New generation process control solutions for the solar industry

New-Generation Process Control Solutions For the Solar Industry Deploying Comprehensive, Company-wide Data Collection, Feedback & Realtime Control Methods to Improve Manufacturing Performance and Lower Costs

By David Kallus and Guillaume Hennion, KLA-Tencor Corporation

Overview Solar electricity generation is playing an increasingly important role in the global move toward more environmentally friendly energy sources. With photovoltaic (PV) devices being the fundamental building blocks in the solar revolution, achieving high-quality, high-volume PV manufacturing is a key element for success. Many of today’s advanced inspection platforms that have evolved through decades of deployment in semiconductor IC manufacturing have been successfully adapted for use in PV manufacturing.

However, unique process control challenges exist in the PV segment due to the high volumes, fast processing times and huge amounts of optical image data that can be generated from inspection tools throughout the production floor. These challenges require comprehensive analysis methods that go beyond individual “on-tool� approaches by aggregating, organizing and analyzing plant-wide information to support real-time decisions and corrective actions.

For example, a solar plant running at 1 gigawatt capacity generates over 300 million units per year, which means that undetected process errors can put large amounts of material at risk in a relatively short time. Therefore the time required for error detection, root cause identification and corrective action is critical for achieving the yields and efficiency goals to meet cost-per-unit requirements and to support rising market demand.

This paper provides an overview of these process control challenges and introduces FabVision Solar, a new integrated data collection and defect analysis software solution that is specifically designed to address the special needs for comprehensive, plant-wide visibility and process control in high-volume PV manufacturing environments.

Trends and Driving Factors Pressure on Reducing Price-per-Watt to Achieve Grid Parity A primary driving goal in the solar electricity industry is the achievement of grid parity, which represents the tipping point when the cost of solar equals the cost of conventional

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methods of generating electricity. As the average price-per-kWatt for conventional methods continues to rise and the price of solar is driven downward, the general industry consensus is that grid parity will be achieved and then solar adoption rates will accelerate even faster. In practical terms, the achievement of grid parity is happening at different rates for various countries throughout the world, with a few regions already at parity and most working toward it. While some countries have used government subsidies to spur solar adoption, these incentives are inherently temporary and therefore continuous cost reduction is necessary.

True grid parity will only be achieved through the continuing reduction in the unsubsidized price-per-kWatt of solar generation methods. As shown in Figure 1, the ongoing experience curve for photovoltaic (PV) manufacturing and the demand for higher production volumes are steadily driving down the cost of solar modules toward the point where solar will have a clear price advantage without any subsidies or incentives.

Figure 1 – Photovoltaic cell manufacturing experience curve is driving down costs

Yield and Efficiency Improvements are the Keys to Success The ability to drive up yields and efficiency for PV manufacturing will be one of the critical factors for driving down the cost of solar to achieve grid parity. Continuous improvement of manufacturing efficiency is the next key step for the industry, in conjunction with scaling up production and technology improvements. Maximizing productivity will be essential for companies to maintain competitiveness and to capture market share by satisfying the accelerating demand for solar cells, which will grow exponentially after the grid parity tipping point has been surpassed.

Achieving sustainable success in the PV manufacturing sector will result from three key focus areas: Technology Advances, Scaling up Production, and Increasing Productivity.

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Figure 2 – Key elements needed for Yield & Efficiency Improvements (Source: Q Cells)

Comprehensive process control benefits all three of these areas by accelerating innovation and maximizing capacity potential.

Technology Technology improvements include innovations such as reducing wafer thickness, minimizing Kerf loss during sawing processes, back-side printing, different materials, etc.

For example, a 20 micron reduction in wafer thickness (from 200Âľ to 180Âľ) can result in a 7 percent cost savings. Industry estimates indicate that each 1 percent improvement in efficiency results in as much as 15 percent in cost savings for the PV manufacturing cell.

Process control accelerates innovation through faster learning.

