ASRS sizing for recreating automotive assembly sequences

Since a mixed model assembly line's efficiency depends on the sequence of jobs moving down the line, manufacturers spend considerable effort optimizing the sequence of jobs entering the plant. In automotive assembly plants however, repair loops and parallel stations scramble the sequence before it reaches the final assembly stage. Many automotive assembly plants use an automatic storage and retrieval system to revamp the scrambled sequence before final assembly. One plant even goes so far as to reconstruct the original sequence by completely undoing the sequence scrambling. We derive a relationship between the sequence scrambling information, the variety of model-colour configurations, and the size of the automatic storage and retrieval system needed to reconstruct the initial sequence. We enunciate this new ASRS sizing problem actually facing industry, show how to model it, present a solution approach, and demonstrate the approach on actual sequence scrambling data from an automotive assembly plant.