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APRIL 2020 I SMT007 MAGAZINE 13 Reference 1. J. Manyika, M. Chui, M. Miremadi, J. Bughin, K. George, P. Willmott, & M. Dewhurst, "Harnessing Automation for a Future That Works," McKinsey Global Institute, January 2017. Dr. Jennie S. Hwang—an interna- tional businesswoman and speaker, and a business and technology advi- sor—is a pioneer and long-stand- ing contributor to electronics hard- ware manufacturing as well as to the environment-friendly lead-free electronics imple- mentation. Among her many awards and honors, she was inducted to the International Hall of Fame—Women in Tech- nology, elected to the National Academy of Engineering, an R&D-Stars-to-Watch, and YWCA Achievement Award. Having held senior executive positions with Lockheed Martin Corp., Sherwin Williams Co., SCM Corp, and CEO of International Electronic Materials Corp., she is currently CEO of H-Technologies Group, providing business, technol- ogy, and manufacturing solutions. She is the Chairman of the Assessment Board of the DoD Army Research Labora- tory, serving on Commerce Department's Export Council, National Materials and Manufacturing Board, NIST Assess- ment Board, Army Science and Technology Board, vari- ous national panels/committees, international leadership positions, and the board of Fortune-500 NYSE companies and civic and university boards. She is the author of 500+ publications and several books, and a speaker and author on trade, business, education, and social issues. Her for- mal education includes four academic degrees as well as the Harvard Business School Executive Program and Columbia University Corporate Governance Program. For more information, please visit www.JennieHwang.com. To read past columns or contact Hwang, click here. works at higher speeds, using smaller anten- nas. Advanced sensor technology and other embedded technology aid the materialization of unmanned operation in pertinent functions, offering flexibility of on-demand production throughput. Benefits are evidently abundant, yet chal- lenges tenaciously remain. With the massive amounts of data from different checkpoints, the challenge in data management takes the front and center seat, including ensuring the quality of data, classi- fying the data, cleaning the data, interpreting the data, and analyzing the data. The ready availability of workers who have suitable skill sets is another challenge. Although AI serves as the eyes and ears of factory operation and can learn quickly to alert irregularities and to initiate remedial actions, it has to be "trained" and to gain "experiences" to do the job well, such as recognizing production defects with- out misses and with required accuracy to gain the ability to know when and how to alert humans for necessary intervention. To put a business case forward, a smart fac- tory will be able to be smart enough to deliver intended beneficial results. Then, the question becomes, "How smart is smart enough to a specific operation?" Each company (or operation) needs to for- mulate its plan to garner the merits of intel- ligent manufacturing in establishing a smart factory. As AI and sensor technology continue to evolve, staying in sync with the technolo- gies demands systematic, deliberate, and pru- dent endeavors. SMT007