Our customer builds highly complex machines that are capable of functioning at the atomic-scale level. These machines are made up of between 20,000 to 40,000 individual parts, all sourced from within their own supply chain and many of which are custom designed in-house. Managing a supply chain of thousands of suppliers, manufacturing millions of unique parts, requires a tremendous amount of manpower and resilience. However, the year 2020 challenged these networks and they, as well as their peers, had a hard time sourcing the material they needed to manufacture their complex products.
To make matters worse, with the Russian invasion of Ukraine, an important raw material, Nickel, was suddenly at risk of becoming unprocurable. Supply chain executives immediately asked: “Which of our materials contain Nickel?” It was difficult to find the answer to this question since Nickel did not appear in any internal databases, but was called out only on the CAD drawing of the individual part that required it.
Our software was used to extract raw material from hundreds of thousands of CAD drawings and, while successfully finding each part that contained Nickel, we were also able to generate a distribution of other raw materials.
How did our customer accomplish it?
Firstly, our customer extracted their purchase order history from their Enterprise Resource Planning (ERP) system. View a sample of the extract here. They then combined this extract with SourceOptima's generated dataset of raw material.
By combining these two datasets, our customer was able to easily pivot the data, summing up purchase order data by raw material.
How to read the output?
Raw Material ALUMINUM was purchased 145 times in 2022 across 19 different suppliers, across 86 different Part Numbers
Conclusion
Even though the exercise was meant to expose supply chain risk around nickel, our customer was able to uncover the fact that they were purchasing raw materials from within their direct material purchases across a large number of suppliers, resulting in them missing out on potential volume purchase discounts.
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