Combinatorial algorithms
instead of simple sorting for optimized transport orders
Reduction of travel expenses
through sensible combination of orders in multi-order picking
Optimization of order sequence
considering both automated and manual sections holistically
Increase of delivery performance
with simultaneous reduction of processing time through correct wave sizes and avoidance of bottlenecks
Equalization of the workload
in consolidation areas and storage areas through appropriate sequencing of replenishment and picking orders
Operational usage with integration into the system world
via SAP or database connector or RESTful APIs
Optimized Tour Building & Routing
Holistic consideration using combinatorial algorithms
Reduction of walking and driving effort
Avoidance of traffic jams
Equal load balancing
Interaction with the methods for product placement
The efficiency of multi-order picking processes depends very much on the right sequence and configuration of the orders. On the one hand, this multi-order
picking process has the goal of minimizing the efforts required for order picking. On the other hand, restrictions such as departure times and workload on packing
stations have to be considered. Time-consuming optimization runs, possibly even overnight, are things of the past. Despite large amounts of data and complex individual
restrictions, the situation should be constantly reassessed in a short time. W2MO meets this challenge with state-of-the-art combinatorial optimization technology and
algorithms, resulting in picking tours with shorter distances and no traffic jams due to equal load distribution. Minimizing path lengths for single tours is not
sufficient; instead the total amount of all required picks must be considered in order not to have one long tour as the “cost” of another very short one.
Optimized order sequence
Prioritization of orders to ensure adherence to schedules
Reduction of downtimes to increase productivity
Calculation of a suitable start time based on the expected workload
Synchronization of replenishment and picking orders
Coordination of the consolidation of different storage areas
Equalization of the workload of buffer and consolidation areas
The aim of optimizing the order sequence is, on the one hand, to ensure that deliveries are made on time and, on the other, to increase the productivity of
employees and machines by reducing downtimes. With the help of the digital twin of the distribution center, the expected workload to complete an
order can be determined. Based on personnel and machine resources, system performance, and picking and transport speeds, a suitable start time window for the order
can be determined. Buffer and consolidation areas should be equally utilized and a coordinated combination of different storage areas should take place. With
the integration of the online workload preview it is possible to detect early on if the scheduled deliveries cannot be processed with the
available resources in the specified time. Re-prioritization can then be carried out.
Intelligent replenishment
Demand oriented inventory calculation
Prioritization of order sequences for replenishment
Forecast of replenishment
Reduction of picking efforts
Increase of service level and alignment to delivery dates
Volatile demand presents the biggest challenge in picking and replenishment processes, and can oftentimes lead to temporary peaks in replenishment that
might exceed the maximum supply chain capacities). Replenishment systems therefore require smart concepts and algorithms which can fulfil the needs of
highly dynamic material flows. Here W2MO comes into play with its tailor-made solutions and modern calculation methods to guarantee durable and punctual
delivery capacity through range-driven target stock calculation and prioritization of replenishment order sequences. This also results in a reduction of
picking efforts, as incorrect picks are avoided. An optimal bin assignment can also be calculated with consideration of picking and replenishment times.
Replenishment bottlenecks can be smartly avoided when under-load times are being used purposefully for replenishment precautions. W2MO and its intelligent
algorithms can identify articles that will most certainly be demanded in the near future.