Scaling Scaling up production also will lead directly to lower per-unit costs as the demand for solar energy drives up manufacturing volumes. It is projected that each doubling of production output will result in approximately 22 percent lower per-unit costs. The creation of huge solar fabrication facilities is greatly increasing the economies of scale; however, at the same time these larger facilities are driving up the need for better cell efficiency management and process control methodologies.

Process control enables innovations to become manufacturable at high volumes.

Productivity Productivity improvements are aimed at lowering costs by maximizing cell efficiency.

Experience has shown that every 1 percent increase in yield can provide a corresponding 5 percent improvement in costs. As mentioned above, with manufacturing technologies changing and the scale of production escalating, the implementation of advanced process control and productivity improvement tools will be absolutely vital for achievement of lower costs by maximizing capacity potential.

Process control enables improved capacity potential through fast and deep understanding of process bottlenecks.

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Goals of Process Control in PV Manufacturing Comprehensive process management encompasses the following four key areas: • Quality Control – inspection processes that focus on “good vs. bad” decisions with the objectives of detecting errors, sorting out bad quality and checking process limits • Process Control – managing real-time production by incorporating mechanisms to stop-the-line to avoid further errors that lead to waste and scrap. Objectives include real-time measurement of production parameters, warnings, alarms and triggering of process control actions.

• Process Improvement – using error source analysis techniques to identify root causes and to initiate timely process corrections that continually raise the overall consistency and effectiveness of the production system.

• Classification and Sorting – processes that rate and categorize production output according to specific quality parameters in order to assure that devices meet specific acceptance criteria for various market categories.

Process control and defect reduction technologies have already become an integral part of the IC manufacturing industry through a multi-generational evolution of inspection platforms, data analysis software and process management disciplines. These mature process control technologies and concepts that have been developed over decades of experience in the semiconductor IC manufacturing segment offer a solid foundation for adapting to the needs of photovoltaic manufacturing. However, there are special challenges in PV cell manufacturing that must be addressed to assure success.

Key Process Control Challenges in PV Manufacturing High Volumes of Data One of the major challenges for process control in a PV cell production line is the high rate at which cells are being processed. With PV lines running at 1500-3000 cells per hour and a range of key process parameters that need to be addressed, the data handling and analysis requirements can be orders of magnitude above those found in IC lines. Optical inspection modules used in PV manufacturing generate huge amounts of data due to the file sizes, the amount of information and the frequency of measurement.

Fast Feedback Loops The speed at which PV cells are being processed also means that undetected process excursions can put a large number of cells at risk, often at key processing points early in the production flow so the risk of added cost to bad parts during subsequent operations is also very high. Therefore the time to detection, root cause identification and corrective action becomes extremely critical in PV manufacturing.

Root Cause Analysis Root cause analysis in PV manufacturing can be especially challenging because of the large amounts of image-oriented data, the criticality of a range of different parameters and the sometimes subtle variations that can foreshadow emerging process excursions.

As will be discussed in subsequent sections, the ability to capture and retain all wafer/cell image data and to analyze defect signatures across multiple wafers by stacking images is a key to being able to identify root causes and to spot potential excursion trends before they become major problems.

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Real-time Corrective Actions The ability to detect, analyze and correct defects and excursions when they first occur is the heart of effective process control and is essential for improving yields and reducing costs. With the high volumes of devices moving at high speeds through advanced PV manufacturing facilities, any delays in taking corrective action can result in a large number of scrap devices and significant wasted cost down the line. For example, in a line producing 1,500 cells per hour, even a short 10 minute delay in correcting a critical issue would represent a 0.7% yield loss.

FabVision Solar Technology Overview Building on decades of experience creating inspection platforms and software for the semiconductor IC and PV manufacturing industries, KLA-Tencor developed FabVision Solar to unify inspection and process control activities across the entire PV line.

