An Integrated Framework to Reduce Time to Market for MEMS/NEMS Developments

Abstract

Innovative products based on micro and nanotechnologies (MNT) have made rapid improvements in terms of functionality, cost and performance. Several developments based on these technologies have already benefited society greatly. However, many applications and devices based on these systems are still in the research phase, struggling to reach the commercial stage. The ultimate goal of our research work is to develop a new methodology that reduces the time to market for MNT based products. The first research methodology used as part of our work is based on prescriptive research to investigate the current state of affairs of the micro and nano electro-mechanical-systems (MEMS/NEMS) industry to identify, synthesize, and tie together different perspectives regarding MEMS/NEMS development. By doing this, it was possible to identify the main bottlenecks in the process and define a more specific objective: To develop a new methodology that allows MEMS/NEMS designers to expedite the design and fabrication stages for devices based on those technologies. The second research methodology used is based on descriptive research to propose an algorithmic methodology to assist some of the main problems for the MEMS/NEMS industry. A modular knowledge based system was conceived, where different managerial and technical tools are used. We developed a standardized language to define manufacturing steps required to fabricate and prototype MEMS devices based on an international standard: ISO 18629. We also developed a hierarchical structure based on object-oriented principles to define new taxonomic levels of abstraction for MEMS processes, providing a generic, but at the same time, comprehensive, and flexible structure. Another important part of our research work was the development of mathematical models to evaluate potential alternatives for MEMS manufacturing process. Many of the manufacturing processes for MEMS are new variants of semiconductor processes or totally new processes. Because of this, there is very little statistical information which can be used to evaluate alternatives. We developed mathematical models using fuzzy inference systems to evaluate potential alternatives in an efficient way, effectively reducing the MEMS/NEMS development time and impacting positively the time to market for these developments.