Optimized transport orders and order sequence

easy to use and powerful

Combinatorial algorithms instead of simple sorting for optimized transport orders

phenomenal google geographic data

Reduction of travel expenses through sensible combination of orders in multi-order picking

easy to use and powerful

Optimization of order sequence considering both automated and manual sections holistically

easy to use and powerful

Increase of delivery performance with simultaneous reduction of processing time through correct wave sizes and avoidance of bottlenecks

easy to use and powerful

Equalization of the workload in consolidation areas and storage areas through appropriate sequencing of replenishment and picking orders

easy to use and powerful

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.

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