FabVision Solar is an integrated, end-to-end turnkey solution for PV cell manufacturing that addresses the challenge of providing comprehensive plant-wide data aggregation, analysis and process management across potentially hundreds of production tools in new generation solar production facilities.

The FabVision software architecture is designed to help photovoltaic cell manufacturers improve production effectiveness and profitability by enabling manufacturers to centrally manage all relevant data and to react more quickly to metrology and defectivity excursions.

Key elements of the FabVision Solar software include: •

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Excursion/process monitoring (statistical process control): provides process control through in-line monitoring of all PVI-6 measurement parameters and alarms/email notifications on excursions.

Automated report generation: increases visibility into manufacturing process with time-based automated reporting and analysis of optical inspection results from multiple inspection modules across multiple fab manufacturing lines.

Detection of repeating defects and warning capabilities: enables quick reaction to excursions with configurable rules set by proximity, defect type and frequency of occurrence; and real-time alarms for email notification and on-tool warnings.

Defect signature identification using multiple wafer/cell stacking: provides means to visualize defect signatures or frequently impacted wafer/cell locations for root cause understanding and action in the production line.

Eased problem identification through wafer/cell image review: captures wafer/cell images and data from the PVI-6 and allows complete review of images complemented by eased navigation through data

End-to-End Real-time Process Control FabVision Solar leverages KLA-Tencor's ICOS® PVI-6 data through a wide range of analysis and monitoring features to provide better control and improve visibility into the

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manufacturing process. Leveraging high-speed data transfer mechanisms that are optimized for the industry-standard PVI-6 platforms, FabVision Solar enables users to review information and analyze data in real-time from any operation throughout the production line.

Figure 3 – FabVision Solar enables centralized management of the entire process flow

The ability to review inline data at any point and/or drill-down to concatenate data from multiple time periods enables process engineers to spot emerging issues, not just defects or excursions, throughout the production line. This not only improves responsiveness to problems, it actually enables a shift toward predictive actions that prevent problems.

Building a Foundation for Ongoing Process Improvement In the past, the PV manufacturing industry has relied on time-consuming manual analysis methods to find and correct defectivity issues along with an emphasis on backend sorting and classification to weed out defective parts. With the market demand driving up cell efficiency requirements, these methods are no longer sufficient.

With FabVision Solar, users can quickly identify the root cause of defects by applying production-proven defectivity and metrology methodologies from the integrated circuit and wafer markets that are designed specifically for ICOS PVI-6 tools and optimized for the solar industry.

FabVision Focus Areas & Benefits The following sections provide more detailed information on the key capabilities and benefits provided by FabVision Solar as compared with conventional approaches for process control in PV production lines.

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Comprehensive Capture & Analysis of Real-time Data Capturing and analyzing data in a timely fashion can give manufacturers valuable information for optimizing key operations within the PV production flow.

The trend charts in Figure 4 show how comprehensive data collection coupled with the ability to interactively focus in on key data segments can support proactive process control decisions. These charts track the average finger-width of lines on the front side of solar cells. The left chart is finger width over time. Although the width variation appears random in longer time duration, the zoom-in view reveals abrupt change in finger width, which correlated to screen replacement, indicating an opportunity for improving efficiency by optimizing screen replacement. There is a direct positive correlation between the finger width and cell efficiency.

Figure 4 – Interactive drill-down into key data supports real-time process control

The ability to interactively zoom into the data gives manufacturers valuable information for making process adjustments, such as altering the frequency of print screen set-up, in order to better control the consistency of finger-width and to eliminate the frequency and duration of lower efficiency episodes. Efficiency gains of even just a couple tenths of percent can have enormous ROI payback in a high-volume PV line.

By interacting directly with each of the ICOS PV-6 platforms deployed throughout the line and aggregating all of the data for the whole production environment, FabVision Solar gives manufacturers the ability to see the both big picture and the relevant detail.

