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Feature Articles

Machine Vision in the Assembled Printed Circuit Board Market – Part 1

by Nello Zuech, Contributing Editor - AIA

 

The Past

Much has happened since the first machine vision systems were introduced to inspect populated printed circuit boards in the early 1980s. Today these systems are no longer called machine vision but rather “automated optical inspection” or AOI systems. Originally the term AOI was associated with machine vision systems addressing bareboard inspection applications. Today the term is widely used for all automated visual inspection systems used in electronic manufacturing. It is likely the term AOI has been favored because the performance of the early machine vision systems addressing assembled board applications was only marginally acceptable. Regardless, the underlying technology is still machine vision.

Since the early 1980s the fundamental manufacturing process for electronic assembly has changed. At that time the principal approach involved lead-through-hole mounting. The machine vision application included top-side presence and orientation but also bottom-side lead presence and clinch angle verification. Today the principal manufacturing approach involves surface mount technology. Now the application includes both presence and placement validation. Significantly, there are still many boards that combine the two assembly approaches. Board designs that use component direct attach methods are gaining in popularity.

All these assembly approaches yield a unique set of appearance variables. Variables are the “gotchas” of machine vision systems. Today’s machine vision systems are far better at handling these variables than ever before and they are only getting better with the advances in the underlying compute power which have made it possible to handle the resolution required at the throughputs required, all while reducing the false calls and false accepts and reducing training time for new board designs. The technology is finally living up to its much-heralded promises of the past.

Adoption Drivers

Driving demand for these AOI systems are factors such as ever-smaller components, ever finer pitch density, ever more components per square inch, higher production rates – all of which make it increasingly more difficult for people to inspect. Bob Ries of CyberOptics specifically cited “Primary drivers are PCB complexity and component size.” And “The need to improve first pass ICT yields.”

The subjectivity of people leads to even greater quality judgment uncertainty as boards become more complex. Similarly these factors make it ever more difficult for conventional in-circuit testing. In this country using people to perform these inspections requires companies provide them with ergonomically correct inspection workstations, which are expensive. Increasingly electronic manufacturing service companies or contract manufacturers are doing board assembly. This is a business that is very competitive price-wise. Consequently, there are economic drivers to substitute capital for people. In the case of AOI systems additional benefits include improved quality, improved yield, reduction of rework, improved customer satisfaction – all results that go to the bottom-line.

The cost of failure in electronic manufacturing is appreciably greater with each value-adding step, with the cost of the failure of a product reaching the consumer the greatest cost. The ultimate price of many consumer electronic products is relatively low, to the point where many are not worth repairing. In the case of cellular phones many are actually given away as a promotion to provide the phone service itself. However, if the phone does not work one has a very unhappy customer and one likely not to use the service promoted or re-enlist in the service. Hence, there are significant economic drivers among both contract manufacturers and OEM manufacturers to avoid failure.

Chuck Gamble of Leica Microsystems made the following observation: “AOI is usually associated with three things, PAIN, they usually have so many problems producing a product, that they turn to AOI in a move of desperation. SALES, their customer tells them they won’t get an order unless they have AOI in place for their products. And KNOWLEDGE, the PCB assembler has learned through experience that they can ultimately produce a superior product, have faster start-up times, raise yields and lower overall production costs with the proper implementation of AOI.”

The North American electronic industry is apparently the earliest champion for in-line AOI systems. Bob Ries attributes this to “the relative complexity and high cost of PCBs assembled here.” Chuck Gamble suggests that Europe is following closely but that the “Pacific Rim tends to be strictly an inspection (good or bad) market.”

Where to Use AOI?

The biggest challenge is not whether to use AOI systems, but rather where to use them. To avoid shipping a reject product suggests the use of AOI systems at the end of the production line. The challenge is that at the end of a production line AOI systems are not likely to provide a comprehensive solution. Rather they have to be considered a complement to X-Ray-based machine vision systems, which have the capacity to assure the quality of a solder joint as well as verify the joint’s presence. X-Ray-based systems used in the electronic industry will be the subject of another article.

Using AOI systems to sort rejects at the end of the production line does not avoid rework, which can be reduced by using AOI systems to monitor the results of each of the value adding steps along a board assembly line. In other words, a line designed with prevention in mind might include the following operations:

SIDE 1

Screen print solder paste or adhesive dispensing solder dots

AOI

After chip placement

AOI

After fine-pitch placement

AOI

After reflow

AOI

Through-hole assembly

SIDE 2

Screen print solder paste or adhesive dispensing solder dots

AOI

After chip placement

AOI

After fine-pitch placement

AOI

After reflow

AOI

Wave solder

AOI

In other words, based on the philosophy of process monitoring or prevention of rejects, up to nine AOI systems could be required. Given an average price of as little as $100K suggests that it would cost at least $1M to install AOI systems as part of a comprehensive process control strategy and even more if one were to include X-Ray-based systems as part of the strategy. This is a highly unlikely scenario! Using an AOI system after fine-pitch placement would detect conditions associated with chip placement machines, however, it would not provide immediate feedback as to the performance of the chip shooter. The key is to provide data immediately after a process step so an indication of pending failure can be flagged and corrective action take place before failure is actually experienced.

