Online liquid particle counter

Acona LE MiniOnline liquid particle counterIt is an online particle counter for CMP process fluids, based on the SPOS single particle counting principle, supporting real-time monitoring before and after filtration and at the end of transportation, providing large particle count (LPC) trend and threshold statistics, assisting in filtration optimization, abnormal warning, and release decision-making. It is suitable for CMP sludge production, transportation, and wafer manufacturing scenarios, improving process control accuracy and equipment utilization.

Acona LE MiniOnline liquid particle counterIn CMP process, LPC (Large Particle Count) is commonly used to characterize the risk of large particles at the tail end. LEMini supports online monitoring of key nodes such as before filtering, after filtering, and at the end of delivery, providing data support for filtering optimization, anomaly warning, and release decisions.

【 Applicable Objects and Scenarios 】

CMPsludge manufacturer: factory quality control, batch consistency, storage/mixing process monitoring.

SDS (Slurry Delivery System) integrator: online quality monitoring, alarm linkage, and maintenance window optimization for the delivery system.

CMP production line of wafer fab: pre release monitoring of POU end, evaluation of filter changeouts, and anomaly tracing.

【 POU Online Particle Counter Deployment Suggestions 】

The goal of POU is not to 'do a detection', but to directly serve process control with data. Typical deployment locations include:

Before filtering: Establish a baseline for incoming materials and mixed materials, and identify the impact of upstream fluctuations on LPC.

After filtering: Verify the filtering effect and filter status to form a characteristic curve before and after replacement.

SDS Transport Terminal (Tool Terminal): Monitor the impact of the transport chain on the Large Particle Control (LPC) at the tail end and capture any anomalies at the end.

Figure 1 Schematic diagram of bypass online monitoring of MPsludge in storage mixing transport filtering PU nodes

Core Technology and System Design

1SPOS single particle counting

Using the SPOS (Optical Particle Counting/Reduction) mechanism, the particle size distribution and threshold statistical results that can be used for process control are output, providing quantifiable data basis for the tail end large particle risk (LPC) of CMPsludge.

2. Online stability design

For the demand of online continuous or timed sampling, components such as steady flow, back pressure, defoaming, protective filtration, and flushing can be selected according to the working conditions to reduce the impact of bubbles/fluctuations on trend data and improve the maintainability and repeatability of long-term operation.

3 Modular bypass flow paths

The bypass sampling detection reflux/discharge path can be configured to match different on-site pipelines and process windows. For high-value sludge, online particle monitoring and risk escalation can be achieved without changing the main process.

4 Integration and linkage

Provide communication and alarm interfaces (according to configuration) for interfacing with SDS systems or upper computers to achieve online data archiving, over limit warning, and maintenance event correlation analysis.

Frequently Asked Questions | FAQ

Q1: Where is the POU suitable for placement?

A: Usually deployed at POU nodes such as pre/post filtering, mixing, and SDS delivery end (tool end), it is used to observe the LPC trend and threshold statistics of CMPsludge online.

Q2: What does the LPC of CMPslurry refer to?

A: LPC (Large Particle Count) usually refers to the number of large particles exceeding a certain threshold size (such as>0.5um,>1um,>5um, etc., according to internal control definition). In the CMP process, the abnormal increase of LPC is often related to the risk of scratches, filtration status, and transport conditions.

Q3: What decisions can online data be used for?

A: Used as a trend basis for optimizing filter changeouts, adjusting SDS operating conditions, isolating abnormal batches, and determining POU release.

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