OVER-Train Staff for Warehouse Automation Success

Most companies that have attempted to implement automated materials handling equipment have discovered that these projects can be particularly vulnerable to Murphy’s Law, the principal that, “anything that can go wrong, will go wrong.” This blog is twelfth in an ongoing series on “Beating Murphy’s Law in Warehouse Automation Projects.”

When it comes to operator training, there’s no such thing as too much. It can be inconvenient and costly to take operators away from their duties to train them on new processes, but it is important to remember that training will happen – it will either be in a controlled fashion, ahead of the deployment, or chaotically in the heat of the go-live.

Project leaders and engineers may find it easy to underestimate the degree to which new processes and technology must be clearly laid out to the those who must actually use them. The key project stakeholders may have been living and breathing these changes for over a year prior to deployment, as new processes are designed, built, and tested. Many times, however, the system operators themselves are only exposed to the new processes in the immediate lead-up to the implementation. It may take them longer than expected to embrace the new ways of working, and they may not readily admit when they do not understand aspects of the new workflows. Murphy’s Curve cannot be eliminated, but relentlessly training, testing, and re-training can make it as shallow and short as possible.

Warehouse Automation Projects: Don't Forget Inbound Processes!

Most companies that have attempted to implement automated materials handling equipment have discovered that these projects can be particularly vulnerable to Murphy’s Law, the principal that, “anything that can go wrong, will go wrong.” This blog is twelfth in an ongoing series on “Beating Murphy’s Law in Warehouse Automation Projects.”

On warehouse automation projects, the outbound processes of picking, packing, and shipping often receive a disproportionate degree of attention during the design process, to the exclusion of inbound processes like receiving, put-away, and bin replenishment. Companies often reason that, because failure to ship product can put them out of business quickly, all resources must be focused on this area, and that somehow the replenishment process will “figure itself out.”

While it is true that problems with outbound processes can negatively impact the operation in immediate and direct ways (orders don’t ship), inbound problems may be slower to manifest themselves, but every bit as serious to the operation. Many material handling systems appear to go live successfully at first, with just “a few minor problems” putting away product and replenishing the forward pick areas. However, as these “minor problems” build up, they can eventually cripple an operation over time as each day, more and more pickers arrive at bins that do not have enough product to fill their orders. More and more labor must be dedicated to getting product in the right pick faces, or inefficiently performing picks from reserve locations. Often, when trying to quickly stock bins to get product out the door, workers may take short-cuts and make product moves without taking the time to record them in the WMS system. This creates another insidious problem as inventory accuracy begins to drop, making the WMS incrementally less able to effectively trigger replenishment tasks. The impact of inbound flow problems is less immediate, but just as consequential as outbound problems.

Matrix content from Stephen Covey’s Seven Habits of Highly Successful People

 

This inattention to inbound processes is a classic case of failing to focus on areas of the design that are “important, but not urgent,” known as the “Quadrant 2” tasks, a term coined by author Stephen Covey in The Seven Habits of Highly Effective People. If “important, but not urgent” areas are ignored long enough, they become critically urgent and can potentially sink a project.

 

The remedy to this situation is to insist on rigorous design and discussion around the receiving, put-away, replenishment, and slotting processes at all design meetings. The rules for system-directed put-away must be thoroughly defined:

• How will the WMS or WCS know if newly arrived product will be able to fit in the desired bin location?
• Will bins that already contain product be “topped-off”, or should new product always be put in empty bins only?
• If newly-arrived product is put-away in overstock locations as a rule, what should happen if the forward pick location is empty?  Should new products be put there first?
• How will the WMS system manage these rules and execute this strategy?

 

Attention should also be given to bin replenishment:

• What will be the replenishment triggers?
• Will minimum and maximum stocking levels be defined for each product in each forward pick bin?
• How precise will these rules be?
• What happens if a SKU is re-slotted in a different forward-pick storage medium?
• How will the min/max quantities be calculated?
• What will be the specific trigger for min/max bin replenishment?
• Will the trigger occur as soon as product is allocated from a bin that will deplete it below the minimum level?
• Can bins be proactively replenished prior to product being allocated and waved to orders?
• Will pickers only be sent to bins when it is known that there is sufficient product to fill the demand to avoid a random, first come/first served allocation in short stock situations?
• What will happen if a replenishment takes place before the bin is depleted and the newly arrived product will not fit in the bin?  Where will the product be placed?
• Can a certain percentage of bins be intentionally left empty to accommodate these situations?
• How much labor will be required to replenish bins each day?
• How much additional labor will be required to get through the “Murphy’s Curve” period of reduced productivity?
• Has this labor been obtained and trained?
• How will replenishment tasks be measured and managed-to, each day?

