By prioritizing improvements in end-to-end yield, semiconductor companies can better manage cost pressures and sustain higher profitability. The path forward involves a shift in mindsets as well as the deployment of advanced analytics solutions.
As we progress into the digital era, semiconductor manufacturing competition is intensifying, with industry players looking to make productivity improvements while undertaking a record level of M&A activity. Front-end fabs and back-end manufacturers have typically focused transformational improvement efforts on direct and indirect labor-cost reduction, overall equipment effectiveness and throughput increases, material consumption, and cost reductions, and global procurement and spending adjustments. Although lean techniques have been the standard method of achieving productivity gains, many companies—particularly back-end manufacturers—have difficulty sustaining lasting impact. Our experience working in Asia shows that a differentiating factor to effectively manage increasing cost pressures and sustain higher profitability is improving end-to-end yield—encompassing both line yield (wafers that are not scrapped) and die yield (dice that pass wafer probe testing).
Yield optimization has long been regarded as one of the most critical, yet difficult to attain goals—thus a competitive advantage in semiconductor operations. According to the Integrated Circuit Engineering Corporation, yield is “the single most important factor in overall wafer processing costs,” as incremental increases in yield significantly reduce manufacturing costs.
1 In this regard, yield can be viewed as being closely tied to equipment performance (process capability), operator capability, and technological design and complexity. Over the years, advances in fab technology such as more efficient air-circulation systems and better operator capabilities, as well as efforts to lessen direct human contact with the production process through the use of automation, have led to a decline in particulate problems.
2 And yet many semiconductor players struggle to implement sustainable yield improvements due to ingrained mindsets, an insufficient view of data, and isolated efforts as well as a lack of advanced analytics capabilities.
As devices continue to get smaller and more sophisticated, the effects of Moore’s law—that is, the estimation that the number of transistors in a given chip doubles every two years—will continue unabated. Thus in the semiconductor industry, the risks to yield due to process variability and contaminations are ever-increasing, as is the importance of continuously improving design and machine capabilities. In this paper, we describe a new approach to changing mindsets, gathering the right data to inform improvement initiatives, and achieving sustainable yield increases through systemic improvements. We also offer an overview of the impact that advanced analytics can have on semiconductor yield and highlight seven capabilities that semiconductor players can pursue to inform their efforts.
Current perspectives on improving yield
Much has been discussed around the advent of Industry 4.0 tools to improve yield across front-end and back-end manufacturers. Yet without even entering that stage of technological maturity, most semiconductor players still seek to understand yield data by focusing on excursions, percentage, or product—or a combination of the three.
A percentage focus involves a bottom-up approach toward viewing yield percentages, either as an integrated view or by specific process areas. This information is typically highly dependent upon the accuracy of the data captured by operators and made readily available for engineers through manufacturing execution systems.
Some manufacturers focus on a specific set of products or product families, either by highest volumes or lowest yield performances. Resources are then assigned to solve the root causes of specific product problems, as a means of prioritizing the company’s efforts. This approach requires engineering resources from cross-functional teams, such as equipment, process, product, quality, testing, and, of course, yield.
Excursion—that is, when a process or piece of equipment moves out of preset specifications—can be a significant contributor to yield loss, particularly if it goes undiscovered until after fabrication. An excursion focus can thus be defined as tackling the highest and most obvious sources of yield loss or excursion cases identified from past historical occurrences either in the plant or from customer incidents. The key focus is to ensure the root causes of those yield losses and their potential failure modes are addressed to avoid a repeat occurrence.
These approaches can enable manufacturers to capture, monitor, and control various forms of yield losses—but they may leave other opportunities on the table. To target the highest impact on profitability, semiconductor companies must first translate yield loss into actual monetary value (rather than simply volumes or percentages), enabling them to more effectively direct resources toward solutions across all products and processes. This approach goes beyond a yield-loss focus on specific products or excursion cases to encompass a more end-to-end view. As a result, semiconductor companies can more effectively implement systemic process changes and, particularly given the different cost structures for each product, result in significant and as yet unrealized cost savings.
A new approach to semiconductor yield improvements
To translate yield loss into actual monetary value, a semiconductor company must begin by aligning the language and data used by engineering and finance to gain a better understanding of end-to-end yield. Next, it can use a loss matrix to develop a holistic view of the company’s greatest sources of loss then it can use that data to design more targeted initiatives that will have the biggest impact on increasing yield—and thus on improving the company’s bottom line.
Align the language and data of engineering and finance
In our experience with semiconductor manufacturers, there is a consistent disconnect between the engineering and finance functions. Engineers focus on and celebrate gains in percentage yield, but they often overlook the connection between yield and cost. Indeed, the celebrated percentage increases may or may not lead to any significant impact on the bottom line. Furthermore, many engineering and finance functions use different systems to track yield, which can result in constant disagreements or misalignment between the functions, rendering data less usable by the lack of agreement about which to use as the source of truth.