This blog post was authored by Will Worrall, Director & Data Scientist at Miminal
At Miminal, one of our largest projects is the commercialization of bespoke artificial intelligence which reveals hidden dependencies in complex engineering projects. The product that does this is KADlytics, and more can be found out about the product at www.kadlytics.com.
So, how is this done? The AI is built on the principle that if two assets (e.g. CAD model files, documents etc.) are updated at approximately the same time then this is a proxy for some kind of dependency. For example, employee A makes an update to their CAD model and notifies employee B that they must update their CAD model, to account for A’s changes. Employee B does this at the next possible opportunity. Whilst this dependency relationship is simple, organizations suffer from not understanding these dependencies in enough detail in large collaborative projects. This often leads to unforeseen work having to be carried out after an update to an asset, to update unforeseen dependencies.
KADlyitcs learns and tracks a project dependency network using just update metadata as input, namely the timestamps of asset updates. It then puts this network to use, alerting employees of whose work they may affect when they change an asset, or if their work must be updated due to an asset change. Beyond digital assets, KADlytics also reveals the dependencies between people and organizational departments. In addition, it aids the project management team in predicting the project-wide design effort (cost) created by an update to a particular asset in the project.
In order for KADlytics to operate on a project, several stages of processing must occur:
Each of these stages have 3 things in common:
These commonalities form a set of requirements for the hosting infrastructure. Our research showed that Fn Project is the only solution that meets these requirements, scales, doesn’t lead to unused compute capacity at times of low traffic, is failure resilient and supports any desired runtime environment with its revolutionary use of Docker containers as serverless functions. In addition to this, using Oracle Cloud Infrastructure to host our Fn Project servers means our serverless functions run on physical servers with an underlying compute-power far greater than the commodity servers of other cloud providers.
Finally, Fn Project has made developing a flexible, modular and extensible microservice architecture a pleasure. Go and check it out at https://fnproject.io .