Data has always played a role in semiconductor and electronics manufacturing. In the semiconductor industry, data was initially collected manually to track WIP (work-in-progress). In many instances, the analysis was performed in a very manual “ad-hoc” fashion by domain experts.
Over the years, data collection has become much more automated. But even with this improvement in the ability to collect data, it has been estimated that more than half of it is never processed. And of this data that is processed and stored, most of it is never again accessed.
Moving forward, data volume and velocity is increasing rapidly, as more sensors are added and data collection rates on process tools are increasing by several orders of magnitude.
Recently there has been lots of interest and progress in the fast-growing field of Predictive Analytics. Thanks to the emergence of the ability to harness massive parallel processing architectures (Big Data) and the advancement of machine learning algorithms, we are now able to gain insights and make predictions using massive amounts of data at speeds that make such approaches relevant and realistic. At StreamMosaic, we will bring to bear the latest in machine learning and predictive analytics technologies to get the most out of your available data.