Modelling the impact of lot priorities on production cycle times: a data-driven approach

The production of electronic chips from silicon wafers in semiconductor manufacturing is widely regarded as one of the most complex industrial processes. This production context is characterised by high global demand, intensive utilisation of costly equipment to ensure profitability, and consequently, a high level of saturation that generates long queuing waiting times. Combined with the hundreds of operations required to produce a single lot, this leads to cycle times spanning several weeks or even months. To meet the varying cycle time requirements of different products in such a saturated environment, a priority queuing discipline is implemented, using a mix of different priority classes. In this context, and using data-driven models, this paper characterises the impact of the priority mix on the cycle times of products in each priority class within a wafer manufacturing facility. A fluid analytical queuing model is proposed, which extrapolates the effects of different priority mixes beyond the observed data range, using priority scores estimated from historical data. The model reveals a linear relationship between the ratio of hot lots and the speed-up of priority classes, defined as the inverse of their relative mean queuing waiting time. The results are consistent with findings reported in the literature.