In cooperation with Merantix Labs we created an interactive series of events so that we can bring AI in all stages of the value chain to life.
Because there’s a simple fact: Using AI applications can generate impactful added value for the whole company.
The central question is: How?
Answers to that questions are provided by Nicole Büttner-Thiel (CEO and co-founder Merantix Labs) und Charlotte von Dryander (Project Manager Merantix Labs). Throughout four lectures, the two experts talk about the potentials of AI in combination with Smart Production, Smart Logistics, Smart Sales and Smart CRM – each with its own use case and specific advice on what to do. In our series of articles, we’ll write about the different use cases so that you can see that advantges of AI on the value chain.
Nicole Büttner-Thiel presents:
AI Use Case In Smart Logistics – Automated Control of Returned Articles In the Logistics Department
Problem: The rising importance of e-commerce and the low delivery costs lead to an increase of B2C movement of goods. It is only natural that this in turn leads to an increase in product returns. In the textile sector, returned clothing must be inspected for damaging. Visual quality assurance carried out by employees are done by hand, require a lot of resources, and are expensive. Often, specialized personnel training creates additional costs. The low degree of standardization in human evaluation capacity is joined by a barely transparent process assurance.
AI solution: AI can examine returned products based on image data in a fully automated process. Such algorithms can exceed the human evaluation capacity by several degrees. Algorithms are able to recognize anomalies in image data, localize the source, and classify the observation. This process often is based on the application of supervised machine learning techniques: an algorithm is trained using labelled (“This image shows an example of damaging”) image data to recgonize and learn patterns between incoming and outgoing data.
Results: The application of these learned patterns leads to a significant process improvement. For the quality assurance of returned goods, this leads to time-savings and increased standardization. Repetitive process steps can be eliminated, employees receive efficient support through an early-warning-system. Ultimately, digitalization enables an uniformization of work steps and an accumulation of effective knowledge about internal processes.
Nicole Büttner-Thiel, CEO and co-founder of Merantix Labs is part of the 42.cx advisory committee. She develops technology-oriented solutions, is a member of the Digital Leaders for Europe Board des World Economic Forums, and is volunteering in the alumni board of the University of St. Gallen. She was awarded with Rising Talent award by the Women’s Forum and named a Young Leader by the Aspen Institute. She studied macroeconomics in St. Gallen, Stockholm, and Stanford.
Merantix Labs develops innovative, custom-built machine-learning solutions for companies from various sectors. They oversee the complete implementation of process and production automation for their customers – the guarantee the quality of their products.
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