On Equilibrium Probabilities for the Delays in Deterministic Flow Lines With Random Arrivals

While flow line models have been studied for decades, excepting some cases with three servers or less, their equilibrium probabilities remain elusive. As such, approximations based on aggregation or decomposition methods are generally employed. In this paper, by focusing on flow lines with deterministic service durations and a renewal arrival process, we develop exact methods for steady-state analysis. Our starting point is the investigation of recursions for customer delay based on exact decomposition methods. We demonstrate that the delay a customer faces in each server possesses a Markovian property. For discrete-time flow lines, we obtain a multidimensional discrete-time time-homogeneous Markov chain for the delays; there are an infinite number of balance equations for the equilibrium probabilities. Exploiting a similarity between our system and the GI/D/1 queue allows us to reduce these to a finite number of balance equations that can be solved numerically. We also investigate the implications for continuous-time flow lines and consider an example inspired by production time windows in semiconductor manufacturing. To our knowledge, these are the first results that allow one to exactly obtain the equilibrium probabilities in flow lines consisting of more than three servers.