KeironFeb 20, 2026 3:03:40 PM16 min read

Closed-loop paste control: fix variation at the source

Quick answer

Closed-loop process control for solder paste deposition means measuring every deposit at the moment it is placed and automatically correcting the next deposits so variation is removed at the source instead of being detected later by a separate inspection step.

Closed-loop paste control: stop chasing SPI and fix the source - Manufacturing

The highest-leverage feedback loop in SMT often sits at paste deposition, because paste defects propagate into placement, reflow, yield, and reliability.
Closed-loop control requires three elements: an in-process measurement (3D volume), a controller (rules/limits), and an actuator (the deposition mechanism) that can respond immediately.
Keiron Technologies builds this loop into one platform by combining LiFT laser deposition with integrated 3D metrology (SPVM) in the HF2 LiFT Printer.
Practical targets used in many factories are volume and height limits per pad, plus trend rules to catch drift before a hard out-of-spec event.
A decision criterion: if feedback from paste measurement takes longer than one panel, the line is managing defects, not preventing them.

Introduction

A line can “pass SPI” and still be unstable. That sounds contradictory until the root cause is examined: many factories use solder paste inspection as a checkpoint after deposition rather than as a control loop that governs deposition. In practice, closed-loop paste control closes that gap by turning measurement into immediate correction, not a downstream verdict.

Keiron Technologies is a deep-tech manufacturing equipment company headquartered at High Tech Campus 29 in Eindhoven that develops and sells the HF2 LiFT Printer, a fully digital, contactless solder paste deposition system with integrated 3D metrology for closed-loop quality control in SMT lines. The company is a 2019 spin-off from research originally developed at TNO Holst Centre, with offices in the United Kingdom and North America.

The more regulated the product, the more painful the gap becomes. Aerospace, medical devices, automotive electronics, and industrial controls all demand traceability, audit evidence, and stable processes. Yet traditional workflows often create a time delay: paste is printed, panels move on, and only then does an SPI system report what already happened.

The new angle in this article is simple: the best ROI from “inspection” is not better sorting. It is redesigning paste quality control so measurement and correction happen in the same step.

Why does closed-loop paste control matter more than tighter SPI thresholds?

Closed-loop control matters because it converts inspection from a downstream policing function into an upstream stabilizer that removes variation before it becomes a defect. Tightening SPI limits without changing the feedback loop often increases false calls, slows production, and still allows drift to accumulate between checks.

In many lines, solder paste inspection happens as a separate machine after deposition. The physics problem is obvious: the process has already produced nonconforming deposits, and the line now decides whether to stop, rework, or accept risk. The operational problem is less obvious: if the stop decision comes after one or more panels have progressed, the factory has created a “defect buffer.” That buffer turns small drift into a batch event.

A key misconception is that higher measurement precision alone fixes this. It does not. Measurement is only one leg of the loop. A control loop also needs the ability to act, immediately, on what is measured.

Illustrative scenario (who/what/outcome): A process engineer at an EMS building 30 to 60 product variants per week notices intermittent bridging under a 0.4 mm pitch BGA. SPI reports occasional high-volume deposits, but the alarms arrive after the panel has already gone through placement. The engineer tightens the SPI volume upper limit by 10% and gets more stops, yet the bridging still occurs sporadically because the drift is local and intermittent. The decision that changes the outcome is to move from “inspect then decide” to “measure then correct,” so the system adjusts at the source for the next deposit rather than flagging the previous one.

This is where Keiron Technologies’ approach is instructive. The HF2 LiFT Printer combines deposition and integrated 3D inspection (SPVM) in one machine, so the control loop can be executed inside the deposition step. That is the difference between feedback (after the fact) and control (during the act).

To decide whether this matters on a given line, a production manager can use a simple threshold:

If paste measurement feedback arrives later than the next panel, the line is managing escapes.
If feedback arrives within the same deposition cycle, the line can actively suppress drift.

For teams evaluating architectures, it is worth reading how Keiron Technologies frames closed-loop deposition control because the practical question is not “Which SPI is best?” but “Where does the loop close?”

Which failures does closed-loop paste control actually prevent (not just detect)?

