The back end of line (BEOL) workflow in the mask shop still has crucial issues throughout all
standard steps which are inspection, disposition, photomask repair and verification of repair
success. All involved tools are typically run by highly trained operators or engineers who setup
jobs and recipes, execute tasks, analyze data and make decisions based on the results. No matter
how experienced operators are and how good the systems perform, there is one aspect that
always limits the productivity and effectiveness of the operation: the human aspect.
Human errors can range from seemingly rather harmless slip-ups to mistakes with serious and
direct economic impact including mask rejects, customer returns and line stops in the wafer fab.
Even with the introduction of quality control mechanisms that help to reduce these critical but
unavoidable faults, they can never be completely eliminated. Therefore the mask shop BEOL
cannot run in the most efficient manner as unnecessary time and money are spent on processes
that still remain labor intensive.
The best way to address this issue is to automate critical segments of the workflow that are
prone to human errors. In fact, manufacturing errors can occur for each BEOL step where
operators intervene. These processes comprise of image evaluation, setting up tool recipes, data
handling and all other tedious but required steps. With the help of smart solutions, operators
can work more efficiently and dedicate their time to less mundane tasks. Smart solutions
connect tools, taking over the data handling and analysis typically performed by operators and
engineers. These solutions not only eliminate the human error factor in the manufacturing
process but can provide benefits in terms of shorter cycle times, reduced bottlenecks and
prediction of an optimized workflow. In addition such software solutions consist of building
blocks that seamlessly integrate applications and allow the customers to use tailored solutions.
To accommodate for the variability and complexity in mask shops today, individual workflows
can be supported according to the needs of any particular manufacturing line with respect to
necessary measurement and production steps. At the same time the efficiency of assets is
increased by avoiding unneeded cycle time and waste of resources due to the presence of
process steps that are very crucial for a given technology.
In this paper we present details of which areas of the BEOL can benefit most from intelligent
automation, what solutions exist and the quantification of benefits to a mask shop with full
automation by the use of a back end of line model.