 

Slotting rules and data integrity are also key topics to address:

• What rules will be used to slot the forward pick locations?
• Will slotting be based upon sales velocity, SKU affinity, segregation, family groupings, or other criteria?
• What system will manage these rules and suggest the optimal bin location for each SKU?
• How will this information be relayed to the WMS or WCS during put-away and replenishment tasks?
• What will be done to remediate data errors as they are encountered?
• If a replenishment worker is unable to fit all the product in the bin as expected, is there a defined resolution path where the situation can be investigated, and can corrections be made to master data expeditiously?

 

By giving thorough attention to these and other issues during the Design Engineering period, companies can help ensure a harmonious flow of materials in the distribution center in both inbound and outbound directions.

Warehouse Automation Projects: Don't cut corners with slotting!

Most companies that have attempted to implement automated materials handling equipment have discovered that these projects can be particularly vulnerable to Murphy’s Law, the principal that, “anything that can go wrong, will go wrong.” This blog is twelfth in an ongoing series on “Beating Murphy’s Law in Warehouse Automation Projects.”

A key design area that can cause problems with material handling system implementations is that of bin slotting: determining the optimal location for each SKU in the system. There are two basic approaches which can be taken to bin slotting: (a) using spreadsheet-based tools, and (b) using commercially developed, specialized slotting software. Each approach can be effective in certain situations.

Spreadsheet tools can often be used to perform very accurate bin sizing. This step is crucial as the final storage mediums are designed, and shelf spacing is set during implementation. Improper bin sizing can result in bins which are too large (creating wasted space and excessive travel), or too small (creating product overflows and excessive replenishment labor). Incorrect bin sizing is usually caused by either (a) faulty master data, or (b) shortcomings in the calculation methodology. Errors in master data can often be caught by having individuals who are knowledgeable of the business review the data, investigate outlying data points with a critical eye, and look for results which do not intuitively seem right. Conversely, errors in calculation methodology can often be remedied by having individuals experienced in slotting processes create the slotting tool using proven methods.

Many companies have found it beneficial to utilize a commercial slotting software system. Commercial slotting tools surpass the capabilities of spreadsheets in a number of ways:

• Pre-coded calculations and rules that have been battle-tested in numerous applications
• Ability to perform more complex slotting using multiple criteria, including:
  • Sales velocity
  • SKU affinity
  • Family groupings
  • Segregation rules
  • Ability to interface directly with a WMS system to trigger product moves and manage directed put-away

While commercial slotting tools are not inexpensive, they can often prove to be a wise investment. In the chaos of a system implementation, it can be difficult to rapidly correct slotting mistakes on the fly; far better to avoid making them to begin with by investing in a rigorous slotting program from day one.
To read Commonwealth’s complete white-paper titled, Beating Murphy’s Law in Warehouse Automation Projects, click here.

 

Using Simulation on Warehouse Automation Projects

Most companies that have attempted to implement automated materials handling equipment have discovered that these projects can be particularly vulnerable to Murphy’s Law, the principal that, “anything that can go wrong, will go wrong.” This blog is eleventh in an ongoing series on “Beating Murphy’s Law in Warehouse Automation Projects.”

One key way to mitigate risk is to spend “Smart Money" on key technologies like system simulation.

Simulation software differs from other forms of data modeling in some significant ways. Simulation software allows actual material handling equipment to be built with defined performance parameters and logic models, which simulate the decisions that are made by the controls software as various inputs are received. Graphical layouts are created which show what the equipment looks like in 3D renderings. Both mechanical as well as human work rates can be defined and modeled. A material handling system can be virtually “built”, and the software can simulate the picking, packing, and shipping of actual sales orders both by human and mechanized processes. Some of the key questions that simulation software can often answer include:

 

• How will the system respond if last Wednesday’s sales orders were processed through it?
• How would the system respond if the orders from the busiest day last year were processed through it?
• What bottlenecks exist in the system?
• What would happen if a key component in the system failed?
• What if we grouped orders in batches like this?  How quickly can the system process them?
• If we don’t have the labor perfectly balanced across zones, what level of labor imbalance will make the system choke?
• What happens if the shipping area falls behind for “x” minutes?  At what point does the system back up and shut down the picking area?
• Will it be possible to replenish the system quickly enough without interfering with picking?
• What if the average lines per order drops from three to two?  How will this impact the system throughput?

 

In complex material handling systems, simulations can identify design flaws in ways that no other modeling tools can. Unfortunately, simulations can be very costly and time-consuming to build. Many companies choose not to have a simulation performed in an effort to save money or preserve the project timetable. However, buyers would do well to consider the time and cost of rectifying a design flaw after a system has been built and installed.

 

Sometimes companies choose to have their material handling equipment provider perform a simulation of the system. However, purchasers should consider that equipment providers are not always the best source for this form of critical design validation. It can often be more effective to have an independent, third party perform the simulation, if for no other reason than to review the design with a “fresh set of eyes.” Many independent consulting firms can perform material handling simulations free from any desire to sell equipment, or any pride of authorship in the design which could inadvertently bias the results.