Data acquisition and traceability

Zestron records process data during PCB cleaning

When cleaning electronic PCBs, demand is increasing for the collection of process data and the assurance of its traceability. This not only entails advantages for customers of electronics manufacturers, but also for the manufacturers themselves, who will then be able to improve their processes on the basis of the data raised.

Stefan Strixner, Principal Engineer, Zestron Europe

Numerous forms of process data can be recorded during a cleaning process. The two general parameters that can be assigned to each of the above-mentioned process steps are time and temperature.

Producing cleaning process data

Each process step has unique monitorable parameters:

1. Cleaning step:

  • Chemistry type and batch number
  • Cleaner concentration on the items to be cleaned
  • Bath loading
  • Ultrasonic energy & frequency
  • Spray pressure, filter pressure, and/or differential pressure
  • Flow rate (filter loading)

2. Rinsing step:

  • Quality of rinse water or rinsing medium (fresh water and rinsing tank)
  • Ultrasonic energy & frequency
  • Spray pressure, filter pressure, and/or differential pressure
  • Flow rate (filter loading)

3. Drying step:

  • Air blowing pressure
  • Filter pressure
  • Volume flow
  • Negative pressure (with vacuum drying)

Depending on the specific data type, a wide range of offline (manual) and online (automated) procedures can be used for recording the above-mentioned process data. Many cleaning machine manufacturers have already integrated automated data gathering tools into their systems. However, some procedures are either very specific or cannot be automated. (See table on top of page)

Whilst offline methods generally suffice to provide snapshots of process states, a continuous process and result assurance cannot be guaranteed, let alone any true traceability or substrate-specific assignment of the process data. In addition, not all the data that can be collected is critical to the results so that it only makes limited sense to record it in its entirety.

The most important data to be monitored is that which is subject to temporal variation or continuous change. The most obvious in a cleaning process is the concentration of cleaner, which can fluctuate due to over-dilution or over-concentration.

This is not just applied to cleaners administered as concentrates and diluted down to a defined concentration, but also “ready to use” mixtures, which may also fluctuate during the process as they are usually composed of more than a single chemical component.

Concentration measurement in particular is a parameter that requires more concern than just measuring a single value. Since many aqueous systems have holding tanks that see density-related segregation and have varying abilities to homogenize the mixture, there is the potential that the concentration measurement in the tank differs from the actual concentration level in the cleaning material. For measurement and tracking purposes, the actual level of concentration in the cleaning material is the relevant measurement for the cleaning process. Therefore, it is important to think about the nature of the process data and install measurement sensors in locations suitable for data capture. For measuring the cleaner concentration, a flow sensor in the spray circuit of a spray-in-air cleaning machine is preferable to a submersible sensor in the holding tank.

By default, the recording of process-relevant parameters is used for the alarm display or a process interruption, whenever these surpass the set thresholds. Even if little used in practice, data recording is also useful for process control. Here, for example, the parameters temperature and cleaner concentration should be mentioned. For example, monitoring the cleaning temperature is often used simultaneously to control itself, so that any undershooting or overshooting of the switching on-and-off of the media heating process can be controlled. Online monitoring of the cleaner concentration can also be coupled with a dosing system for the cleaner concentrate and the water, in order to ensure that the working concentration always remains constant.

Improving traceability

As already mentioned, most of the measuring methods mentioned are already included as standard in many cleaning machines or are at least relatively easy to integrate where this is desired. However, traceability of the prevailing process conditions with respect to the cleaned substrates is still absent at this point. Nevertheless, there is a clear trend towards realising that this is becoming an increasingly important feature and is being offered as an option by more and more equipment manufacturers. At the core of such a traceability concept is the scanner-based acquisition of items marked with a barcode or QR code, as well as their assignment to the selected and monitored parameters. To improve traceability even further, it is also conceivable and possible to record the goods carrier, operator, and even the type and batch of cleaner used. This data could then also be used to release or block the process in case of misuse.

Most cleaning machine manufacturers now include digital connection interfaces to view or export data to a hardwired or networked operation workstation for production line monitoring. Within the Industry 4.0 concept, the data can then be passed on to subsequent processes (e.g. a coating process) triggering their release. In the case of PCBs for which cleaning is planned prior to coating, if the data indicate that they are insufficiently clean, the coating process will be unable to start, and an error message will be displayed instead.

Statement

There is a broad range of monitorable process parameters that can be recorded and traced using standard or optional hardware. When implementing a process, carefully consider which variables are truly relevant for operability and traceability, and use these to control the process.

Exported data can connect to and trigger follow-up processes, though lack of standardization of data formatting can complicate this and represents, in this context, one of the greatest challenges facing the market.

Also, as far as the feedback of information from the steps downstream of the cleaning, such as the offline cleanliness checks or reliability data, etc., serving as the completion of the feedback control loop of the cleaning process (e.g. information on upcoming cleaner or filter changes at elevated residual contamination levels), optimisations can still be envisaged.

productronica, Booth A2-359

www.zestron.com


Zusammenfassung

Bei der Reinigung elektronischer Baugruppen steigt die Nachfrage nach der Prozessdaten-Erfassung sowie der Sicherstellung ihrer Rückverfolgbarkeit. Dies bringt Vorteile für die Kunden der Elektronikhersteller und auch für die Hersteller selbst, die dann auf Basis der erhobenen Daten ihre Prozesse verbessern können.

Résumé

Dans le domaine du nettoyage des composants électroniques, la demande ne cesse de croître en termes d‘acquisition de données process et de traçabilité. Les clients des fabricants d‘électronique mais aussi les fabricants eux-mêmes peuvent ainsi améliorer leurs processus sur la base des données collectées et en tirer des avantages majeurs.

Резюме

В сфере очистки электронных узлов возрастает потребность в системах сбора и отслеживания технологических данных. Это выгодно как заказчикам производителей электроники, так и самим производителям, которые на основе собранных данных могут совершенствовать свои процессы.

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