We manage master data, including Bill of Materials (BOM) and Bill of Processes (BOP). AI assists in the optimization of master data by extracting comparable items from large BOMs and BOPs. High traceability may be maintained while operating various versions thanks to version management tools.

We track manufacturing data and assign production numbers. We effortlessly integrate data across the whole supply chain, from upstream to downstream, by connecting production numbers and master data with signals from the shop floor, such as operational records, equipment signals, video, or picture data.

We compile your distinct insights from operational records, master data, and other sources into a knowledge base. AI agents enable efficient knowledge use by extracting relevant knowledge from massive volumes of data.

We integrate primary and secondary data to master data and operational records in order to manage the data needed for the CFP (Carbon Footprint of Products) calculation. This makes it possible to calculate CFP in accordance with rules and targets for reducing GHG emissions. Additionally, we guarantee data integration following industry standards.

Supply chain cooperation for GHG emissions data is developing faster in the battery industry than in other industries, and companies must disclose their calculated emissions through appropriate channels. SeizoMind CFP offers an interface with the emissions data integration platform in addition to emissions calculation and visualization. You can efficiently gather and handle primary and secondary data by integrating it with SeizoMind Mas and SeizoMind Tra.

The process of making automotive parts involves assembling various components, including electronic and material components, which sometimes leads to complex structures including hundreds to thousands parts for a single component. The BOM optimization feature of SeizoMind Mas allows you to manage a large number of components effectively by standardizing related parts and variations and optimizing the amount of BOM entries. Furthermore, using SeizoMind Age to create a knowledge base improves BOM searchability.

Appropriate setting of raw materials, equipment, and operational conditions is crucial in the manufacturing of materials. We gather data from real processes and evaluate it along with production and raw material insights in order to improve these parameters. Through an agent system, you may naturally integrate these previously scattered data sources and centrally manage them by combining SeizoMind Mas, SeizoMind Tra, and SeizoMind Age.

Chemical raw materials are essential to the creation of batteries and other materials because they influence the end products' functionality and characteristics. To control the performance of their final goods, customers of chemical material manufacturers might request particular criteria for inspection values and production methods. Complex manufacturing management is made possible by the efficient management of those criteria established for specific clients through the use of SeizoMind Mas and SeizoMind Tra.