When looking at work flow through a factory from the perspective of minimizing cycle time and honoring demand-pull policies, work should be processed on a first authorized, first processed (FAFP) basis. In other words, once a WO has been authorized within a WC’s queue, it should be pulled into production on a FAFP basis.  Deviating from this policy can result in an increase in the average cycle time, unless batching of WOs will reduce their aggregate cycle times due to machine capacity.  For an example of the latter situation, a machine may be capable of simultaneously processing ten pieces, and if there are two five-piece (or fewer) WOs, they could both be processed at the same time to reduce their aggregate cycle time, improve efficiency and maximize capacity.      More common examples of "jumping the queue” include changing priorities at the WC due to material shortages and preferential treatment of WOs to accommodate customer requests, management priorities or operator training.  But because some WOs will spend more time in queue than they otherwise would, processing work out of chronological order is not optimal and can be counter-productive.  Although the WOs that jump the queue will spend less time in queue than they otherwise would, the additional non-value-added time spent prioritizing each WO, in addition to the added time spent in the queue for WOs that are not prioritized, results in higher cycle times and more turbulent flow of the production process/operation.

    Given this principle, with a pool of work to be done in a WC, it is usually desirable to work first on the WO that is first authorized, based on demand, at the WC.  This would be the WO with the earliest-dated work authorization (or Pull-Tag (PT)).  

    To enable this policy, WOs should only be started when all the requisite resources are available, that is, never started into production if a resource shortage is present. If a shortage is present, it may not be possible to process the WO with the earliest dated PT, which can cause turbulence in the production flow.

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Xilinx, Inc.

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