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Smart Automation: Odd-form Assembly—Dedicated Insertion Equipment Matters
Nolan’s Notes: Everyone Has Their Eye on India
eSMART Factory Conference 2019, Day 1
September 2, 2019 | Happy Holden, I-Connect007Estimated reading time: 11 minutes
Marybeth Allen of KIC Thermal Systems Inc. gave the fifth presentation about, “Industry 4.0: The Next Industrial Revolution—The Smart Factory.” This was another presentation about the benefits of creating a smart factory. Allen summarized how to:
- Use data to run the factory more effectively
- Use data analytics and optimization
- Acquire sensor-based technologies to obtain data
- Utilize industry connectivity, such as CFX
- Employ process visibility and traceability for sustainable production
Challenges include automating and integrating, which means:
- Factory-wide connection to all equipment (automatic and manual)
- Event data/connected devices
- Database/storage
- Search, filter, and analyze
- Web and mobile
- Enterprise Integration
- Networking/management
- Analytics
Thus, smart factory integration involves:
- Refined decisions
- Flexibility
- Production planning
- Machine-to-machine learning
- Corrective actions
- Efficiency
- Scheduled maintenance
- Product tracking and traceability
- Acquisition and processing of machine parameters
But the benefits to be achieved include:
- Immediate corrective actions
- Lower production costs
- More competitive operations
- Consistent quality
- Higher profits
- More happy customers
The final three speakers of the day had subjects on software systems and processes. The first was Dr. Bill Cardoso of Creative Electron who discussed "How AI Is Changing the Way We Make and Inspect Things." He gave an overview of how AI helps in the data collection and interpretation for automated optical inspection (AOI) and X-ray image analysis.
On the modern connected SMT assembly line, defect data is associated with paste application, component placement, and reflow. Statistical process control (SPC) can statistically analyze the data to identify drifts, trends, and other relevant quality issues. But how does data become information? The process still depends on operators catching the problem and requires an experienced line manager to debug the problem and start corrective action.
The replacement for this is data fusion and AI. AI software lowers the barrier to entry by training a fusion system using the AI engine. AOI and automated X-ray inspection (AXI) identify bad ball grid arrays (BGAs) or solder joints and the fusion dataset maps the source of the problem. The AI training progresses from operator warnings to fully automated, self-healing actions.
The end goal is more complete digital twin models that catch all of the problems and provide predictive results.
The second afternoon talk was by Greg Vance of Rockwell Automation on “Automating Detection of Pick-and-Place Nozzle Anomalies.” He recapped their progress by implementing smart factory data analytics—in this case, the analysis of pick-and-place nozzle monitoring. Rockwell Automation has 23 SMT lines operating 24/7 with up to 2,200 pick-and-place nozzles in use placing 5.5M components per day. Nozzle monitoring detects clogging and wear on the pick-and-place nozzles that lead to machine downtime, placement errors, and reduced quality.
The original software approach was Cloud-based software to consolidate and format streaming data, but there was latency and a lack of the single point of failure for the visualization. Using a new AI-based Cloud analytics software with machine learning, they created six pick-and-place nozzle monitor dashboards. The real-time analytics can self-correct or settle in placement performance while providing dynamic optimization and alters, even to their cellphones.
The impact of the new app and alarm brokering will lead to:
- Descriptive notifications to technicians indicating what machine, head, and nozzle has a problem, reducing troubleshooting time by 30 minutes
- Improved SMT line productivity by reducing machine stoppage and waste by up to 15%
- Resolved machine component pick difficulties that may result in an end-of-line defect
Future applications include in-circuit test (ICT) probe characterization, software process improvement (SPI) failure rate, AOI process failure rate, and product performance by work order over time.
The final talk was on "Smart PCBA Manufacturing: How Software-Powered Automation Increases Innovation and Reduces Production Time" by Shashank Samala of Tempo Automation. The startup in San Francisco focuses on developing PCB assembly automation from the IPC-2581 backbone. Their connection of solder paste, pick-and-place, AOI, and AXI for assembly to BOM sourcing software, fabrication simulation, inspection defect detection, and design records is now eclipsed by CFX. They started before CFX was developed and were surprised by the rapid development and implementation of CFX. Fortunately, since CFX is open, they can rapidly adapt their unique brand of software to the CFX format.
The day ended with a panel discussion moderated by Trevor Galbraith of Global SMT and Packaging with panelists Michael Ford, David Meyers, Michael Schuldenfrei, and Greg Vance who discussed the topics covered during the day.
The conference was co-organized by SMTA and Global SMT, and presentations will be available to SMTA members after September in the SMTA Knowledge Base.
References
Dr. Faith McCreary and Dr. Irene Petrick, “Industry 4.0 Demands the Co-Evolution of Workings and Manufacturing Operations,” Intel Corporation, Q1 2018.Share on:
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