Assembly line balancing: Joint precedence graphs under high product variety

Previous approaches for balancing mixed-model assembly lines rely on detailed prognoses of the demand for each model to be produced on the line (model-mix). With the help of the anticipated model-mix a joint precedence graph for a virtual average model is deduced, so that the mixed-model balancing problem is reduced to the single-model case and traditional balancing approaches can be employed. Today's ever increasing product variety often impedes reliable prognoses for individual models. Instead, forecasts for the estimated occurrences of each product feature (e.g., percentage of cars with air conditioning) are merely obtainable. This paper shows how the generation of joint precedence graphs is to be altered to account for this fundamental change in information. This way, a balancing of mixed-model assembly lines which are confronted with a high degree of product variety is enabled.