In Part 1 we briefly touched on the concept that the obvious problems with a material handling system, especially a system that is suffering from declining productivity and throughput during critical peak periods, may only be symptoms of a far greater problem. In Part 2 we will dig a little deeper for the root causes.

System Backups and Premature Shutdowns

Beyond the obvious equipment problems that plague most material handling systems from time to time, there can be several imbedded operational abnormalities that degrade performance. One of the most common is having too many open orders in process on the system at the same time. As an example, let’s look at a typical batch order picking, sorting, and manual palletizing system operation commonly found in order fulfillment DCs.

In this type of system it is critical to maintain proper segregation between batches and balance between the picking and palletizing operations. If not, you can expect the following problems to occur:

• Because pickers, working in multiple picking zones, pick orders ahead of the palletizers, end of batch cases (stragglers) belonging to large orders from a previous batch can windup accumulating behind cases belonging to the new batch. Thus, orders from the previous batch (containing those stragglers) cannot be completed (closed) at palletizing. Consequently, some of the after-sort palletizing/shipping lanes will not be available in a timely manner for the new batch of orders.
  
  
• System efficiency is further degraded when cases belonging to the new batch of orders have no available after-sort lane, and consequently start accumulating on the sorter recirculation loop until it becomes full. When this happens, inbound case flow to the sorter is interrupted causing those inbound lines to backup, which in-turn shuts down picking. Pickers and palletizers are standing idle while waiting for the system to sort cases belonging to multiple batches, thus reducing system throughput and efficiency. Worse yet, left unchecked, gridlock will occur shutting down the entire system.

Understanding Cause & Affect

The congestion caused by the above picking scenario will quickly fill up the available accumulation. Adding more accumulation conveyor will delay the problem, but not fix it. A better approach would be to first test different batch picking strategies like limiting the pickers to no more than two open batches at a time, and/or inserting end-of-batch totes in each picking zone before starting a new batch. The batch totes are then held at the central merge until palletizing has completed the previous batch.

For systems equipped with WMS, consideration should be given to adding (or perhaps just turning on) wave overlap functionality which can optimize accumulation requirements and go a long way toward eliminating bottlenecks and gridlock. With wave overlap the WMS divides the sorter lanes into two parts where each part is dedicated to a wave. In this way palletizers can work on a completed wave in the first part of the lane while the next wave is being sorted into the second part.

Of course, there are more sophisticated forms of batch and/or wave picking which may be considered, such as waveless picking or continuous flow picking, all of which create operational challenges of their own.

In addition to picking strategies, you should also review critical path merge logic and conveyor/sorter speeds to determine if they can be adjusted for higher capacity (refer to Part 1).

Another good practice is to make sure that the right amount of labor is at the right place at the right time. This may seem elementary but can get out of sync quickly. For example: too many pickers and not enough palletizers in shipping will cause congestion that can reduce throughput and rob system efficiency and productivity. It is better to have a little excess capacity in shipping to insure that order fulfillment efficiency is maintained.

In the typical distribution system, the rate at which cases are introduced into the system from receiving, cross docking, warehousing, picking, special processing, and staging areas, varies greatly throughout the production cycle. By analyzing each of these inbound production areas it is possible to estimate how much accumulation is required under various flow scenarios to keep all areas running at their target design rate. Sometimes computer simulations can be effective tools for companies to use to better understand system performance, test operational alternatives, identify potential bottlenecks, and understand the likely result of changes to an existing system.

Final Thoughts

Order fulfillment processes are inherently complex and becoming more so all the time. Operations managers should examine all production areas to determine how they can be simplified and streamlined. Continually look for functional improvements in slotting, order batching, pick path routing, and workflow simplification.

The suggestions outlined above and in Part 1, are the kind of system management procedures that are low risk and when added together may yield as much as 20 to 30 percent improvement in overall system performance with a relativity small capital investment.

Having an independent general distribution operations audit every 2 to 3 years will help keep your system investment performing at peak efficiency. However make sure that you provide clear guidance to the “auditor” about what you want the focus and scope to be.

Agree or disagree with Holste's perspective? What would you add? Let us know your thoughts for publication in the SCDigest newsletter Feedback section, and on the website. Upon request, comments will be posted with the respondent's name or company withheld.

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