Dr. Michael Himmelhaus Profile

Dr. Michael Himmelhaus

Founder at NanoBioAnalytics

SPIE Involvement:

Author

Publications (6)

Proceedings Article | 5 October 2016 Paper

To repair or not to repair: with FAVOR® there is no question

Anthony Garetto, Kristian Schulz, Gilles Tabbone, Michael Himmelhaus, Thomas Scheruebl

Proceedings Volume 9985, 99851Q (2016) https://doi.org/10.1117/12.2243620

KEYWORDS: Manufacturing, Reliability, Tolerancing, Image processing, Image enhancement, Error analysis, Inspection, Image analysis, Back end of line, Neodymium

Read Abstract +

In the mask shop the challenges associated with today’s advanced technology nodes, both technical and economic, are becoming increasingly difficult. The constant drive to continue shrinking features means more masks per device, smaller manufacturing tolerances and more complexity along the manufacturing line with respect to the number of manufacturing steps required. Furthermore, the extremely competitive nature of the industry makes it critical for mask shops to optimize asset utilization and processes in order to maximize their competitive advantage and, in the end, profitability. Full maximization of profitability in such a complex and technologically sophisticated environment simply cannot be achieved without the use of smart automation. Smart automation allows productivity to be maximized through better asset utilization and process optimization. Reliability is improved through the minimization of manual interactions leading to fewer human error contributions and a more efficient manufacturing line. In addition to these improvements in productivity and reliability, extra value can be added through the collection and cross-verification of data from multiple sources which provides more information about our products and processes. When it comes to handling mask defects, for instance, the process consists largely of time consuming manual interactions that are error prone and often require quick decisions from operators and engineers who are under pressure. The handling of defects itself is a multiple step process consisting of several iterations of inspection, disposition, repair, review and cleaning steps. Smaller manufacturing tolerances and features with higher complexity contribute to a higher number of defects which must be handled as well as a higher level of complexity. In this paper the recent efforts undertaken by ZEISS to provide solutions which address these challenges, particularly those associated with defectivity, will be presented. From automation of aerial image analysis to the use of data driven decision making to predict and propose the optimized back end of line process flow, productivity and reliability improvements are targeted by smart automation. Additionally the generation of the ideal aerial image from the design and several repair enhancement features offer additional capabilities to improve the efficiency and yield associated with defect handling.