Köping.

Leax Mekaniska