By monitoring specific parameters for each station, FabVision can immediately alert operators to excursions that need correction while also alerting process managers to the higher level trends that either pose emerging problems or can offer opportunities for fine tuning the processes to improve costs.

Understanding Yield-loss Problem Areas Another important analysis area that is made possible by FabVision’s comprehensive approach is the ability to understand the relative impacts of various yield-detractors and to focus corrective actions on those areas that can have the most beneficial payoff.

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Total yield loss in today’s PV lines generally can range between 3% and 7% but the process engineer needs to drill down into the specific elements that make up total yield loss in order to begin making improvements. Figure 5 illustrates a typical distribution of yield-detractors.

The biggest reason for yield loss is wafer breakage, which can most efficiently be addressed by incoming wafer inspection focused on micro-cracks or other defects that can lead to breakage at subsequent steps. The next most frequent issue is B Quality cells, which are parts that have too many defects (such as stains or interrupts) that can lead to lower efficiency. In the past, B Quality cells could often be marketed at a lower price but in today’s market conditions B cells are not saleable so manufacturers need to put in place process control mechanisms to eliminate the conditions that lead to lower quality product. The cosmetic aspects of cells are becoming increasingly important in order to produce solar panels with uniformity of color and appearance. Even fully functional cells that have cosmetic defects are becoming much less saleable in today’s market.

Figure 5 – Increasing yield by understanding top yield-detractor issues

Identifying Root Causes of Yield Loss FabVision Solar enables process engineers to identify the various root causes that ultimately result in non-Grade A devices at the end of the process. There can be a variety of contributing factors that cause cells to fall short of Grade A parameters so it’s important to be able to drill-down into the data and understand the nature, frequency and root causes of these contributing factors.

The capability to differentiate random defects from systematic defects is also an important consideration. Root cause analysis helps operators and engineers understand where defects are entering into the process and to assess the relative impacts of various defect types, which then enables a focus on making improvements in the highest impact areas.

Figure 6 provides a Pareto analysis of the relative frequency for various contributing factors that result in non-Grade A devices in a typical PV line. By focusing on the root causes for the defects that occur most often, the process engineer can significantly improve the Grade A parts yield at the end of the line.

Prior to FabVision, this type of analysis was a manually intensive process that required collecting data from various sources, importing it all into spreadsheets and sorting

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through the data to determine relative impacts. In too many instances, by the time the corrective action resources could be focused on the high-defective root causes, thousands of non-Grade A parts could have already been created.

In contrast, FabVision Solar enables engineers to perform this type of relative Pareto analysis for contributing factors on a real-time, shift-by-shift basis so that they can immediately target their corrective action efforts where they will do the most good.

Figure 6 – Relative impacts of root cause factors in non-Grade A devices

Detection of Repeater Defects Repeater defects are problem issues that show up in the same X-Y location on multiple cells. The occurrence of such a defect on each cell may not be enough to raise a process alert but the cumulative impact of many bad cells can be very costly. For example, if a repeater defect goes undetected even for a relatively short time, such as 10-15 minutes in today’s high-volume PV production lines, it could mean hundreds of cells have been impacted by the error.

FabVision Solar has the ability to automatically spot repeater defects within just a few cells and to alert the operator to proactively take action before additional bad cells are produced. For example, as shown in Figure 7 running an ad hoc analysis with stacked image maps allows highlighting of a location with a high frequency of defect occurrence.

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Figure 7 – Stacked map of 1000 wafers highlighting the frequency of occurrence of defect locations

The next logical step is to implement a repeater calculation for the identified defect type so that is can be reacted to in real time. As illustrated in Figure 8, the FabVision software continuously monitors image data and in this instance is able to identify a repeater defect on the cell’s bus bar, raising an alert after only five cells have shown the defect. This prompts the operator to take immediate action, thereby preventing a long run of cells with the same defect from going downstream.

