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Warehouse Performance

18.10.2021

»Warehouse Healing« strategy as the key to an intelligent warehouse! (Part 4/4)

In our last article, we introduced you to the advantages and benefits of optimised batch planning. In this article, we will go one step further and would like to address the topic of minimising routing times through intelligent placement of products. How does this work? With the new development »Warehouse Healing« from S&P Computersysteme GmbH. True to the motto: »Data is the new oil«, data is the raw material for the strategy and uses it in a consistent way to generate real added value. The aim is to recognise existing patterns in the order history and to use them to generate sensible stock transfer and storage suggestions to minimise picking paths.

The concrete implementation follows a simple, investment-saving principle. But let's take a closer look at the individual steps of the strategy:

The first two steps: Data collection and integration followed by visualisation and interpretation

Before the data can be used and real added value can be generated from it, it must first be identified. Relevant data can be found in stock levels, topology, article information, shopping baskets or even movement data. Once the necessary data has been collected and collated, the next step is to visualise and interpret it.

The new strategy »Warehouse Healing« is designed to defragment the warehouse and to reduce the travel times for man and machine through the intelligent analysis of movement data and shopping baskets. Starting from the situation, a strong warehouse fragmentation it is now a matter of analysing, evaluating and recognising patterns. This data forms the basis for the next phase: model creation and training, in order to be able to generate real added value from the data.

Step 3 and 4: Model creation and training and application of the results

The next step is to define the score of a storage area. The lower the score, the better! A high score is mainly created when items that have a strong affinity to each other are stored far away from each other, or when items that are ordered frequently have a long picking path. To find stock transfers after which the score is lower than before, algorithms are used that take into account the »experience« from the order history. The results of the algorithms are then used to simulate healing processes and to defragment the warehouse beyond the normal level - initially without any impact on the ongoing business processes. At this point, the main objective is to create an optimised 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. Via progress indicators, the user can follow the realisation of the potentials and enjoy the savings.

At that point, you rightly ask yourself: »How do I even know whether the application of such a strategy an option for me and my warehouse is?« This is where the potential analysis comes into play, based on which we look at the extent to which the »warehouse healing« strategy affects the warehouse area concerned. The strategy places particular emphasis on a fast “time-to-value«. This is achieved by using an algorithm to determine the stock transfers with the greatest effect and executing them first. After only a few hundred stock transfers, for example in multi-storey shelving systems, it is possible to save up to 40% of travel time in the best case. By means of AI and simulations of changed model parameters, the result is constantly adapted to changed conditions over time to minimise the total retrieval costs. The strategy drastically reduces travel times and thus optimises the extremely labour-intensive process of order picking. It is important for our data science experts to evaluate the results together with you and to discuss the expected benefits. In this context, our experts will give you a neutral assessment and support you in the decision-making process.

The result while applying the strategy: performance increases, optimal utilisation of workflows and efficient resource planning in the logistics centres!

Would you like to use your data consistently and learn more details about it? Don’t hesitate to contact us!



Further information that could be interesting:
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