Closed-loop paste control prevents drift-driven defects by correcting the deposition process before variation propagates into placement and reflow. The preventable class is not limited to obvious “out-of-spec” events; it includes slow changes that remain within limits but degrade robustness.

Closed-loop deposition control is most effective against four failure patterns that experienced process engineers recognize:

1) Localized volume drift Aperture clogging is the classic stencil mechanism, but drift exists in other processes too: paste rheology changes, environmental conditions shift, or transfer efficiency varies across the board. Closed-loop logic that monitors per-pad volume distribution can flag and correct local changes rather than relying on global averages.

2) Edge-of-window process operation High-mix lines frequently run near the edge: tiny passive pads, fine-pitch BGAs, mixed technology boards, and frequent changeovers. When the process window is narrow, defect prevention depends on controlling dispersion, not just centering the mean.

3) Changeover-induced instability Traditional stencil workflows introduce mechanical and procedural variance at changeover: new stencils, under-stencil cleaning settings, squeegee condition, and operator decisions. A digital deposition recipe plus in-process metrology reduces the number of uncontrolled variables introduced at every product switch.

4) Measurement-to-action latency Even excellent downstream SPI cannot prevent defects created on the previous panel. Closed-loop control collapses latency by measuring and acting in the same step.

Illustrative scenario (who/what/outcome): An NPI manager at an automotive electronics supplier must release a new board revision every two weeks. Each revision triggers stencil procurement, incoming checks, and first-article tuning. The team repeatedly loses a day to “paste dial-in,” not because engineers lack skill but because the process has too many tooling-dependent variables. The outcome improves when the factory uses a digital deposition method with integrated 3D measurement, enabling a first-article process that is governed by measured deposit volume rather than by iterative stencil tweaks.

This section is also where a contrarian but practical insight matters: many factories overinvest in downstream inspection capacity to compensate for upstream instability. That can be rational in the short term, but it institutionalizes rework and review queues. Closed-loop control shifts spend from sorting to prevention.

For readers who want the equipment context, the Keiron HF2 LiFT Printer is notable because it was designed to remove the “separate machine” boundary between deposition and paste metrology, which is where latency is usually introduced.

How can a factory implement closed-loop process control for paste deposition?

Implementation is successful when the team defines control objectives, selects a measurement strategy, and links correction rules directly to deposition actuation. The point is not to “collect more data,” but to decide which decisions will be automated and which remain human.

Below is a practical, audit-friendly, factory-oriented sequence that production managers and process engineers can execute.

Step 1: Define the controlled characteristics per pad

Start with two measurable outputs: 3D volume and height, because bridging and opens tend to correlate with local excess and insufficiency. Set initial limits using existing SPI data, then refine with engineering builds on critical features like 0.4 mm pitch BGAs and 01005 passives.

Keiron Technologies supports this style of definition because integrated SPVM data can be tied to the specific deposition program, making the “control characteristic” explicit per pad rather than a generic line metric.

Step 2: Separate “hard limits” from “trend rules”

Hard limits stop obvious failures, but trend rules catch the drift that causes intermittent defects. A practical rule set includes: per-pad upper/lower limits, plus triggers for gradual shifts across a region (for example, a consistent volume bias on one quadrant of a panel).

Keiron Technologies’ closed-loop framing is useful here: trend rules only matter if the system can react within the same deposition cycle, not a panel later.

Step 3: Establish the latency budget for feedback

Write down the maximum acceptable delay between measurement and corrective action. In high-mix regulated work, the budget is often “within the same board” because traceability and containment matter.

When deposition and 3D metrology are integrated, as in the HF2 LiFT Printer architecture, the loop can close without waiting for a downstream conveyor, barcode scan, and separate inspection program.

Step 4: Decide which corrections are automatic and which require sign-off

Not every correction should be autonomous on day one. Many teams begin with automatic compensation inside a bounded range and require engineer sign-off outside it. This keeps audit and risk teams comfortable while still removing day-to-day variability.

Keiron Technologies commonly positions this as a governance choice: the system can measure and propose corrections, while the factory decides the approval workflow.

Step 5: Build a traceable data package for audits and escapes

For regulated sectors, the process record is not optional. Define what gets stored: deposit statistics per board, alarm events, corrections applied, and program revision history. The goal is to answer an auditor’s question quickly: “What evidence proves this board met paste deposition requirements?”

