The analytics engine called Supply Chain Inspector

Supply Chain Inspector

Dimanex, a Dutch start-up based in Utrecht that makes 3D printing easy for supply chain teams, launched Supply Chain Inspector in mid-November 2019. It is an analytics tool that makes use of semantic search and machine learning to help customers identify the right parts for additive manufacturing (AM).

As part of Dimanex’s cloud-based end-to-end platform, Supply Chain Inspector utilizes supply chain data to help teams build up their digital inventory. Supply chain teams often find it difficult to adopt 3D printing due to some gaps in their available data. It is a common misconception that a 3D-printed part is always more expensive than a mass-produced one. In fact, mass ordering a part often saddles companies with several years of inventory holding costs and scrapping expenses.

According to Dimanex, its Supply Chain Inspector provides visibility into the total supply chain costs as the basis for assessing the impact of purchasing decisions on the end-to-end supply chain. “The solution enriches your existing supply chain data with 3D printing capabilities, so you can identify how digital manufacturing technologies can help you optimize your supply chain,” states the company in a press release.

Tackling supply chain issues

Customers such as JLG, NS (Dutch Railways) and Electrolux are already using the solution to tackle immediate supply chain issues like demand unpredictability and long lead times. They can also anticipate and prevent future problems such as excess stock. Securing parts through Dimanex’s distributed network of AM partners not only avoids waste but also minimizes logistics distances travelled and improves the ecological footprint, the company claims.

Supply Chain Inspector is the analytics engine behind Dimanex’s end-to-end platform, which also supports the part design, conversion and approval process, enabling users to collaborate with colleagues across departments in a single workflow. Once the design of a part is approved, it is added to a virtual library of parts. Users can then place orders on demand. The platform automatically matches each order with the most suitable additive manufacturing partner.