December 2018

Product Innovation as a Graph

The first time we were asked to exchange with someone about Product Lifecycle Management (PLM), we needed a whiteboard within 5 seconds of discussion to explain why we should use part masters, part versions, documents. How is this connected to a product definition? How do you relate it to a manufacturing process, to a DFMEA? We ended up with lots of graphs, which once they would be validated, would start defining the digital thread for a company.

PLM backbone is about maintaining a graph

Everything is connected in a graph and the information has value for the product whenever it happens. Whether it’s a requirement or a field incident it has a lot of value to a common product. These should be easily linked.

Importance of Semantic

Storing data like you use it is the real deal. On a graph you want to be able to specify node type names but also edges names to have a graph semantic that means something for anyone looking at the data.

Further analysis with graph algorithms

In addition to creating a PLM graph for the digital thread, an interesting use-case for Graph is to analyse production incidents and look for similar causes of defects. During graphconnect 2018, Boston scientific with graphaware presented some studies they made to find product defects coming from a similar production machine. When you see where to look, than any database solution could help you. When you don’t know where to look then graphs are opening a much wider spectrum of analysis.

What about Ganister?

We do store all our data within a graph database. Which means all the data you store and manipulate has the capability to be queried with a very advanced query model with graph algorithm. It’s also much easier to understand the data. The semantic graph representing your data gives you a good understanding of your information value. API First and graph database = the right way to digitize the product lifecycle management.

“API First” to digitize product lifecycle management

Ganister is the first “API-first” solution for digitizing product lifecycle management. This is it, very simple, by design we decided to build our API before anything else. It means, we had to build all our technical (playing with nodes) and functional (playing with parts and documents) tests on this API. We had to focus on security, performances but also ease of access.

A functional API

The functional API gives you the power to communicate with the API in business terms. You don’t want to always use technical names, like nodes and items,etc… to query a document. You want to query a document, you want to get a full BOM, you want to have an Engineering change request impact analysis. We get close to business best practices within the API, way before thinking about a web User Experience.

A Technical API

We can’t cover every one’s business specificity. So we give freedom to extend the digitization of your business processes with Ganister by using more technical API at first. Create, query,update nodes, and you have a world of possibilities for digitizing any process.

A documented API

This is a key aspect. We hear sometime that developers don’t like documentation. Well the only true statement is that they don’t like writing things that could be automated. Updating a word document… yikes ! Most of the technical description of the API generates a documentation that is actually actionnable. You can test it directly in the documentation.

There must be a lot more to say about API, and we’ll let you discover all that, in our training or just by yourself during a trial period or as a customer.