Stackflo Sonata delivers specific and measurable benefits to the financial performance of assets in the coolroom:
- Reduced Labour Overhead
- Efficiency in Decision Making
- Fewer Fork Movements
- Diminished Warehouse Footprint
- High Density Space Utilisation
- Minimal Volume of Stock at Hand
- Proactive Management of Date Codes
- Elimination of Loss through Pick Errors.
The result is a measurable reduction in the cents per litre/gallon metric of coolroom asset performance.
Stackflo Sonata achieves this with key features that simplify tasks for the operators, and with sophisticated algorithms that make optimum decisions.
simplify logistics tasks
Operator effectiveness is supported by a range of Stackflo Sonata screens and functions, such as:
- 3D user interface views of all the stock in the coolroom
- Real time views of the status of orders to be picked, during picking and at the cart dock ready to go
- Traceability of individual crates from receipt into store right through to dispatch
- Realtime KPIs for continuous improvement and 6 sigma programmes
- Every action in the warehouse directed or monitored; Stackflo Sonata logs every event of note.
algorithms make optimum decisions
Algorithms model complex systems and enable development of ‘scoring’ or ‘cost’ functions. They simulate many millions of scenarios for the choices possible to drive complex systems, then search across this vast set of possibilities to quickly find a very good set of choices; that is - ones that score the best.
The results are demonstrable, including:
- Direct fork drivers, to minimise travel distance
- Choose a sequence of picking orders to achieve delivery in full on time (DIFOT)
- Suggest adjustments to the production schedule to avoid stock outages
- Minimise production changeover costs.
Milk logistics is a challenging environment
- Multiple SKUs with short shelf life
- Complex planning environment where things go wrong
- Limited space
- Limited time in which to achieve Delivery In Full, On Time, Error Free.
Every day in the coolroom, decisions are made on the fly … when trucks are late, when stock is short … all executed by staff under pressure. Essentially, it's impossible for staff to work out all the consequences of their decisions. There is no question of the planning and on-the-fly decisions being in any way optimal.
A case study
Stackflo recently created a new planner to optimise performance in a New Zealand coolroom.
The planner starts with a group of orders that must be picked in a given sequence.
Next it must determine a set of actions to be undertaken by forks and automated machinary that results in correct crates being picked for each order.
In addition to picking correctly the planner is required to optimise, by:
- Minimising fork replenishment travel distance
- Consolidating the SKUs - keep like crates together
- Managing weight distribution within each stack so that the heavier ones are below the lighter ones
- Picking as quickly as possible.
But these objectives can't all be simultaneously satisfied all of the time. By using a scoring function, weighing up how well each constraint is individually satisfied, the planner can determine the overall score for one possible way of moving crates through the system.
Stackflo Sonata algorithms are able to investigate millions of different ways that the picking could be done quickly. It takes seconds of CPU time on a server and arrives at the most efficient overall solution.
The result in this coolroom has been a demonstrable improvement in all factors. Our algorithms find perfect solutions for SKU Consolidation and Weight Distribution more than 95% of the time, because weighting was given to these priorities. The priorities were set and can be adjusted by the coolroom staff.
The only time that Stackflo Sonata algorithms don't find a perfect solution is when there is no perfect solution possible.