New feature delivers cost transparency in engineering and procurement.

PartSpace is adding a new feature to its AI-powered software platform for technical procurement that enhances both operational and strategic benefits: assembly analysis. This enables industrial companies to automatically analyze and evaluate not only individual components based on drawings, but also entire functional assemblies and modules, and to assign reliable target costs to them. The new feature addresses a key bottleneck in procurement and cost engineering: in industrial practice, decisions regarding costs, suppliers and contract awards are generally made not at the level of individual parts, but at the level of complete assemblies.

With this extension, PartSpace extends its AI-powered analysis of design data to multi-level bill of materials (BOM) structures. Bills of materials, CAD models and technical drawings are imported via bulk upload or through interfaces with existing ERP, PLM and SRM systems. The software then automatically analyzes every component within the assembly, extracts manufacturing-relevant characteristics such as material, dimensions, tolerances, surfaces and manufacturing processes, and derives target costs from these. These individual values are aggregated at assembly level and linked to procurement, supplier and market data. The result is transparent target costs, visible cost drivers, price variances and supplier recommendations for individual items and complete assemblies. The system takes into account components produced using various manufacturing technologies, such as milled, turned, sheet metal, injection-moulded, stamped or deep-drawn parts, as well as machined castings and forgings; standard and off-the-shelf parts can also be integrated. Particular emphasis is placed on welded assemblies – where, in practice, the welding effort can often only be reliably assessed with a high level of expertise – including assembly units.

From individual components to robust assembly evaluation

This is relevant for companies because procurement decisions regarding complex modules, comparisons of quotations and ‘make-or-buy’ considerations cannot be meaningfully derived from isolated analyses of individual components. A component that appears to be optimized may actually increase costs at the assembly level if assembly, joining or logistics costs are not taken into account. Key areas of application include early-stage cost assessments during the design phase, the consolidation of suppliers across entire assemblies, and a shared data foundation for procurement and engineering. This provides companies with a robust pricing basis even before tenders are launched and complex supplier quotations are available – quotations that often take one to two weeks to prepare. The new feature thus better reflects the actual working practices of procurement and design departments and significantly speeds up the analysis of large, nested bills of materials. “In industrial procurement, it is not the individual part that determines cost-effectiveness, but the assembly as a functional unit. This is precisely where the new analysis comes in,” says Sebastian Freund, COO and co-founder of PartSpace. “When procurement and engineering receive reliable target costs and supplier recommendations at assembly level, more informed decisions are made much earlier in the process and with significantly less manual effort.”

The automated analysis of assemblies makes it possible, in particular, to reduce the need for manual, item-by-item costing across hundreds of bill of materials items. What previously took days or weeks to complete can now be provided in a short space of time as a consistent cost assessment at assembly level. In documented customer projects, potential savings of around 12 to 25 per cent were identified for drawing-linked parts, whilst the workload was reduced by up to 55 per cent. In a mechanical engineering project involving more than 10,000 drawing-linked components, an analysis of the first two product groups revealed potential savings of around 12 per cent in the tens of millions; the return on investment was achieved within a few weeks.

The assembly analysis forms part of PartSpace’s strategic positioning, which aims to make design data available as the basis for data-driven procurement decisions. The focus here is not on generic AI, but on a system specializing in engineering data that links CAD files with historical ERP data, supplier information and production plans. PartSpace thus positions itself at the interface between design and procurement, occupying a new software category between ERP and PLM.