Everything you should know about virtual spare part warehouses based on 3D printing
RECODE.AM #5
Anyone involved in industrial 3D printing has come across the concept of the virtual spare part warehouse.
It consists of storing digital models of parts and managing their on-demand production using 3D printers. It is intended to reduce inventory levels and transform spare parts logistics.
In reality, however, implementing this idea faces a range of challenges related to ensuring full traceability, generating the necessary certificates of conformity, and organizing “virtual” stock within 3D printing farms.
Additive manufacturing of parts on demand assumes that instead of physically storing them in a warehouse and shipping them worldwide, only their digital counterparts and production parameters (3D printing technology, material, post-processing) are stored.
When a need for a given part arises, the production facility closest to the point of demand manufactures it and delivers it locally.
This makes it possible to significantly reduce costs associated with maintaining inventory levels and to limit losses resulting from obsolete stock, which becomes unnecessary as products evolve. Of course, there are also savings in transport costs and reductions in delivery times.
This revolutionary idea was described as early as eight years ago by ING analysts as “a threat to global trade.”
A key aspect of this concept is, however, ensuring full process traceability — from the digital CAD model, through additive production, to final part inspection.
In traditional supply chains, certification of finished components relies on physical documentation, an audit trail, and archival storage of samples. In the virtual warehouse model, all this information must be generated automatically and stored in a way that allows immediate issuance of a certificate of conformity.
This means that CAD, PLM, ERP, and MES systems must be integrated with applications that generate the required reports and certificates based on collected process data.
Such a process has been proposed in numerous studies on intelligent inventory management in the Industry 4.0 environment.
In practice, however, the lack of uniform standards for data exchange between different platforms is an obstacle.
Closed file formats are often used, and the APIs of software and hardware suppliers are fragmented or undocumented.
Another issue is the validation of the printing process in industries with high certification requirements — aerospace, energy, or medical — where strict compliance with ISO standards or FDA specifications is expected.
Without automation for generating documentation and reports, each print batch becomes a potential production bottleneck due to the need for manual document preparation.
The development of digital twin concepts combined with machine learning helps to mitigate these barriers. Virtual models of printers and 3D printing processes allow simulation of a print before the machine is physically launched, which reduces the risk of errors and accelerates the certification process.
This means that when production is requested, the part is optimized not only in terms of geometry and parameters but also for compliance with standards. The system can automatically detect nonconformities and suggest corrections, while the final version of the report and quality certificate is generated together with the print.
Geographically distributed 3D printing farms are another piece of this puzzle.
These are production centers equipped with dozens or hundreds of machines that execute orders from various locations. Each print is immediately linked with post-processing and inspection.
However, the centralization of virtual spare part logistics carries risk: centralized platforms can become a bottleneck for the entire process. If the system managing the virtual warehouse fails or falls victim to a cyberattack, the entire production network may come to a standstill.
Furthermore, farm operators may become dependent on a software provider who controls the optimization algorithms and documentation generation. This raises the question of the balance between efficiency and independence: is it better to trust an external platform offering full automation or build in-house solutions, risking higher maintenance costs?
The virtual spare part warehouse is based on the assumption that the digital model and its production process are sufficient for full certification. In reality, however, even with automatically generated certificates of conformity, metrological confirmation and non-destructive testing are necessary, and their results must be synchronized with the digital data.
This means that a physical warehouse and laboratory still play a key role in the final stage of the process.
Until the virtual system enables fully remote quality supervision of parts, the role of traditional warehouses and laboratories will remain significant.
In summary, the virtual spare part warehouse has real potential to revolutionize the logistics of certified spare parts. However, its implementation requires overcoming significant barriers related to data exchange standardization, ensuring full traceability, and maintaining the independence of farm operators from software providers.
Only the creation of open, interoperable platforms capable of integrating with existing validation and inspection systems can enable full realization of the benefits offered by virtual spare part warehouses in the AM industry.
Absolutely right on Pawel
So, instead of 'importing' 3D Printer components and paying heavy freight charges, one could just get the parameters, algorithms with certification / quality or standard checks software and produce the printers themselves locally. Of course the materials would still be needed physically depending on the parameters of casings etc.
Very interesting article.