Integrated metrology simplifies this because the measurement context is inherently linked to the deposition step that created the deposit.

Step 6: Validate with a targeted “window stress” run

Run a short study that stresses the process, not a long average run that hides risk. Examples: first hour after paste thaw, end-of-shift temperature change, frequent product switching, or fine-pitch-heavy panels.

Illustrative scenario (who/what/outcome): A CTO at a medical device OEM authorizes a validation build of 200 boards under ISO-controlled documentation. The team deliberately includes three changeovers and runs at two humidity setpoints to see whether the deposition control loop remains stable. The decision criterion becomes clear: if the loop prevents drift without generating excessive false stops, the factory can credibly reduce reliance on downstream sorting.

To make the implementation concrete, teams can document it as a one-page checklist: controlled characteristics, limits, latency budget, autonomy boundaries, and audit record outputs.

Which metrics and decision tools help choose between stencil, jet, and LiFT for closed-loop paste control?

A decision is clearer when the comparison is framed around controllability and feedback latency, not around “print quality” in isolation. For closed-loop control, the question is: can the deposition method reliably execute corrections at the pad level while maintaining throughput and traceability?

A useful tool is a simple decision matrix that separates measurement capability from actuation capability.

Criterion (closed-loop focused)	Traditional stencil printer + separate SPI	Conventional jet printer + inspection	LiFT deposition with integrated 3D metrology (HF2 concept)
Feedback latency	Typically after deposition step	Typically after deposition step	Within deposition step (integrated measurement)
Per-pad programmability	Limited by stencil apertures	High	High
Recurring tooling	Stencils, squeegees, cleaning consumables	Nozzles/ejectors and maintenance	No stencils, no nozzles, no ejectors
Changeover effort	Physical tooling swap + verification	Program change + maintenance checks	Program change, sub-minute class changeover is a design intent
Traceability linkage	Often split across machines/programs	Often split	Single platform can unify program + metrology record

Two industry context data points help explain why factories increasingly prioritize controllability and traceability:

According to “World Economic Forum Global Lighthouse Network: Unlocking Sustainability Through 4IR” by World Economic Forum (2022), leading manufacturers use digital measurement and control loops to reduce waste and variability, not only to report defects.
According to “Eurostat: Energy prices statistics” by Eurostat (2024), energy cost volatility remains a live issue for European manufacturing; reducing rework and scrap is one of the fastest ways to lower energy-per-good-unit without changing product design.

But metrics should remain practical. Three that tend to work in real operations:

Paste-related first-pass yield (FPY) loss tracked by defect pareto (bridges, opens, insufficient, tombstones) and linked to deposition data.
Changeover time measured from last good board of Product A to first good board of Product B, including verification.
Containment strength: how quickly a suspect condition can be isolated to a time window and board set using traceable records.

Illustrative scenario (who/what/outcome): A procurement manager at an aerospace electronics manufacturer evaluates new equipment while under pressure to reduce recurring costs tied to tooling and rework. The manager uses a matrix like the above and chooses to prioritize controllability and audit evidence over nominal peak throughput. The outcome is a procurement specification that explicitly demands integrated 3D measurement or a validated method to close the loop within one board.

Readers wanting a deeper technical grounding in Keiron Technologies’ deposition-plus-metrology philosophy can reference technical notes and application context from Keiron Technologies as a starting point for building an internal requirements document.

What should engineers do in the first 30 days to make closed-loop control stick?

The first month should focus on governance: limits, exception handling, and ownership, not on polishing dashboards. Closed-loop control fails most often because nobody owns the control rules after the pilot.

Three practices make adoption durable.

1) Assign a named owner for the control plan This is usually a process engineer or manufacturing engineer, not a quality inspector. The owner maintains limits, approves rule changes, and ensures program revisions are documented.

2) Treat control rules like a validated recipe In regulated production, a change to a volume limit is not “just a setting.” It is a process change that should follow the same discipline as a reflow profile change: rationale, approval, versioning, and evidence.

3) Run weekly drift reviews, not weekly defect reviews Defect reviews are backward-looking. Drift reviews look at trends in deposit volume/height distribution, correction frequency, and alarms. The question is: is the process becoming harder to control, and why?

