Developing MEMS for Volume Manufacturing, Part One



What methodologies and best practices bring about effective commercialization of a MEMS device?

Editor’s Note: In the first of a three-part series, the authors survey the MEMS volume manufacturing landscape, introduce the concept of translational engineering, and name four characteristics a prototype must possess to show manufacturing readiness. The second article in the series will cover designing for testing and data gathering as well as for package and system integration, with the concluding article offering guidance on fabrication of advanced prototypes and on the process of transfer to the foundry.

Adapted with permission from Translational Engineering: Best Practices in Developing MEMS for Volume Manufacturing[1]

From Research Project to Commercial Product
Aiming to advance technology and knowledge, academics invent MEMS devices. When market opportunities appear, a new goal arises: commercializing the technology. However, the initial prototype was never engineered to meet this new goal. Before a new MEMS device can be commercialized, it must be reengineered and adapted for the volume manufacturing environment. We address these reengineering and volume manufacturing issues by introducing “translational engineering,”  a method we developed over the past 15 years and more than 160 client projects.

Many new MEMS devices, whether sensors, actuators, or passive microstructures, are invented and initially developed in a university or a government-sponsored laboratory. In that setting, researchers focus on demonstrating new physics of operation or enhancing performance capabilities using new materials and methods. Then comes the first “proof of concept” prototype. The researchers create these prototypes using the tools available within their own laboratory, typically much older models that have been donated or purchased used. Often, because of limited equipment or budget, manual fabrication steps may be used. In a research project, a successful prototype is defined as one that provides sufficient insights and data for the publication of a peer-reviewed journal article, so these fabrication limitations are acceptable.

MEMS (or semiconductor device) research often inspires entrepreneurial ambitions, and many new companies have been formed on the basis of a founder’s Ph.D. dissertation. However, one cannot simply send a successful research prototype straight to a foundry for commercial manufacturing. A research prototype developed solely for academic purposes has several deficiencies for commercial manufacturing:

  1. The relationship between process tolerances and device performance is not yet fully understood.
  2. The process may involve the use of machines, materials, or methods not commonly available in production facilities.
  3. The design and process have not yet been optimized for items crucial to a commercial product, that is, packaging, testing, high yield, and low cost.

Successfully commercializing technology created in a research environment requires specially focused development work. Sometimes referred to as “design for manufacture,” this effort is one we call “translational engineering,” because the original intent of the inventors must be interpreted and translated into a design that can be manufactured in volume (thousands to millions or billions of units per year). This work is needed for MEMS especially because the design and fabrication process of a MEMS device are heavily interdependent. Small design changes will impact the process flow and vice versa. Depending on the complexity of the device design and its process, translational engineering can span years and consume millions of dollars before commercial production can begin. It is a necessary and unavoidable step in MEMS development. Many MEMS startups have failed because developers and other stakeholders substantially underestimated the time and funds that translational engineering demands.

Manufacturing Environment Economics
The goal of translational engineering is to deliver a MEMS design and process flow to a production fab for manufacturing. To sharply focus such development efforts, one must first understand and appreciate the volume manufacturing environment.

Wafer fabrication facilities (“fabs”) are complex factories whose construction costs a minimum of $100 million for MEMS production and a minimum of $2 billion for state-of-the-art semiconductor production. These costs, and significant recurring operating costs, can only be justified by operations focused on high manufacturing throughput, 24/7 operation, and equipment utilization rates as close to 100% as possible.

Foundries (contract manufacturing fabs) therefore seek customers who will buy large quantities of wafers per year. Minimum order quantities of 5,000 wafers per year are common for high-volume MEMS foundries producing 200-mm-diameter wafers. Even smaller foundries, producing 150-mm-diameter wafers, may require minimum order quantities of 500 wafers per year, with 100 wafers per year being a typical minimum.

Fabs typically run dozens of different products. In some cases, fabs run both CMOS (semiconductor) and MEMS products, each of which have distinct process flows, through the same facility. Managing so many groups of wafers moving along different paths through the fab and keeping the tool utilization high require complex and detailed tool scheduling. Each tool will have a queue of wafer batches waiting their turn. Disruption of that queue or the tool (for example, to conduct experiments) will cause cascading schedule problems. Owing to this complex operating environment, fabs strongly favor producing MEMS that will be compatible with their existing tools and processes.

The foundry business model demands the selection of customers having the lowest risk processes at the highest possible profit margin in order to derive the most profit possible from the fixed production capacity of a facility. While a foundry might consider, for strategic reasons, accepting a customer with a new type of design or process, the foundry will very likely charge higher prices to compensate for the anticipated disruptions to its existing operations. Any development work undertaken by the foundry requires special attention from foundry engineers, which will be charged to the customer (as nonrecurring engineering fees). The foundry will also want to retain rights to any new process intellectual property (IP) developed. If a customer’s process is deemed too early stage or too different from core processes, the foundry will likely decline the business outright.

With an understanding of the foundry business model just described, one can better appreciate that a proof-of-concept prototype is too fragile to go straight to a production facility. The translational engineering work to be carried out must be focused on ruggedizing the technology for the demanding production environment; the MEMS design and process flow must be engineered to require a minimum of human intervention during fabrication, have process tolerances that are comfortably met by existing fab equipment, and for each process step, have well-defined pass/fail criteria, which can be easily inspected using common metrology equipment.

In summary, a totally new prototype must be designed and built. This advanced prototype is what will eventually be transferred to a foundry for production.

Preparing for Manufacturing
The advanced prototype demonstrates readiness for manufacturing. In addition to the functionality demonstrated by the earlier proof-of-concept prototype, an advanced prototype must also have the following new attributes.

