This inventor holds 1 USPTO granted patent and 1 EPO patent. Top assignee: Maillefer Extrusion Oy. Active years: 2025.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2025
Title: Samppa Orhanen: Innovator in Fiber Optic Cable Quality Prediction
Introduction
Samppa Orhanen is a notable inventor based in Vantaa, Finland. He has made significant contributions to the field of fiber optic technology, particularly in the area of quality prediction during the manufacturing process. His innovative approach utilizes machine learning to enhance the quality assurance of fiber optic cables.
Latest Patents
Samppa Orhanen holds a patent for a method titled "Machine-learning-based quality prediction of manufactured fiber optic cable." This invention focuses on monitoring the quality of loose tube fiber optic cable during its manufacture in a secondary coating line. The method involves maintaining a trained machine-learning algorithm that calculates expected values of quality metrics based on production process parameters. The computing system monitors these parameters in real-time and outputs expected quality metrics to a user device, ensuring high standards in fiber optic cable production.
Career Highlights
Samppa Orhanen is currently employed at Maillefer Extrusion Oy, a company known for its expertise in extrusion technology. His work at Maillefer has allowed him to apply his innovative ideas in a practical setting, contributing to advancements in manufacturing processes.
Collaborations
Throughout his career, Samppa has collaborated with talented individuals such as Janne Harjuhahto and Jussi Hanhirova. These collaborations have fostered a creative environment that encourages innovation and the development of cutting-edge technologies.
Conclusion
Samppa Orhanen's contributions to the field of fiber optic technology through his innovative patent demonstrate his commitment to improving manufacturing quality. His work continues to influence the industry and showcases the potential of machine learning in enhancing production processes.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile