Experiments suggest that using head-up displays like Google Glass to support parts picking for distribution results in fewer errors than current processes. Making Glass opaque instead of transparent further improves selection efficiency.

Wearable and contextually aware technologies have great applicability in task guidance systems. Order picking is the task of collecting items from inventory in a warehouse and sorting them for distribution; this process accounts for about 60% of the total operational costs of these warehouses. Current practice in industry includes paper pick lists and pick-bylight systems. We evaluated order picking assisted by four approaches: head-up display (HUD); cart-mounted display (CMD); pick-by-light; and paper pick list. We report accuracy, error types, task time, subjective task load and user preferences for all four approaches. The findings suggest that pick-by-HUD and pick-by-CMD are superior on all metrics to the current practices of pick-by-paper and pick-by-light.

No abstract

No abstract

No abstract