Warehouse Healing: Path Time Reduction through Intelligent Algorithms

In the midst of the age of digitalization and automation, almost all logistics centers have one thing in common: the consistent use of data to derive recommendations for action or strategies usually falls by the wayside. As a result, immense potential lies hidden and is rarely exploited.

The new warehouse strategy "Warehouse Healing" defragments the warehouse. It reduces the travel times for man and machine through the intelligent analysis of movement data and baskets of goods. This greatly reduces the costs of the most labor-intensive process in a warehouse - picking - with little effort. This leads to performance increases and efficient resource planning in the warehouse. The realization is very easy for the operative logistics: The Warehouse Management System SuPCIS-L8 suggests stock transfer as well as exchange processes for stocks. Both classic pick frequencies, as known from ABC analysis, and the fact that a large number of articles are frequently ordered together(product affinity) are taken into account.

Whether during off-peak times or by interspersing them into the regular daily business - these operations can be carried out easily and at any time. In the automated warehouse, on the other hand, for example in an automated high-bay warehouse (HRL), these operations are carried out outside the normal shift.

Many companies are now dealing with the data in their systems, but not infrequently face these particular questions. How do I select the right data sources and automation processes in the first place? How do I derive company-specific use cases from them that offer real added value? And even if a company has successfully overcome these hurdles, they still have a long way to go:

• Bring about concrete changes in the business processes and
• self-learning models with better and better results over time.

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With the innovation "Warehouse Healing", customers can tap the full potential from predefined use cases. From data collection to use in intralogistics, smart tools and experts from the Data Science team are available.

The actual implementation follows a simple, investment-saving principle and divides the rollout into two phases:

1. Proof-of-Value
   The first step is to validate the benefit based on the customer data. Subsequently, the data sources are determined, the data integrated, transformed and visualized. Algorithms are then used to determine initial results (rerouting and swap suggestions), and by interpreting the results, the savings in travel time specific to the use case are determined. The goal is to make a data-driven decision for or against the introduction of "Warehouse Healing".
   
   
2. Implementation of the use case
   In the second phase, data integration is automated using cloud services. The results of the algorithms are now used to simulate healing operations and defragment the warehouse beyond the normal level. This has no impact on ongoing business processes. At this point, the main goal is to create an optimized virtual target state that can be used to train the optimal combination of model parameters. Automatic training experiments in the background continuously improve the results. Also new in this phase is the actual use of the results in the business processes and the direct interaction with the warehouse management system SuPCIS-L8. Communication takes place via an API. Via progress indicators, the customer can track the realization of the potentials in real time and enjoy the savings.

The strategy places particular emphasis on a fast "time-to-value". This is achieved by the relocations with the greatest effect, which are determined by an algorithm and executed first. After just a few hundred stock transfers, for example in multi-story shelving systems, up to 60 % travel time can be saved in the best case.

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By means of AI and simulations of changed model parameters, the result is constantly adapted to changing circumstances over time in order to minimise the sum of the outsourcing costs.

With the innovative "Warehouse Healing" from the "Warehouse Intelligence Suite", customers can transform existing data into business benefits. The strategy drastically reduces path times and thus optimizes the extremely labor-intensive process of picking. The result: performance increases, optimal utilization of workflows and efficient resource planning in the distribution centers.

This topic or strategy was chosen as "Product of the Year 2021" in the software category by the intralogistics trade medium "Materialfluss"!

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Are you interested in Warehouse Healing and would like more information? Please feel free to contact us.