FEATURE CONTRACT MANUFACTURING
STAYING AHEAD THROUGH DATA ANALYTICS By Joe Booth, Altus Director Business Devlopment & Marketing
C
ontract Electronics Manufacturers (CEM) has and always will be an incredibly competitive landscape in which to do business. As a service provider, CEMs rely on external customers and the sales team to ensure that order books are full and production lines busy. A large issue that CEMs face is competition. There are many companies offering a similar service both nationally and internationally, all jostling for the same business. Even when the contract is secured, there is relentless pressure to keep the customer happy whilst managing costs and efficiencies to ensure that the project is profitable and up to standard. CEMs are always asking themselves; how do I differentiate from the rest? How can I bring my costs down? How can I work smarter and more efficiently? There are many strategy-based answers to these questions, and they can be approached in many ways. This article will look at differentiation from competitors by supplying additional value to the end customer through data analytics. By ‘value’, I mean by providing insight and increasing product quality and by ‘data’ I mean fully 3D measurement data from the inspection tools of the production line.
THE KEY TO DATA ANALYTICS Imagine this scenario, you work in a CEM and have a meeting with an important customer looking to significantly increase their production and extend their contract by three years. They have been a customer for six months and during this time have developed and increased their product line and are now finally expecting large volume orders. They are looking at a local rival as a comparator to your offering and it is crunch time. Your CEO is under pressure and your competition has a great reputation. Even with this burden you are confident because over the last month you have seen their production yield reach 100 per cent pass rate, efficiencies across
32 JUNE 2020 | ELECTRONICS
their product build have brought the tact time down 20 per cent and their quality manager emailed you last night to say ‘your team have done a great job!’. This sounds like the ideal situation so how can you use data analytics to ensure this always happens? Using Koh Young, the leading 3D measurement-based inspection equipment and solutions provider as an example, let’s look at the importance of data analytics. The key to data analytics and why Koh Young has been so successful in selling both AOI and SPI, is how they acquire data and turn it into customer value. Koh Young systems use 100 per cent light measurement of the PCBA utilising a Fringe Moire technology. With each field of view an AOI system takes 32 quantifiable measurements (4 measurements at each position with 8 projectors) all of which are data points to be aggregated. This results in producing the most accurate and reliable inspection available and is why false calls are so much less than with 2D hybrids (subjective calls).
Reducing false call rate is important,
but for CEMs it is also crucial to look at valuable insights, increasing yields and tackling quality issues. This is where the AOI and SPI system comes into their own utilising statistical software packages like KSMART and the power of machine learning algorithms.
DATA COLLECTION – ADDING VALUE In a world of IoT communication and data collection, it was obvious that the only path for AOI and SPI was to capitalise on the data collection, repurposing the content into a deliverable that can add value to the end customer. Based on this fact, the key direction of inspection companies was to invest heavily in software and Graphical User Interface (GUI) to translate the content. Investment in the development of AI capabilities and machine learning
for statistical analysis was also key. The aim of this investment was to create a platform allowing Process Engineers to use real time data from their production. Using the software and data analysed to make data driven process improvement decisions and enhancing upstream and downstream processes. Not it has improved? But it has improved by X! Koh Young KSMART is a modular based software solution allowing customers to access content sets through their GUI. The modular nature allows users to pick and choose what information can be seen so that the package is tailored to information benefitting specific requirements. Previously if there was a problem on a PCB such as a component of difficulty, decisions were made from an engineer’s knowledgeable eye and adjustments made through previous subjective experience. This made the process an educated finger in the air. With KSMART, process engineers can recall large data sets from real time production and use that information to make data derived decisions. KSMART can report the top components causing problems so they can be actioned proactively and brought to the customers attention. Furthermore, engineers can monitor their chosen actions closely to adjust processes to ensure an improvement to overall yield. Koh Young has gone one step further into the future with the KSMART Process Optimiser. This module designed for SPIs and solder printers takes an inspection system (SPI) in connection with a configured screen printer to take real time inspection information and form an automated feedback loop to improve the printing programme all without human intervention! The KPO programme automatically enhances the printing performance variation and therefore the quality of the product being assembled. This SPI unit has progressed from, letting the operator know if the results are ‘good/bad’ into evaluating the ‘good’ board information further and recommending improvements to the upstream processes. Adapting to data and the analysis of
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data that is available can be immensely valuable to a contract manufacturer in modern times. Using the data will increase the quality of the customer’s product and save vital time internally by increasing yields and creating automatic efficiencies. These are capabilities that those in the 2D world cannot utilise and a differentiator amongst the crowd.
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