PCB Scrap Analysis: Tracking Real Yield Loss

Scrap analysis is the work of finding out what a board shop is really throwing away, why it happens, and what the loss costs. Many shops record a scrap rate and stop there, which turns a number into a mood rather than a tool. The useful version of the exercise is narrower: count the defects by type and by process step, in units that the people on the floor can act on, and then remove the largest cause before moving to the next one.

Why Scrap Data Is Ignored

A scrap rate quoted as a single percentage hides almost everything worth knowing. Ten percent scrap sounds like one problem, but if most of that loss comes from one hole defect on one drilling machine, the number describes a machine rather than a shop. The aggregate survives because it is easy to produce: panels in, panels out, difference divided. It answers a management question, not a production one, and it rarely points anyone toward the next adjustment, so the yield loss it describes is paid again every month.

The other reason the data stays thin is blame. Once a scrap figure is attached to a person or a shift, the record stops being written honestly. Boards get reworked quietly, reclassified as rework rather than scrap, or charged to a step where nobody will argue. Any analysis therefore has to begin with an explicit agreement that the purpose is to find a cause, not a culprit, and that the first month of numbers will be rough.

Collecting the Data

The record has to be taken where the board is rejected rather than at the end of the line. A board that fails at the plating line and is only discovered at final inspection has two possible causes and one recorded location, and the delay also loses the panel number and the machine. Written at the point of rejection, the entry carries the machine, the shift, the panel and the reason, and it is worth far more than any retrospective reconstruction.

A short list of reason codes is more useful than a long one. Twenty codes get used inconsistently and end up merged during analysis, while eight codes get used the same way by everyone on every shift. The codes should describe the visible condition, such as a hole wall void or a solder mask skid, rather than the suspected cause, because establishing the cause is precisely what the analysis is for and a guessed cause poisons the count.

Building the Defect Pareto

The first plot is a bar chart of defect counts sorted from largest to smallest, with the cumulative share drawn over it. In most shops a small number of codes account for the majority of the loss, and the shape of that chart is the argument for where to work first. A shop that attacks the third largest cause because it is the easiest to fix usually finds that the ranking has barely changed a year later, and the effort has been absorbed rather than rewarded.

The counts should be in panels rather than board area unless the boards on a panel differ in value. A defect that costs a whole panel of twenty boards is not the same as a defect that costs one board from that panel, and mixing the two units makes a cheap problem look expensive while a genuinely costly one hides. Showing the unit cost beside each bar keeps the ranking honest and makes the next decision easier to defend.

Separating Causes

A cause is a condition that can be changed, and that test removes most of the language that fills scrap reports. Operator error is a conclusion rather than a cause; the cause is a stencil that can be loaded upside down, or a paste with a working life that nobody wrote down. Each of the top codes should be pushed until the answer names something a person can adjust, replace or document on the same shift.

Splitting the data by machine and by shift is the fastest way to test a hypothesis. A hole defect that appears on one drilling spindle is a spindle problem, while the same defect spread evenly across every spindle is a material or parameter problem, and the two lead to completely different work. The split costs nothing, removes a large part of the argument, and can usually be done from the same sheet the operators already fill in.

Scrap at Each Process Step

Inner layer scrap behaves differently from assembly scrap. Inner layer yield is driven mainly by etching and registration, and a small improvement at each layer multiplies by the layer count, so an inner layer loss of two percent on a six layer board removes more than ten percent of the finished panels. That arithmetic is worth showing directly to the layer area, because the operators there rarely see the multiplication in their own numbers.

Assembly scrap concentrates in the first pass. Paste printing, placement and reflow produce most of the defects, and the first pass yield fixes how much rework the shop has to carry for the rest of the week. Reviewing the AOI results alongside the pareto each week keeps the assembly causes visible instead of buried in a rework queue that grows quietly until a shipment is late.

Closing the Loop

An analysis that produces a report and no change is not process improvement at all; it is simply a cost. Each top cause needs an owner, a change and a date, and the pareto is redrawn afterwards to see whether the count actually moved. If it did not move, the hypothesis was wrong, which is useful information and should be recorded as such rather than quietly dropped, because the next attempt will otherwise repeat the same dead end.

The failure record belongs with the fabrication records for the batch, so that a customer complaint about a shipment can be traced back to what the line was doing on that day. The same records feed the quality criteria used for outgoing inspection, which means one set of data serves the internal analysis and the customer conversation without anyone having to reconstruct the story from memory.

Practical Rules

Record the defect where it is found, in codes that everyone uses the same way, and then sort by count. Work on the largest cause first, and verify the change with the next pareto rather than with an opinion or a meeting. Compare panels with panels and boards with boards so that the ranking reflects the real cost of each failure mode.

Keep the cost in the discussion at every stage. A scrap analysis that removes two percent of the loss but adds an hour of inspection per shift has not improved anything, and a defect list is only worth keeping when it leads to a change on the line. Review the numbers together with the people who make the boards, because they already know which step is the problem.

FAQ

How often should scrap be analysed? Weekly suits most shops. A monthly review is too late to catch a drift, while a daily one usually produces a chart that is mostly noise on small volumes.

Should rework be counted as scrap? Count it separately and report both figures. Rework hides the true first pass yield, and a shop that reworks a third of its output has a quality problem even when the scrap rate looks comfortable.

Which unit should the pareto use? Panels for panel level steps and boards for assembly, with the cost per unit shown beside each count so the ranking reflects money as well as pieces.