  • A model of how process tolerances affect device performance
  • A process flow and mask layout that can be executed in a production fab
  • A design that considers downstream packaging, testing, and system integration needs
  • A fabrication cost that allows adequate profit when sold in a given market

Designing Advanced Prototypes

Developing Parameter Sensitivity Models
A device technology is not fully mature nor manufacturable until one understands how all process parameters contribute to its proper function. In other words, how sensitive is the device performance to variation in each process step? Knowing the parameter sensitivities enables both implementation of inspection on that process step and establishment of pass/fail criteria to screen out wafers whose process variations will cause device failure.

For example, film thickness is one of several parameters that affect the stiffness of a membrane device and its resonant frequency. How thick or thin could that film be before the variation in stiffness impairs overall device performance? Membrane stiffness is proportional to the cube of film thickness. If the required device performance depends on controlling membrane stiffness to within ±10%, then the film thickness must be controlled to within +3.2 and −3.5% (the cube roots of 1.1 and 0.9, respectively). If a deposition tool cannot repeatedly perform within those thickness tolerances, then the process will depend on luck (random
variable) to achieve the correct film thickness and will therefore have poor yield.

Exploring and understanding parameter sensitivities is best done using simulation. The simulation environment allows one to explore the interaction of many design parameters much faster and more cost effectively than by building and measuring actual devices.

First, an adequate model of the device physics must be created. The model does not require precise material properties data nor does it need to look exactly like the finished device; it must, however, capture the fundamental physical behaviors of the device. At this stage of the development, we seek to understand how relative changes in input variables affect device performance, not to calculate absolute values with precision.

Often, a lumped parameter model (such as the equations for a mass-spring-damper system) is sufficient to elucidate the sensitivity to major process variables. Such a model could be implemented on an Excel spreadsheet or a Matlab script and used to quickly identify the most sensitive parameters and their approximate range of acceptable tolerances. Once first-order behaviors and sensitivities are well understood, then a more advanced model could be created by finite element analysis (FEA) simulation to study the subtler parameter interactions. For example, FEA is well suited to explore interactions with 3D geometries. FEA models an be time-consuming to build and verify, so engineering judgment must always be applied to determine the appropriate level of detail in a model. The ideal FEA model contains only enough features to correctly simulate the critical physical behavior and no more.

Data and insights gained from parameter sensitivity modeling must inform process integration and design layout. Typically, several iterations are needed between modeling and process integration before convergence to an advanced prototype design.

Process Integration and Mask Layout for Manufacturing
Designing an advanced prototype requires creating a process and mask layout that can eventually be executed by a production fab. The following factors are important when translating a proof-of-concept design.

  • Selecting processes compatible with those at production fabs
  • Engineering the device design to function within reasonable process tolerances
  • Having clear prototype performance goals in order to guide process and design trade-offs

For smooth commercialization, it is essential to create an advanced prototype using processes commonly found in production fabs. Any chemicals, photoresists, or tools needed for the process must already be commercially available. Processes should not require individual wafer-by-wafer tuning, nor any manual steps. All materials and chemicals must be compatible with the types of foundries to which the product could eventually be transferred. For example, if the likely manufacturer will be a CMOS foundry, then materials such as gold or processes such as KOH etching, both of which contaminate CMOS devices, cannot be used.

Even with processing of very large volumes of wafers under stable conditions, all manufacturing processes have some random variation that will cause a plus or minus tolerance on dimensions and material properties. An advanced prototype design must be engineered to work within the limitations of available processes. This requires a deep understanding of how typical manufacturing processes perform and then creating a design that can accommodate those process imperfections. Creating designs that can succeed within typical process tolerances will maximize the selection of candidate foundries, which in turn will help get competitive pricing for volume manufacturing.

When developing an advanced prototype, the goal should not be perfect performance but making sure the device will function. There might be one step where tight process tolerances may be required, but it is always worth considering if sacrificing a certain performance will allow a wider tolerance and therefore a higher overall chance of creating a working device. Test data from an imperfect device is useful for tuning the models and the design as well as for identifying further process optimization. A second, subsequent prototype could always be used to further improve the design and process. The opportunity to learn is greatly diminished if a prototype fails to demonstrate even basic functionality.

Interactions and tolerances between the registration of different mask layers must also be carefully considered. The results of this analysis will eventually help to establish design rules for future device design. Minimum linewidth or spacing between the features on each layer is defined by the lithography variation and etch accuracy. The minimum overlap or spacing required between layers is defined by a combination of lithography variation and layer-to-layer alignment accuracy of the exposure tool.

Typically, misalignment errors and lithography variations are considered to be normally distributed random errors. This enables one to calculate an overall expected error from accumulated tolerances by adding the sum of the squares of each contributing error and then taking the square root. An advanced prototype’s layout should reflect a realistic lithography error “budget.”

In MEMS, process and design are inseparable. While considering trade-offs between the two, the big picture in business and technical goals must always guide engineering choices. Whether the technology is being commercialized by a startup company or a Fortune 500 company, prototypes must always demonstrate capability in order to be further funded. As different processes or designs or layouts are considered, they should be evaluated and guided by the goals of what the prototype must eventually demonstrate. Choices should always be conservatively made to ensure that it will be possible to yield some working prototypes, even if they have less-than-ideal performance. An overly ambitious, high-risk prototype that is designed idealistically for a perfect outcome but ultimately fails to work in practice is much less useful.


The authors are employed by A.M. Fitzgerald & Associates, LLC (www.amfitzgerald.com), a MEMS product development company located in Burlingame, CA, USA. Corresponding author email: amf@amfitzgerald.com

 

 

 

[1] Sensors and Materials, Vol. 30, No. 4 (2018) 779-789 MYU Tokyo

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