A customer order may be picked entirely by one worker; or by many workers but only one at a time; or by many at once. The appropriate strategy depends on many things,but one of the most important is how quickly must orders flow through the process.For example, if all the orders are known before beginning to pick, then we can plan efficient picking strategies in advance. If, on the other hand, orders arrive in real time and must be picked in time to meet shipping schedules then we have little or no time in which to seek efficiencies.
A general decision to be made is whether a typical order should be picked in serial (by a single worker at a time) or in parallel (by multiple workers at a time). The general trade-off is that picking serially can take longer to complete an order but avoids the complications of co¨ordinating multiple pickers and consolidating their work.
A key statistic is flow time: how much time elapses from the arrival of an order into our system until it is loaded onto a truck for shipping? In general, it is good to reduce flow time because that means that orders move quickly through our hands to the customer, which means increased service and responsiveness.
A rough estimate of the total work in an order is the following. Most warehouses track picker productivity and so can report the average picks per person-hour. The inverse of this is the average person-hours per pick and the average work per order is then the average number of pick lines per order times the average person-hours per pick. A rough estimate of the total work to pick the skus for a truck is the sum of the work-contents of all the orders to go on the truck. This estimate now helps determine our design: How should this work be shared?
If the total work to pick and load a truck is small enough, then one picker may be devoted to an entire truck. This would be a rather low level of activity for a commercial warehouse.
If the total work to pick and load an order is small enough, then we might repeatedly assign the next available picker to the next waiting order.
If the orders are large or span distant regions of the warehouse or must flow through the system very quickly we may have to share the work of each order with several, perhaps many, pickers. This ensures that each order is picked quickly; but there is a cost to this: Customers typically insist on shipment integrity, which means that they want everything they ordered in as few packages as possible, to reduce their shipping costs and the handling costs they incur on
receipt of the product. Consequently, we have to assemble the various pieces of the order that have been picked by different people in different areas of the warehouse;
and this additional process is labor-intensive and slow or else automated.
For warehouses that move a lot of small product for each of many customers,
such as those supporting retail stores, order-picking may be organized as an
assembly-line: The warehouse is partitioned into zones corresponding to workstations,
pickers are assigned to zones, and workers progressively assemble each
order, passing it along from zone to zone.
Advantages include that the orders emerge in the same sequence they were released,
which means you make truck-loading easier by releasing orders in reverse
order of delivery. Also, order-pickers tend to concentrate in one part of the
warehouse and so are able to take advantage of the learning curve.
The problem with zone-picking is that it requires all the work of balancing an
assembly line: A work-content model and a partition of that work. Typically this
is done by an industrial engineer.
Warehouses tend to use combinations of several of these approaches.
1 回答
3.3.1 协作拣货
单个客户订单可以是由单个工人独自完成,也有可能是由多人分段顺序执行,也可能是同时由多人并发执行。什么方式才是最合适的,它取决于许多的因素,不过其中最重要的一条 是:越快越流畅越好。如果在拣货开始前就已经知道了所有的订单需求,那么就能预先规划出最有效率的拣货策略;但是,如果订单时时刻刻都在进,且要求仓库立即执行拣货来达成发货及时率,那么要想提升其效率基本上只有一点空间,或者没有。
因此,需要进行这样的决策:订单是应该被串行(由一个工人一次),还是被并行(由多个工人一次)拣货。它需要权衡,是接受串行的长订单周期;还是用多人并行更快地完成拣货,并协调他们和集货。
订单处理周期是一个关键统计指标,是指从订单下进系统到完成装车待发总共过去的时间。通常来说,越短的处理周期越好。越短,就意味着订单会越快地通过我们的手交付给客户,它还意味着我们的服务能力和响应水平越高。
关于一个订单总工作量可以精略按以下估算。在许多仓库里,会跟踪和统计拣货工人的作业效率,以人均每小时拣货次数来计,因此,可以用它来推算出每次拣货的平均工时,从而推算出每个订单的平均工作量,就是以每个订单的平均拣货行数乘以每次拣货的平均工时。而将每辆车上所有订单工作量合计一下,就粗略地得到了每车的拣货工作量。用这种评估现在可以帮助我们的进行设计决策:应该如何进行拣货协作?
如果一辆车的拣货和装载的总工作量足够小,那么一个拣货工就可以负责整这辆车。但对于一个商业仓库来说,它业务量实在是相当地低。
如果每个订单的拣货和装载工作量不大,那么我们可以顺序把订单分发给所有有空的工人,让他们持续不断完成每一个订单任务。
如果订单都很大,或分布几个离得很远的库区,又或订单必须尽可快地完成,那么就可能需要几个或多人进行协作才能完成它。它是为了保证拣货尽可能地快;但是会有其它成本产生,比如,客户通常会坚持运输的完整性,这意味着他们想要所订购的全部货品在打包成尽可能少的包裹,以减少运输费用和在收到时产生的处理费用。因此,我们必须将仓库不同区域的不同人员拣出的不同部分进行集货;这个额外的过程是劳动密集型的,速度很慢,或者采用自动化来完成。
对于那些需要同时给许多客户拣取许多小件的仓库,比如零售配送中心,它们的拣货过程可以看作是一条装配线:仓库按不同的分拣站划分成不同的库区,工人被分配到了指定的库区,逐步按区组装每一个订单,并将其从一个区域传递到另一个区域,到最终完成。
它的好处是,订单会按照发布的顺序依次出现,这样可以按照到货的逆序排,装车将变得很方便。并且,工人只在个别区域工作,培训起来比较容易。
分区接力拣货需要和装配线一样,所有区域的工作量要均衡的,也就是说工作与分区要相匹配,这通常是由工业工程师完成的。
仓库倾向于使用这些方法的几种组合。
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