EDA Applications and Benefits for Smart Manufacturing: Introduction to a New Series

With the adoption of the latest SEMI EDA (Equipment Data Acquisition, also known as Interface A) standards accelerating significantly over the past 18 months, it is time to highlight the applications across the industry that make the best use of these standards, and the specific manufacturing benefits that result.

The articles in this series are not simply suggestions of what one could do by leveraging the performance, flexibility, and architectural features of these standards. Rather, they are leading edge application-specific mini-case studies derived from actual production experience, and as such, can provide genuine guidance for those companies just now contemplating potential pilot projects or even factory-wide deployments of the EDA standards.
Another important aspect of this series is that the applications described affect a broad range of stakeholders in a semiconductor manufacturing company. These include, of course, the process control engineers and statistical modeling support staff responsible for the Fault Detection and Classification (FDC) implementation strategy in all modern wafer fabs, since this application has consistently been the initial consumer of the high-density, precisely framed equipment/process data and associated context information provided through the EDA interfaces.

However, other direct beneficiaries of EDA-enabled applications extend well beyond this group, and include:

Industrial engineers responsible for monitoring equipment and factory throughput in real-time, identifying opportunities to eliminate wait time waste in individual equipment types as well as the overall factory, and addressing bottlenecks as they shift and emerge;
Production control staff responsible for determining the material release schedule and managing the factory scheduling/dispatching systems to accommodate changes in customer orders and/or factory status;
Equipment engineers responsible for fleet matching and management to minimize or eliminate the need to dedicate certain equipment sets for critical process steps and thereby simplify the overall factory scheduling process;
Maintenance engineers responsible for minimizing equipment downtime, MTTR (mean time to repair), and test wafer usage required to bring equipment back to production-ready state;
Facilities engineers responsible for collecting and integrating sub-fab data from pumps, chillers, exhaust systems, and other complex subsystems into the production data management infrastructure for use by a growing range of analysis applications;
Sensor integration specialists responsible for supplementing the built-in sensing and control capabilities of critical process and measurement equipment to support advanced process development…

… and the list goes on. EDAApplications_1.1.png

Despite their diversity, these application articles all share a common profile, which includes a statement of the manufacturing problem addressed; a description of the major solution components required; a discussion of how the solution leverages specific, unique characteristics of the EDA standards; and finally, identification of the key ROI (return on investment) factors that are impacted by the solution. In addition, where available, example ROI calculations will be provided so that the readers can adapt them to their own company environments to quantify the potential benefit of implementing a comparable application solution.

From the above description, you may be tempted to assume that the series focuses mostly on the careabouts of semiconductor manufacturing companies (IDMs and foundries)… but this is not the case. Since the performance of the highlighted applications depends heavily on the “quality” (for lack of a better term) of the equipment interfaces supplying the data, the equipment suppliers have a major role to play in achieving the promised benefit. Specifically, the metadata models (specified by SEMI E120, E125, and E164) that define the parameters, states, events, exceptions, and other data available from the equipment and structure this information for external access essentially form the data collection “contract” between the equipment suppliers and their factory customers. For this reason, the detailed requirements for this aspect of the EDA implementation must be carefully specified and negotiated. This will not happen overnight, as the implications for future equipment design are significant.

As a number of industry experts have already expressed, it is an exciting time to be in the semiconductor industry, regardless of your position along the value chain. For those involved in the collection and use of equipment data to optimize factory performance, we hope you will find the coming series of articles especially useful in formulating you own company’s EDA implementation roadmap.