PLM graph-aware architecture and search for data

PLM graph-aware architecture and search for data

In many ways, one of the most important functions in every PLM system is a capability to interconnect multi-disciplinary data about products and processes. Almost every PLM project I was exposed to had to deal with the complexity of data modeling – defining all business objects, attributes, relationships, dependencies. There are PLM systems that can do it easy via user interface and there are PLM systems that will demand you to write Java code to define business objects. Many PLM systems will allow you to federate and create links to the data located elsewhere. And at the very moment you think that your PLM implementation job is done, the next big question will come – how to search and navigate through all levels of data complexity. This is where engineers spent from 12% to 30% of their time according to multiple researches. Here is an interesting passage I found in the article – Various Survey Statistics: Workers Spend Too Much Time Searching For Information:

A new survey by SearchYourCloud revealed “workers took up to 8 searches to find the right document and information.” Here are a few other statistics that help tell the tale of information overload and wasted time spent searching for correct information – either external or internal.

Another article written by Dick Bourke Consulting – Search and… Find can give you an interesting perspective on work done by vendors in engineering domain (CAD, PDM, PLM) to improve the way engineers can search for data. The link inside of the article will allow to download the paper.

Although search was always part of PDM and PLM interfaces, new data management approach and cloud services can give you many advantages on how data can be indexed and searched in modern systems. The variety of architectures are available. Check my old blog – Why PLM need to learn about Google Knowledge Graph. The concept of Knowledge Graph was developed for the last few years and I found an interesting reference architecture for Knowledge Graph and search implementation provided in Neo4j blog – Relevant Search Leveraging Knowledge Graphs with Neo4j. The article describes the idea of knowledge graph, core data sources, data model and other services needed to build search application. Read the article- you can find it useful. Alternatively, you can just take a look on a picture below representing the architecture overview.

What is my conclusion? PLM represents a huge complexity of data management to every system. Collecting data from multiple sources, organizing data in a graph and getting insight how to search and navigate to the relevant data is a big deal for every PLM system. And the problem is getting even more complex as PLM is moving toward connecting products, IoT and related domain. To have an architecture that capable to scale with the data complexity is a big challenge. A good reminder to PLM architects and PLM vendors. Just my thoughts…

Best, Oleg

Want to learn more about PLM? Check out my new PLM Book website.

Disclaimer: I’m co-founder and CEO of openBoM developing cloud based bill of materials and inventory management tool for manufacturing companies, hardware startups and supply chain. My opinion can be unintentionally biased

Disclaimer 2: Neo4j didn’t sponsor the content of this publication. 


Share This Post