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Worker coordination policies in parallel station systems: performance models for a set of jobs and for continuous arrival of jobs Varying workloads and uncertain processing times in parallel assembly cause idle times for skilled, high-cost workers. This idleness can be avoided and the utilisation of the workers improved by allowing workers to move between the stations to help each other. Worker movement between assembly stations needs efficient and feasible coordination, and therefore, this paper compares four different worker coordination policies: no helping, floater, pairs and complete helping. The dynamics of the policies are modelled by studying the parallel assembly as a continuous-time Markov process. The system is studied with two different job release cases for non-identical jobs (customised products). In the first case, a given number of jobs have to be completed by the entire system. In the second case, new jobs arrive with a Poisson-distributed rate. The models assume that when one worker helps another, their collaborative inefficiency reduces the productivity. The models are used in numerical experiments to compare the performances of worker coordination policies as average job cycle times. The main conclusions from the results suggest the use of the complete helping policy in minor collaborative inefficiency conditions, especially with a given set of jobs. The pairs policy is a reasonable alternative in major inefficiency conditions with the continuous arrival of jobs.

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