The manufacturing world is undergoing a huge transformation. Digital technologies are reshaping what is possible and how companies are able to achieve new levels of operational efficiency. One of these transformations is new innovative business models and technologies that help manufacturing organizations achieve digital excellence.
Earlier this month my attention was caught by the article, A network perspective on the visualization and analysis of bill of materials which covers a topic near and dear to my heart: Bill of Materials. The article is a bit geeky, but it may it be good weekend reading for you. In a nutshell, the article discusses how to apply graph theory to analyze product structure for multiple products in such a way as to enable huge positive impact for providing recommendations to manufacturing company on how to optimize their BOMs or discover a potential impact from specific parts, processes, or suppliers.
Here are a few passages from the article to make my point about Bill of Materials and the new technological opportunities:
A bill of materials (BoM), or product structure, is a diagram that lists all the components and parts required to produce one unit of a finished product, or end part. It is often represented as a tree structure with hierarchical relationships among different components and materials. In this article, we introduce two procedures to convert single and multiple BoM into networks. These procedures allow us to leverage the potentialities of networks analysis, providing new perspectives in terms of representation and extractable informative content, and thus gaining insights into the criticalities of parts and components.
My favorite topic is aggregating multiple BOMs using graph structures:
When we have to deal with many BoMs of different products that share some components, a one-by-one evaluation may become very difficult and sometimes unfeasible. Indeed, when the number of items increases, so does the complexity of the number of considered products. For this reason, the evaluation of critical nodes necessitates the introduction of an aggregation procedure. The aggregation procedure is a common way to examine systems that interact on multiple layers and which sums up the data from different layers into a single one.40 The resulting network is weighted and the edge weights between two nodes derive from a linear combination of the weights between those same nodes from each of the layers.
And here is the key passage:
The most important implications of the aggregated BoM relate to the overall part number centrality; specifically to the starting materials, assemblies, and subassemblies. The analysis of parameters, such as strength and in-degree, indicates the centrality of the part in the manufacturing process of the final products. The in-degree value points out the number of finished products that uses the part (i.e. the assembly, subassembly or starting material). The latter could be taken into consideration when analyzing the impact on production planning and thus determine how to manage the related supply or production. Indeed, the more the part is shared among BoMs, the more the reordering and production planning criteria should be accurately managed.
You may remark and ask, this is an interesting scientific story, but how is it related to OpenBOM? So here’s the thing, OpenBOM is a new type of product. We develop technologies to manage data for multiple products to be managed by multiple companies and teams. It allows you to optimize data management, but most importantly, it allows you to develop techniques of how to optimize product and its bill of materials.
We are building our data analytics story and are very excited as a result. Graph technologies is a natural part of what OpenBOM does. We would like to talk to companies interested in how to optimize their Bill of Materials and make improvements in component usage as well as decisions about contractors and suppliers.
Conclusion. A buzzword I recently picked-up is called ‘datafication’. We live in an era where data is everywhere. Individuals and companies produce data at every moment of every day. The same applies to manufacturing companies. The Bill of Materials is the lifeblood of every manufacturing business. Knowing how to optimize a bill of materials can provide huge benefits. In the near future, data-driven manufacturing companies will succeed because they will be able to apply data science to product structures and bill of materials.