Chan Pin was appointed as Executive Vice President & General Manager, K&S' Products and Solutions in December, 2019.
He joined K&S in 2014 as Vice President of Wedge Bonders business unit and has successfully turnaround the business and led the team to higher growth by diversifying the business into the battery bonding market.
Chan Pin is a technology industry veteran with more than 27 years of engineering and operations experience in the semiconductor and electronics industry. He started his career first as a Process and Test Engineer at Motorola Pagers and Cellular group and pioneered multiple factories in Asia before advancing to the role of Manufacturing Manager at Flextronics. In 1999, Chan Pin joined KLA-Tencor and held a number of diverse positions, including Senior Technical Director of Engineering and General Manager of Strategic Business Unit in Greater China. Chan Pin then pioneered the efforts of starting the MEMS factory in Singapore when he became the Vice President of Sales and General Manager at Form Factor. In 2010, he was the Global President & CEO at Everett Charles Technologies, managing and leading in test and probe technologies.
Chan Pin received his bachelor's degree in Electrical Engineering and Computer Science from the State University of New York at Buffalo and a master's degree in Business Administration from the University of Leicester, United Kingdom.
Factory Video Tour:
Digital Transformation Journey in Equipment Manufacturing
The video will introduce to the audience an introduction of the digital transformation journey for Kulicke and Soffa Equipment manufacturing. The video will describe our manufacturing operation analytics and decision making from supply chain to our customers. The use of data automation and data Analytics to drive decision making analytics. Along the theme of sensing, connecting and predicting, Kulicke and Soffa will show examples of how we develop analysis and goal setting to define action plan to drive productivity and yield improvements. The use of Smart manufacturing systems deployment in semiconductor equipment manufacturing to support the business goals. Machine learning will also be highlighted toward the analytics or predicting topics.