I’d like to come with questions about the topic of PLM and Data Modeling. The idea of this discussion came out of some comments and conversation made on PLM Think Tank. Since, it was presented as a significant differentiation in the capability of PLM system(s) to make their job, I decided it important enough to discuss.
Fundamentally, PLM Data Model is the heart and the core of any PDM/PLM implementation and system. The ability to model design, engineering and manufacturing data as well as processes around, obviously comes as a very important. However, since the topic of modeling is about company products and process, it is always coming as something unique in the organization. In the early beginning of PDM, systems were not flexible and requires physical change (re-build) to handle specific product and process data. Nowadays, PDM/PLM systems are claiming sort of flexible data modeling capabilities that make them possible to apply to any customer situation. At the same time, cost of this “application” is sometimes very expensive.
PLM Data Model Uniqueness
What make PLM Data Modeling so unique? Why do we need it? Maybe we can avoid this process, by supplying something generic and not requiring change for every customer? There are two extreme examples I want to bring in the context of these questions. One is about Excel (or spreadsheets). Basically, we can model almost everything in the spreadsheet these days. It is absolutely good, since it is damn flexible and can run out-of-the-box. However, to understand these models, you need to keep Chief Excel Officer in your organization for full time job. As an opposite – why we cannot make “the universal PLM data mode”. Since, this is all about engineering and manufacturing, we can finally identify what to put there. It may work, but every time, your customer will ask you about “small changes” to be made in order to support their requirements.
Standards and Best Practices
I can see these two options as a industry try to deliver a compromise between Excel and One-PLM-Model. Standard activities were very popular (and may be still popular) in the engineering and manufacturing world. Standards for product data exchange, supply chain, industry standards, etc. In parallel with that, big software and service vendors tried to come with so called “best practices”- a simplified way to delivery data model for a specific segment of customers, industry vendors. The fundamental difference between standards and best practices, in my view, was at the level of “agreement” achieved between parties involved into this activity.
Where I want this discussion to go? I think, PLM (or engineering and manufacturing) data models are an interesting topic and real problem. In many cases, it defines the success of the implementation or PLM software in general. This is a technical and marketing issue at the same time. At the same level data modeling influence implementation and product architecture, it is always used as part of the marketing story. Do you think a PLM data model is a key of the future success of PLM implementations? Conversely, maybe you think it is a technical term, and it should dissolve into “real conversation about functions and value of PLM systems”?
What is my conclusion today? I want to listen to your opinions. From my side, I’ve seen this topic touched hearts of many people involved into discussions. In my view, PLM Data Model defines the level of flexibility (or new word – “granularity”).
Just my thoughts…