If the boards were rerouted through the same component assembly machines for side 2, only five systems would be required and if no wave soldering took place, only four systems would be required. While more manageable these would still be expensive scenarios. It is also noted that today even for lead-through-hole components solder paste can be applied in the holes in the same manner as for surface mount devices. This practice eliminates the need for wave solder.

Where is the Most Value?

The challenge is where to get the most “bang-for-the-buck?” One factor will be the nature of the assembly line itself. Is it one geared for high volume/low model mix, medium volume/medium model mix or low volume/high model mix production? In the high volume/low model mix scenario one stands to gain the most from a comprehensive strategy to avoid adding value. Nevertheless, four to nine systems on a production line will be unlikely.

Since assembly starts with solder paste application and any reject condition at this stage will manifest itself later on it makes sense to perform a comprehensive inspection after application so reject boards can be cleaned and reused. At this stage the system should inspect for solder registration with respect to the pad, sufficient/insufficient solder on the pad and solder bridging between pads. One issue at this stage whether 2-D or 3-D measurements are required. As smaller components and components with finer pitch densities are adopted, volume measurements will become more critical.

Some, however, suggest that inspection before reflow not only finds placement machine errors but also can find defects resulting from solder paste deposition. One issue at this stage is whether the system should be quantitative or qualitative or both. Systems that offer qualitative solutions can tell if components are present and correct, oriented properly and relatively aligned or positioned properly. Quantitative systems can actually measure component offsets and can be used to monitor the placement machine’s performance and flag conditions trending out of spec so corrective action can take place before actual defective conditions occur. Conditions detected before reflow can be corrected more easily than after reflow, where rework requires unsoldering which can further damage neighboring circuitry and result in ultimately throwing out the board.

Using an AOI system after reflow will likely detect most of the errors caused by solder paste deposition, placement and the reflow process itself. However, at this stage one can sort rejects and provide immediate feedback for the reflow process but not for the screen printing or chip placement processes. It is also more difficult to rework a reject condition after reflow than it would be after the previous steps in the assembly process. In other words, a good deal of the value of AOI is lost!

Understanding Requirements

If a qualitative approach is satisfactory, it is important to understand the principles of detection associated with machine vision systems. Most today would agree that in order to detect an artifact in an image that artifact should cover a minimum of 3 X 3 pixels. Sub-pixel detection schemes do not apply when simple presence is the application. If one then suggests that the smallest component on the board (say a component that is 0.1” X 0.1”) will be covered by 3 X 3 pixels, each pixel will be 0.03” X 0.03”. If the typical system based on an area array camera has nominally 500 X 500 pixels, the maximum field-of-view of that camera should be 15” x 15”. If, however, one is trying to detect bridging between neighboring pads or lines that are only 2 mils a part, then the 3 X 3 pixels have to cover an area of 0.002” X 0.002”. This then suggests the maximum field-of-view should be 1” x 1”. As board densities have increased the AOI industry has responded by offering systems with cameras that have nominal resolutions of 1000 X 1000 or even greater in some instances.

If a quantitative approach is required, then the rules of metrology apply. That is that the measurement instrument should have a repeatability that is 10 times the total tolerance band and ideally an accuracy that is 20 times the tolerance band. In gauging applications, since measurements are typically made to boundaries or objects and boundaries are defined by their edges, the concept of subpixel processing does apply. What all this suggests, therefore, is if one is measuring features with tolerances on the order of +/- 0.001” so the tolerance band is 0.002”, the repeatability of the measurement instrument or AOI system in this case should be 0.0002”. This means the AOI system must be able to discriminate to 0.0001” increments, as there is inevitably a +/- one discrimination unit of uncertainty in the measurement.

All this suggests that the AOI system should have the ability to find an edge such that the subpixel is 0.0001”. Given that a typical system has an ability to perform subpixel processing to one-tenth of a pixel suggests that a pixel unit will be 0.001”. This then suggests that a camera with a nominal 500 X 500 array can only have a field-of-view of 0.5” x 0.5”. One could relax these rules somewhat but for reliable measurement performance it is not advisable to relax them by any more than a factor of two. In other words one might expect reasonable performance with such a camera covering a 1” X 1” field-of-view.

Recognizing these “rules-of-thumb,” so to speak, one can see why sys

 

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