Features and innovations

Run marathons in the warehouse? Not at Technilog. Store goods sensibly and reduce travel times.

As part of a pilot project, Technilog decided to conduct a proof-of-value of the "Warehouse Healing" strategy in February 2021. In the process, our data science experts validated the high benefit and potential in the warehouse using concrete customer data. "Warehouse Healing" is one of a total of 3 strategies for optimized decision making in the warehouse, in our Warehouse Management System SuPCIS-L8.

Exterior view of the Obeta logistics center

Our long-standing customer Oskar Böttcher GmbH & Co. KG and its logistics subsidiary Technilog pursue the approach of continuously increasing logistics performance and thus the level of service for their own customers. In doing so, Technilog relies not only on forward-looking automation technologies and the continuous expansion of its warehouse capacities, but also on the use of data science and AI. With its fleet of vehicles and their optimally coordinated deployment, the company delivers to customers throughout Germany on a daily basis. "We have been involved with the use of data in logistics for some time now, and it is becoming apparent time and again what opportunities this offers us in the warehouse. Together with the experts from S&P, we have now taken the step and carried out a potential analysis. With the help of existing data and intelligent models, unused potential is to be uncovered. One thing is already clear to me: an extremely exciting and forward-looking project," says Nico Schubert, project manager at Technilog Technik und Logistik GmbH.

Creating real added value from concrete data
Under the motto: "Data is the new oil", existing data from Technilog's logistics form the raw material for proof-of-value. Before the data can be used and real added value can be generated from it, the relevant data such as stock levels, topology, item information, shopping baskets and movement data are identified in Technilog's warehouse. The data basis is provided by our warehouse management software SuPCIS-L8. The data is then visualized and interpreted. Algorithms were used to determine stock transfer and exchange suggestions, and by interpreting the results, the savings in walking time specific to the use case were determined. "The storybook answer would probably be: collect data, analyze it, model it, put putaway and swap suggestions into action, and create real value. However, the use of artificial intelligence also brings its requirements for both sides, which had to be addressed together and implemented in the best possible way," continues Timofej Woyzichovski, our data science expert.

The new strategy "Warehouse Healing" is designed to defragment the warehouse and to reduce travel times for man and machine by better positioning of items through the intelligent analysis of movement data and shopping baskets. Starting from a strong warehouse fragmentation, the two project partners focused on the analysis, evaluation and pattern identification of the prevailing situation. This data is the basis for the next phase, in which the model was created and trained.

The next step was to define the score of the manual pallet warehouse as a storage area. Algorithms are used to find stock transfers at this point, after which the score is better than before. These incorporate the experience from Technilog's customers' order history. The results of the algorithms provide the basis for simulating stock transfers and defragmenting the warehouse beyond normal levels. This process was done entirely without impacting Technilog's ongoing business processes. The beauty of this is that the automatic training experiments in the background continuously improve the results.

From artificial intelligence to real-world use in the warehouse
The "Warehouse Healing" strategy allows Technilog to draw the full potential from predefined use cases. From data collection to use in intralogistics. In the process, it is important for our data science experts to jointly evaluate the results and discuss the expected benefits. At Technilog, the results from the proof-of-value showed that the application of "warehouse healing" in the storage area of the manual pallet warehouse reduced retrieval paths by about 24% after just a few hundred stock transfers.

The logical step - the use of the "Warehouse Healing" strategy in daily operations - was decided immediately after the presentation of the meaningful results. "With the Proof-of-Value, Technilog has taken an important step towards uncovering hidden potential in the warehouse. We are pleased about the joint success, the trust placed in us and the valuable input from our customer Technilog in the further development of our Data Science products," concludes Rémy El Abd, our Managing Director.


Would you like to learn more about the "Warehouse Healing" strategy or do you have any questions about this project? Please feel free to contact us.

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