Figure 8 – Real-time identification and alerts for repeater defects

The FabVision software rules are configurable to enable each customer to define their own parameters with regard to what constitutes a repeater defect and thresholds for how many cells with the defect would trigger the alerts. This allows each manufacturer to tailor the system to minimize false-negatives while ensuring real-time triggering for situations that exceed their acceptable criteria.

Enhanced Analysis of Defect Signatures FabVision Solar has the ability to stack the image data for potentially hundreds of thousands of cells on top of one another and to concatenate all of the defect data. This enables operators to look at patterns such as high densities of defects in certain regions of the wafer or common defects across many wafers.

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Figure 9 illustrates a “commonality analysis” in which all of the cells from a given shift have been stacked together with the associated defect data. This visual representation supports much better decision making than sorting through reams of tabulated data. In this example, the defect circled in red shows up on 30 percent of the cells in the same location, at the edge of the bus bar. This immediately alerts the process engineer that there is likely an issue with the front-side printing process.

Figure 9 – Image stacking supports visual defect-signature analysis

Capture & Retention of Deep Data to Drive Process Improvement One of the major differences from conventional approaches is that FabVision Solar automatically captures and retains all image data generated by all of the ICOS PVI-6 platforms throughout the production line. As shown in Figure 10, the FabVision user interface enables process engineers to interactively manipulate any of the stored data to focus in on specific areas of interest, combining both statistical and image data to gain a much richer understanding of the defects and how they relate to end-of-line yields.

Figure 10 – Interactive user interface supports drill-down into any data sets

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For example, as shown in Figure 11, the engineer can interactively zoom in on statistical peaks or out-of-spec segments in the SPC charts and then pull up the associated image data for just that data set. Instead of having to wade through thousands of irrelevant instances, the engineer can quickly focus on just the images of interest. Also, if needed, the user could pull up data from multiple shifts, machines or wafer batches and concatenate the information together in order to analyze patterns that might not otherwise become apparent.

Figure 11: Example of a zoom-in and drill down from plotted finger width to correlate it with another parameter, in this case with final cell efficiency

From a process improvement perspective, the ability to access and manipulate this deep reservoir of information enables much better decision making. When a potential problem presents itself, the engineer can use FabVision Solar to bring up all of the relevant image information and look at it in a variety of ways to determine the validity of the defects, to spot any repeating patterns, to assess the related recipe settings, confirm SPC parameters, or to focus on individual operators, shift timing issues, etc.

Being able to go back and look at all of the relevant data in context and to interactively drill down as deep as necessary gives the process engineer a rich new set of analysis tools that had not been available before FabVision Solar.

Summary Managers and process engineers in today’s high-volume PV manufacturing facilities are faced with the double-edged dilemma of: 1. Managing multiple inspection platforms generating large data sets of rich information that is vital for process control KLA-Tencor Corporation

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2. Not being able to make full use of the information in a timely fashion to support decision making and process improvement The challenges presented by these large data sets go well beyond the capabilities of conventional on-tool analysis approaches, especially in high volume production environments where even short delays in correcting errors can mean large numbers of parts at risk.

Effective process control in today’s PV production facilities requires the intelligent aggregation and analysis of comprehensive data sets across multiple tools. This means combining the ability to see the big picture and quickly spot deviations with the ability to drill-down into root causes and formulate corrective actions.

FabVision Solar addresses this dilemma by providing a turnkey, comprehensive process control and problem analysis solution that is tightly integrated with existing ICOS PVI-6 platforms already in use throughout most PV manufacturing environments. All of the available data is captured, retained and put directly at the engineers’ fingertips to support deep analysis of root causes and real-time process control decisions.

With FabVision Solar, the bottom line benefits include: • • • • • • • • • •

Significant yield improvement Lower per-unit costs Maximizing production efficiency Reducing cycle times Increasing process tool productivity Reducing materials at risk Detecting and correcting process issues earlier Reducing field failures Accelerating time-to-market Optimizing profitability

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