Tait are one of NZ’s largest electronic goods manufacturers. They utilise a number of robotics lines to build the Surface Mount Technology (SMT) boards that make up their product range. The short-run size nature of the Tait product line and market means that there are large efficiency gains available if product similarities can be understood and this learning is applied to optimising the robotic line set up.
Approach
This project grouped surface mount technology (SMT) products such that the overall component mix within each group was optimised for a single robotic SMT line. This resulted in fewer changeovers and therefore greater productivity. The main tools and approaches being utilised from the I4 suite are:
High volume data capture and time-series tracking
IoT connectivity of systems
Machine Learning to divide the entire product base into homogenous groupings
Results
The first phase of this project is complete, Tait is now using the groupings determined by the machine learning to optimise their robotics production lines.