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OCTOBER 2023 I SMT007 MAGAZINE 71 trol capabilities for screen printers. Key tech- nologies include: • 3D SPI: is technology uses 3D measurement techniques to precisely capture the height and volume of solder paste deposits. • Machine learning and artificial intelligence (AI): Some SPI systems incorporate machine learning algorithms and AI to analyze historical data, identify trends, and make proactive adjustments to the printing process. Automated Optical Inspection (AOI) AOI systems are crucial for verifying compo- nent placement, solder joint quality, and over- all PCBA integrity. Key technologies in AOI include: • Advanced vision systems: AOI systems use high-resolution cameras, advanced optics, and lighting techniques to capture detailed images of PCBAs. ese images are then analyzed using sophisticated algorithms to identify defects and deviations from quality standards. • Machine learning and pattern recognition: Some AOI systems employ machine learning and pattern recognition algorithms to continually improve their defect detection capabilities, adapting to new product designs and variations. The Vital Role of Reflow Process Inspection (RPI) To bring reflow up to the level of automa- tion and precision seen in SPI and AOI, an approach has emerged called reflow process inspection (RPI). ese embedded inspection systems for thermal processes were originally invented and developed by KIC, an industry leader in thermal process solutions for elec- tronics manufacturing. Most available systems today are based on KIC technology. Reflow Process Inspection (RPI) An RPI system consists of an array of embed- ded thermocouple sensors along the process path within the reflow oven tunnel. ese sen- sors measure temperature, track the conveyor speed, and monitor each PCBA as it enters the oven. By continuously and automatically tracking and calculating the temperature pro- file for every production PCBA, RPI elimi- nates the need for manual interventions and downtime required for manual profiling meth- ods. Programming an RPI system is as straight- forward as using a datalogging profiler device. Engineers run a baseline temperature pro- file of the PCBA, allowing the system to learn and adapt to the specific requirements of the assembly. Once programmed, the RPI inspec- tion brings automation and real-time process control to the reflow soldering process, ensur- ing consistency and quality in every PCB. • Machine learning and artificial intelligence (AI): A true RPI system like KIC's has predictive learning capabilities to recommend oven recipe settings with just the PCB dimensions and weight. Furthermore, the on-the-fly AI in the RPI system actively tracks process Cpk, provides temperature profile data for each assembly, and has connectivity capabilities to include critical real-time reflow profile data in the decision feedback loop. It operates with CFX, Hermes, and other standards as well as API connectivity to any MES system. • New sensing technology from KIC: Until recently, there has only been indirect detection of convection changes through monitoring the production temperature profile or possibly monitoring fans. But by measuring the production boards' temperatures directly, KIC reflow process inspection systems will have the ability to know how the oven convection changes over time. KIC has new sensing technol- ogy to measure every production board