Powering the Future: Why True Ceramic Circuits Are Not Just ‘Better PCBs’
Global Sourcing Spotlight: The Global Quality Gap—Why Consistency Wins the Contract
Knocking Down the Bone Pile: Precision Milling of Underfilled SMT Components
Book Excerpt: The Printed Circuit Assembler’s Guide to...Factory Analytics—Unlocking Efficiency Through Data Insights
By Julie Cliche-Dubois, Cogiscan
Chapter 1: Getting and Processing Factory Data
Despite being a widely discussed topic since the advent of Industry 4.0 initiatives, the implementation and utilization of analytics tools by electronics manufacturers has been slow, with an adoption rate significantly lower than anticipated. Most of this stagnation can be attributed to the fact that getting data from the factory floor simply isn’t as straightforward as it should be. This “connectivity conundrum” plagues circuit board assembly manufacturers; worldwide, there is an enormous install base of a variety of machines of varying brands, models, and legacies that communicate and output data in different formats and protocols.
Further compounding the complication of shop-floor data extraction is the large enterprise software ecosystem that relies on access to that data. Electronics manufacturers are using a wider variety of software systems, including MES/MOM, PLM, ERP, IIoT, and APS, to effectively run and manage their production operations. All these systems need shop-floor data and an effective way to seamlessly share and exchange that data, oftentimes simultaneously, to both perform properly and provide meaningful insights. This labyrinth of data exchange requires a strong, open, and flexible connectivity platform with the ability to send factory data in a variety of output formats to multiple hosts concurrently.
The factory floor is a gold mine of data; every machine produces key information that can help provide a clear picture of real-time production status as well as reveal insights on potential issues. It's just there, at your fingertips, but feels out of reach. There are quite a few reasons that explain why it’s so difficult to get data, including configuring machine licenses correctly, understanding each machine’s native output format, as well as normalizing that output data for external consumption.
