Case Study: Flex Smart Factory at Fuyong

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Now, we have machine connection, defect overall process mapping, data automatic feedback to SMT process machine and process improvements based on testing data. Units per hour have increased from 200 to 250 in a short time, and productivity has been improved.

SPC data and analysis have given predictability to the process. Achievements in quality and productivity from April to July of 2015 for Phase I of the project are listed in Table 1 showing the LEAN tools applied: 5W, Fishbone, and value added identification.

Average yield (Final Pass Yield) increased from 99.1 % to 99.44% in the last 3 months.

Figure 11 shows the main SPC data and results from the SMT line. With SPC data/results monitoring, assembly yields are improved significantly.

Taking action predictively with SPC as shown in Figure 12, the FPY (first pass yield) of SPI increased from 98 to 99 percent, AOI from 99.2 to 99.7 percent and ICT from 96 to 98 percent in a short time.

Figure 11: SPC – Predictive

Figure 12: SMT – Predictive

In the past six months, good progress has been made in the manufacturing environment traceability as shown in Figure 13. Traceability has been implemented for main machine parameters of printer, solder paste inspection, pick and place, reflow, AOI, wave solder and ICT for each board. There is good correlation information to analyze processes for defect root cause with this information and process actions.

Figure 13: Manufacturing Environment Traceability

Conclusions

There are five smart levels for the Smart Factory:

• Shop Floor Interconnection
• Supply Chain Interconnection
• Front Office Interconnection
• Back Office Interconnection
• Control Tower.

The Control Tower is through the whole Smart phases. Each phase connection result will be put into the Control Tower for more smart control to the whole factory. Figure 14 is the company road map for the Smart Factory.

Our conclusion for the Smart Factory is as below:

1. Standardization is the basic for Smart.
2. Only standardization can make connection.
3. Smart Factory start from connection.
4. Smart Factory is driven by connected data.
5. Smart Factory’s key approach is predictive.
6. Software first, Hardware second.
7. Data automation first, Hardware automation second.

It is nice to see what practices and achievement we have today; however, there are still many challenges on the way. The company is confident on working together to make a good Smart Factory in the SMT field soon.

Figure 14: Roadmap – SMART Factory

Acknowledgements

The authors would like to thank the engineering and production teams of the company site, AEG (Advanced Engineering Group), our customers and vendors for their strong support for this successful project. Special thanks also go to Dr. Zhen (Jane) Feng for her strong support; also to Mr. LC Tai and Mr. Hill Zhang, for their many contributions during this Smart factory journey.

References 

1. Engineering Team, "Flex Fuyong Smart Factory Roadmap", Flex Report,” September, 2015.

2. R. Rowland, "What is Quality?" SMT magazine, December, 2001.

3. Alejandro Castellanos, Zhen (Jane) Feng, Ph. D., David Geiger, Murad Kurwa, "Head in Pillow X-ray Inspection", SMT magazine, May, 2014.

4. Andy Liu, ChengYong Zou, Jeff Li, CK Tan, Zhen (Jane) Feng, Ph. D., David Geiger, Sunny Liu, JP Wen, Jimmy Xiao, Louis Liu, Evstatin Krastev, Ph. D., "X-Ray inspection methods for Controlling PCBA Potting Process – 2DX and Partial Angle Computer Tomography", SMTA Pan Pacific Proceedings, January, 2016.

Authors

Jeff Li, Leo Xie, Andy Liu, Romen Luo, Jiang Wang, Yenny Zhu, C.K. Tan, Flex International

This article was first presented at the technical proceedings of IPC APEX EXPO.

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