Consumer Products
Engineers and analysts working in the consumer product sector work with high volumes yet much shorter product life cycle- one to two years. Given the latter and the potential need to re-spin silicon design within weeks of first silicon, a yield management system needs to assist engineers and analysts in managing the uncertainty of that comes with new product introductions. Both fabless companies and IDMs require data from split lots to evaluate silicon over a process range. Yet sometimes surprises in yield can only be seen when companies ramp a new product for manufacturing. In this scenario engineers require a toolbox of analytics that enables them to promptly determine low yield causes. Planners/analysts need to route their products through their supply chain and having accurate yield numbers enables order of wafer starts and packaging orders.
At the foundation of making decisions based upon large amounts of data is the need to determine for clean data- data that is complete and accurate. If your yield management solution does not support the processes to do enable stable data, then who cares if you have deep learning in your analytical toolbox.
Tool functionality specific to this industry: Automated Assembly map generation, production yield reporting, yield calculation flexibility, Statistical process control. Cross Work Center Correlation, Log Genealogy.