Magazine for logistics and production

The PRODUCTION manager is published four times a year and informs about the latest developments on the market for software solutions in the field of logistics and production.

You will also find on our blog selected articles from the current issue as well as other interesting topics about energy supply and public transport.

Current cover story

ERP and MES trends 2024

Between Integration and Simplification

It is in the nature of things: as business-critical systems, ERP-MES solutions are subject to particularly close and constant scrutiny. They are continuously being developed in terms of technology and functionality, with particular focal points emerging time and again. For the year 2024, we have identified four topics that will significantly determine ERP and MES: Simplification, resilience, supply chain data management and system updates.

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Recommended articles

Developing manufacturing systems with AI

Artificial intelligence (AI) is rapidly penetrating industrial sectors and has the potential to achieve increasing levels of efficiency in productivity. In the steel and aluminum industries, Manufacturing Execution System solutions are already being used to optimize production. However, by leveraging the strengths of both technologies, metal producers can unleash unprecedented levels of operational excellence.

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AI platform PSIwms AI ensures optimized picking processes at LPP

In a world where the efficiency of logistics processes is becoming increasingly important, the partnership between the Polish clothing giant LPP S.A. and PSI Logistics has set new standards. With the implementation of the AI platform PSIwms AI, LPP has made a significant step forward in the optimization of its warehousing and picking processes, setting the course for the future of logistics in e-commerce.

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Qualitative Labeling for automated preparation of business process data

As part of the Qualicision AI framework, Qualitative Labeling optimizes raw business process data for machine learning applications by qualitatively assessing measurable data directly from business processes in the context of KPIs (Key Performance Indicators) and analyzing interactions based on this. This automatically creates an algorithmic bridge between the unprocessed raw business process data and artificial intelligence (AI) methods, which significantly simplifies the time-consuming process of manual data analysis for labeling data.

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Find more articles on the subject of production on our blog.