About optawa
What do we do?
Manufacturing companies lose time and money due to tool failures, scrap, and inefficient machining. Machine tool breakage is especially impactful, accounting for around 20% of total downtime, and 3-12% of total machining costs are due to tool costs.
We provide a web-based software that uses machine learning to analyze machining data and predict machine tool wear or breakage. The platform delivers data-driven recommendations that empower customers to identify machine issues with confidence, replacing hunch-based discussions with informed decisions that optimize machine tool usage and boost production performance.
Our solution helps manufacturers reduce unexpected stops, scrap, and machine tool costs, leading to higher productivity and profitability. By optimizing machine tool usage, companies can extend machine tool life and make better use of their machines and materials. The result is a more efficient, predictable, and sustainable production process that quickly delivers measurable financial benefits.
Meet the Team
A dedicated team of Computer Science engineers from KTH Royal Institute of Technology.
As a final-year MSc student in Computer Science specialising in Data Science at KTH, I bring a unique perspective that bridges advanced data analytics with hands-on industrial expertise. My background includes four years of championship-level competition in CNC-milling, including the Swedish national championships, Euroskills, and Worldskills. This practical experience with complex manufacturing processes provides me with a rare insight into the real-world systems.
My ongoing Master's studies in Applied and Computational Mathematics help in bridging the gap between raw machining data and insights that benefit customers. In combination with my professional experience in software enginering, I bring knowledge which benefits both the software development and mathematical modeling aspects of our project.
As a final-year MSc student in Computer Science specializing in Visualization and Computer Graphics, I deliver the link between our advanced predictive models and the end-user. My expertise will help transform complex data analysis into intuitive, dynamic visualizations on the web platform, making tool-break predictions immediately clear and actionable.