i4.0 today

Yxlon International




By Ragnar Vaga, Global Business Development Manager, Yxlon International

The digital transformation with concepts like Industry 4.0, Smart Factory or the Internet of Things will change production, work processes and business models in electronics manufacturing radically and forever. It is all about connectivity, gathering and the exchange of big data. However, big data itself does not bring any specific value to the end user, it needs to be interpreted, understood and acted upon. Collecting all possible characteristics and statuses of the production line will end up with a big mess, unless there is a way to collect and process only relevant data in real time. Then visualize these on a sophisticated Manufacturing Information System (MIS) dashboard and initiate proactive measures to improve the quality of the production. These proactive measures should be as automated as possible. The aim being, to keep the process within the operating window, where acceptable quality and no scrap is produced.

However, when talking about completely integrated production environments and proactive decision making, three critical aspects should be considered. It is a quality of the raw data, availability of powerful enough analytical tools and the ability of the systems to find and fix the root cause of the issues. Without these, we cannot talk about real Industry 4.0 solutions, all of these requirements have objective limitations today:

Integrated sensors should have high accuracy and sensitivity

In the connected smart factory, all machines and systems become essentially smart sensors, collecting all possible data from the production line and the boards themselves.

Therefore, the accuracy and sensitivity of those sensors is very critical, especially in quality control systems like AOI and AXI. Without diminishing the strong characteristics of the in-line inspection equipment, these still need assistive technologies for the verification of possible false faults.

Image 1

For example, real 3D AOI is a perfect inspection tool to verify many characteristics, placement accuracy, part numbering, polarity, co-planarity or warpage of the components. However, the system is not able to answer to the question “This QFN is warped, but are the joints acceptable?” or “This BGA is lifted, but are the joints acceptable?” Wouldn’t it be great if high resolution at-line x-ray could go directly to this suspicious area and the operator could verify the problem and make an informed decision on potential soldering problems of bottom terminated components (BTC) with co-planarity issues like in Images 2 and 3 below, where a loose small component was found underneath the BGA.

Image 2
Image 3

The in-line x-ray inspection systems try to find HoP defect by looking at BGA balls in at least 3 different positions – the PCB Pad slice, the BGA Mid-ball slice and The Package Slice. The advanced algorithms and adjustable magnification allow defining if the particular ball is smaller or bigger than its neighbours. With challenging components the number of slices can be even increased, but the time taken also increases. Or they lack a necessary resolution which is required to verify Head on Pillow (HoP) defect. The in-line x-ray inspection system can detect HoP joints at standard magnification but as BGA ball size decreases; this becomes much harder and it is more likely to miss HoP defects.

Head on pillow slices
Image 4

However, most of in-line x-ray inspection systems have rather high false fail rates and these findings should be confirmed either on a verification station or inspected again on a high-end at-line x-ray system.

The reason is simple, the proper search of HoP defects requires high-resolution oblique view images (Image 5). These can be generated by an off-line or at-line x-ray system.

Head in Pillow
Image 5

Last but not least, as components become smaller and smaller, dies shrink proportionally so the thermal stress increases. As components become thinner, so thermal issues increase and can lead to more component warpage, but more importantly voiding becomes a much bigger issue as thermal pads need to move a higher percentage of heat and voiding in the pads now becomes a reliability killer and causes failures in the field due to the cumulative effects of repeated thermal stressing on the die. Therefore the accuracy and sensitivity of inspection systems is very critical.

Integrated machines should become self-learning and proactive systems

As said earlier, smart manufacturing should be a proactive and independent decision-making environment where connected systems or machines will “talk” to each other. That “discussion” is, however, based on algorithms.

By definition an algorithm can give us only one single answer. But does this provide us the right answer or one from three or four or five alternatives?

Will it provide the same response every time or different ones for the same issue? Many MIS systems are not ready to manage big data, due to the lack of smart analytic tools. Without human intervention to make those critical decisions, based on knowledge and experience, we still cannot talk about completely effective and efficient smart production. Therefore the reliable solution combines human brains and algorithms together, allowing Process Managers to make informed decisions after seeing all the data from various collection points. This data is relayed to a single screen where they also have historical information and everything needed to make a truly informed decision. This is definitely a Smart Solution, it is not a “Lights Out” fully automated Smart Factory but it is much better than many factories today. It allows real time monitoring of production flow and the changing of settings and limits to ensure that the product produced remains within the optimum process window, giving potentially 100% acceptable product coming off the line, at least in terms of assembly defects. It is also a big step towards ‘full automation’ and therefore well worth embracing as a way of improving yields and reducing costs.

Connected at-line x-ray systems

An at-line system is essentially an off-line system what is linked to the production line and placed beside it, allowing real time response to issues and making the x-ray system a tool of the production and QA teams and not simply a test machine in a lab, used by QC staff.

We have been working on linked inspection solutions since 2015.

Management Information System
Image 6

The standardization of the communication protocols between machines in the production line and also with the MIS is the primary challenge. It is becoming obvious that all systems in the production line should be connected in order to establish board tracking over the entire production line without the necessity to use multiple barcode readers or perhaps even barcode readers at all. This will allow the MIS system to collect process data and traceability data per board or batch without information loss or throughput loss. This kind of standardized horizontal connection will also reduce the investment cost and minimize effort on product change.

The primary challenge for Industry 4.0 is standardization

Our solution is simple to implement and therefore reliable. The at-line x-ray can be connected to in-line 3D AOI or in-line x-ray inspection system directly and becomes a smart verification tool where only questionable and unsolved faults will be transferred for repeat inspection on a high-resolution at-line x-ray system. The inspection results can be stored on the system PC, but can be also exported to the customer’s MIS. The connectivity of the at-line system is based on Internet Protocol (IP) via Transmission Control Protocol (TCP). Further use of data (collation and visualization of results from different inspection systems) depends on the end customer’s demands and capabilities.

The general task is to provide a dashboard view to the Process Manager who can track down the possible problem areas and initiate proactive measures to improve the quality of production, before rejects or scrap units are produced.

V-One dashboard
Image 7

For that purpose the Hermes Standard (https://www.the-hermes-standard.info/) has been developed and it could become an industry wide communication protocol. Yxlon has joined to this initiative as a first at-line manufacturer. Although the first version of Hermes is focused on enhancement of SMEMA by extending the interface to communicate unique identifiers for the handled printed circuit boards (PCBs), equipment identifiers of the first machine noticing a PCB, barcodes etc, increased benefits for off-line system manufacturers may occur in the next versions of the Hermes Standard.

Besides standardization of machine to machine connection it is as important to standardize connections to the customers’ MIS. While there is an ongoing competition on the position of commonly used standards, the major EMS companies tend to avoid third party platforms and expect a direct connectivity of production systems to their Management Information Systems. This open source solutions should meet the following requirements:

  • Smart Connectivity, being able to connect the systems to any available and upcoming MIS via a network (TCP)
  • Smart Maintenance, being able to send events/status from Yxlon x-ray systems to any upcoming MIS via a network (TCP)
  • Smart Factory, being able to provide added value (automated inspections like Smart Loop) from our systems to any upcoming MIS and or Machine to Machine via a network (TCP)


  • The images 1, 6 and 7 are courtesy of ViTrox. Yxlon is working in partnership with ViTrox on its M2M connectivity solutions v-one.my.
  • Keith Bryant, Yxlon, Global Sales Director, Electronics

The leading supplier of industrial X-ray systems