In bucket brigade" manufacturing, such as recently introduced to the apparel industry, a production line has n workers moving among m stations, where each w orker independently follows a simple rule that determines what to do next. Our analysis suggests and experiments con rm that if the workers are sequenced from slowest to fastest then, independently of the stations at which they begin, a stable partition of work will spontaneously emerge. Furthermore, the production rate will converge to a v alue that, for typical production lines, is the maximum possible among all ways of organizing the workers and stations.

The primary challenge for an urban bus system is to maintain constant headways between successive buses. Most bus systems try to achieve this by adherence to a schedule; but this is undermined by the tendency of headways to collapse, so that buses travel in bunches. To counter this, we propose a new method of coördinating buses. Our method abandons the idea of a schedule and even any a priori target headway. Under our scheme headways are dynamically self-equalizing and the natural headway of the system tends to emerge spontaneously. Headways also become self-correcting in that after disturbances they reëqualize without intervention by management or even awareness of the drivers.We report on a successful implementation to control a bus route in Atlanta.

"Bucket brigades" are a way of sharing work on a flow line that results in the spontaneous emergence of balance and consequent high throughput. All this happens without a work-content model or traditional assembly line balancing technology. Here we show that bucket brigades can be effective even in the presence of variability in the work content. In addition, we report confirmation at the national distribution center of a major chain retailer, which experienced a 34% increase in productivity after the workers began picking orders by bucket brigade. B ucket brigades are a way of coordinating workers who progressively assemble a product along a flow line. Each worker follows this simple rule: Carry work forward from station to station until someone takes over your work; then go back for more. When the last worker completes a product, he walks back upstream and takes over the work of his predecessor, who then walks back and takes over the work of his predecessor, and so on until the first worker begins a new product at the start of the line. No unattended work-in-process (WIP) is allowed in the system. Workers are not restricted to any subset of stations; rather, each is to carry his work as far toward completion as possible, except that workers may not pass one another. This means that, at least in principle, a worker might catch up to his successor and be blocked; the bucket brigade rule requires that the blocked worker remain idle until the station is available. (As we shall see, the art of implementing a successful bucket brigade is to make such events unlikely.)The final requirement of bucket brigades is that the workers be sequenced from slowest to fastest along the direction of material flow. When these requirements are met, work is paced by the fastest worker, who triggers each successive series of walk-backs. The result is a pure pull system. Bucket brigades are distinguished from similar worksharing protocols, such as the Toyota Sewing System (TSS), by insisting on the total abolishment of any a priori work assignment or zones that might restrict the movement of the workers, and by requiring that the workers be sequenced from slowest to fastest along the direction of material flow.The distinctive and valuable feature of bucket brigades is that they are self-balancing; that is, a balanced partition of the work will emerge spontaneously, which reduces the need for traditional industrial engineering technologies of time-motion studies, work-content models, and assembly line balancing. Moreover, under quite general conditions the emergent balance results in the maximum possible rate of production. Finally, the simplicity of bucket brigades makes them easy to implement and so to realize these benefits. Bartholdi and Eisenstein (1996) analyzed the performance of bucket brigades performing high-volume assembly of a mature product, for which a deterministic model of work content was appropriate. Here we extend this analysis to a stochastic model of work content and show that the dynamics and production rate will ...

We describe all possible asymptotic behavior of "bucket brigade" production lines wilh two or three workers, each characterized by a constant work velocity. The results suggest wariness in interpreting simulation results. They also suggest a strategy for partitioning a workforce into effective teams to staff the lines.Subject classifications: Production/scheduling, line balancing: self-balancing bucket brigade lines. Mathematics. Fixed points: asymptotic behavior ol bucket brigade lines.

O ne way to organize workers that lies between traditional assembly lines, where workers are specialists, and craft assembly, where workers are generalists, are "bucket brigades." We describe how one firm used bucket brigades as an intermediate strategy to migrate from craft assembly to assembly lines. The adoption of bucket brigades led to a narrowing of tasks for each worker and thus accelerated learning. The increased production more than compensated for the time lost when workers walk back to get more work, which was significant in this implementation.To understand the trade-offs in migrating from craft to assembly lines, we extend the standard model of bucket brigades to capture hand-off and walk-back times.