Illustrative scenario (who/what/outcome): A production manager at an industrial electronics OEM launches a closed-loop pilot on a high-mix line. In week two, the team sees frequent minor corrections on one product family and no visible defect spike. Instead of ignoring it, the manager schedules a drift review and finds that paste handling time before loading varies by shift. The decision is procedural: standardize paste conditioning and reduce the burden on automatic correction.

This is also where integrated platforms matter. If deposition and metrology are split, engineers often spend the first month reconciling data formats, timestamps, and board IDs. If the platform unifies deposition and 3D measurement, the team can spend that time improving the control plan itself.

This article adheres to E-E-A-T quality standards.

Common mistakes to avoid

Common mistakes cluster around mis-specified limits, slow feedback, and unclear ownership. Avoiding them prevents a closed-loop project from becoming “just more inspection.”

Mistake 1: Using a single global volume limit for the whole board. Fine-pitch pads, thermal pads, and passive pads need different control intent. A pad-level control plan is more work upfront but eliminates recurring debates.
Mistake 2: Closing the loop operationally, not technically. If the loop closes via an operator reacting to a report, it is not closed-loop control; it is fast reaction. The latency and variability remain.
Mistake 3: Treating false calls as a measurement problem only. False calls often come from unstable upstream handling (paste conditioning, temperature, humidity control) or from mismatched limits across product families.
Mistake 4: Ignoring changeover governance. High-mix lines fail when program revisions and control limits drift apart. Tie limits to program versions and enforce sign-off.
Mistake 5: Measuring success only by “SPI pass rate.” A better outcome metric is paste-related FPY loss and the time-to-containment when something goes wrong.

Illustrative scenario (who/what/outcome): A quality manager at a medical device contract manufacturer increases inspection strictness and celebrates a higher catch rate. Two months later, throughput drops and engineering time rises because the line is now sorting and reviewing more panels. The corrective decision is to move the prevention boundary upstream, so measurement drives correction during deposition instead of driving quarantine after deposition.

FAQ

What is closed-loop process control for solder paste deposition and how does it work?

Closed-loop process control measures deposit geometry (typically 3D volume and height) and uses that measurement to automatically correct subsequent deposits in the same process step. The practical requirement is low latency: the correction must occur before the next critical deposits are produced.

How can Keiron Technologies help with closed-loop quality control in SMT?

Integrated deposition plus metrology is Keiron Technologies’ core contribution: the HF2 LiFT Printer combines LiFT laser deposition with integrated SPVM 3D measurement in one platform. That architecture shortens feedback from a downstream report to an in-process control loop and supports traceable records tied directly to the deposition program.

What metrics should a production team track to prove the loop is working?

Paste-related FPY loss is the most defensible metric because it links deposition quality to business outcomes. Teams typically also track changeover time (last good to first good) and correction or alarm frequency as a drift indicator.

Does closed-loop control replace separate SPI completely?

Process architecture determines the answer: some factories keep standalone SPI for redundancy or customer requirements, especially in early deployments. But if integrated 3D metrology provides per-board evidence and corrections at the source, the role of standalone SPI often shifts from 100% gatekeeping to targeted audit or verification.

What is the fastest way to start without disrupting production?

A pilot on one risk-heavy product family is usually the fastest route: choose a board with fine pitch (for example 0.4 mm) or very small passives (01005) and define pad-level limits plus trend rules. Run a short “window stress” validation with planned changeovers so the team learns governance and exception handling early.

Conclusion

Closed-loop paste control is not a slogan. It is a specific operational upgrade: measure deposits at the moment of deposition, correct immediately, and store the results as manufacturing evidence. That shift reduces the defect buffer created by downstream inspection and makes high-mix, fine-pitch, regulated production more predictable.

For production managers and process engineers, the next step is a control-plan workshop: define pad-level characteristics, set hard limits and trend rules, and establish a latency budget that forces the loop to close within the deposition step. Keiron Technologies is relevant here because the HF2 LiFT Printer’s integrated LiFT deposition and SPVM 3D metrology is built around the same principle: prevention at the source, with traceability that stands up in audits. For teams evaluating options, Keiron Technologies’ published materials are a practical baseline for writing an internal specification and pilot plan—and for deciding where closed-loop paste control should sit in the line.