Choosing a part numbering scheme is one of the more important decisions you make as you move toward production… Once you commit to a part numbering scheme, you are married to it for a long time to come, so you need to be 100% sure it is nimble enough to evolve and scale right along with you...
It sounded like a Catholic marriage. Once you decided about part numbering, you are done for many years. The same Arena’s blog post mentioned some external tools you can use to generate part numbers – part-numbering.com and partnumber.com.
The idea that stroke me earlier today is that most of the companies are using “smart Part Numbers” in order to simplify part search, re-use and, even more fundamentally, classification. Type of part, organization, suppliers – these are only small elements of “an intelligent part number”. What if some “smart applications” are available that can add classification information to existing part numbers in order to enrich (actually to annotate) Part Number identification. These tools can be web-based and even applied to existing data in the company.
What is my conclusion? We need to re-think some very fundamental elements and concepts of product development, PDM and PLM. The ability to enrich data without building lots of sophistication in the Part Numbering is something that can make PDM / PLM systems more flexible and drive cost of changes down. I’d be interested how to support it in existing PDM/PLM systems. Not sure if it is a simple task. However, I’m curious if new PLM software coming tomorrow to market from companies like Autodesk will have a different set of capabilities to solve the problem of Part Numbering and identification. Just my thoughts…
It is not unusual to hear about problems with PLM systems. It is costly, complicated, hard to implement and non-intuitive. However, I want to raise a voice and speak about data management (yes, data management). Most of PDM/PLM software is running on top of data-management technologies developed and invented 30-40 years ago. The RDBM history is going back to the invention made by Edgar Codd at IBM back in 1970.
I was reading Design News article – Top automotive trends to watch in 2012. Have a read and make your opinion. One of trends was about growing complexity of electrical control units. Here is the quote:
As consumers demand more features and engineers comply, automakers face a dilemma: The number of electronic control units is reaching the point of unmanageability. Vehicles now employ 35 to 80 microcontrollers and 45 to 70 pounds of onboard wiring. And there’s more on the horizon as cameras, vision sensors, radar systems, lanekeeping, and collision avoidance systems creep into the vehicle.
It made me think about potential alternatives. Even if I cannot see any technology these days that can compete on the level of cost, maturity and availability with RDBMS, in my view, now it is a right time to think about future challenges and possible options.
Key-Value Store
These types of stores became popular over the past few years. Navigate to the following article by Read Write Enterprise – Is the Relational Database Doomed? Have a read. The article (even if it a bit dated) provides a good review of key-value stores as a technological alternative to RDBMS. It obviously includes pros and cons. One of the biggest “pro” to use key-value store is scalability. Obvious bad is an absence of a good integrity control.
NoSQL (Graph databases)
Another interesting example of RDBMS alternative is so-called noSQL databases. The definition and classification of noSQL databases is not stable. Before jumping into noSQL bandwagon, analyze the potential impact of immaturity, complexity and absence of standards. However, over the last 1-2 year, I can see a growing interest into this type of technology. Neo4j is a good example you can experiment with in case you are interested.
Semantic Web
Semantic web (or web of data) is not a database technology. Opposite to RDBMS, Key-value stores and graph databases, semantic web is more about how to provide a logical and scalable way to represent data (I wanted to say in “semantic way”, but understand the potential of tautology ). Semantic web relies on a set of W3C standard and combines set of specification describing ways to represent and model data such as RDF and OWL. You can read more by navigating to the following link.
What is my conclusion? I think, the weak point of existing RDBMS technologies in the context of PLM is a growing complexity of data – both from structural and unstructured aspects. The amount of data will raise lots of questions in front of enterprise IT in manufacturing companies and PLM vendors. Just my thoughts…
I read one of the latest VEKTORRUM re-posts about Autodesk and PLM. Navigate your browser to the following link and read the original article from 2007. According to the article – ” There are “more pragmatic, more digestible approaches” to solving engineering data management issues than PLM, he [Carl Bass] said”. It made me think more about Autodesk, data management and PLM strategies.
History
Let’s start from the history. Autodesk has a long history of data management solutions. It contains multiple products. Some of them were developed by Autodesk and for some of them Autodesk partnering with other companies. The most notable Document and Workflow Management system in early 1990s was Autodesk Workcenter (Google is tracking the following link on Autodesk Workcenter). I had a chance to work on few Autodesk Workcenter implementations, so I had my own Workcenter implementation memories going back in 1994-1995. The next big Autodesk data management project was Motiva PDM. Autodesk made a significant investment into Motiva project in the end of 1990s. You can track the following KMWord article – Autodesk and Motiva to Collaborate for PDM. Both, Workcenter and Motiva development were discontinued.
In the beginning of 2000s Autodesk acquired company truEInnovation. The original product truEVault was a foundation of existing Autodesk Vault. This is the Wikipedia quote:
Autodesk Vault was initially known as truEVault; part of an acquisition from a company called truEInnovations, Inc. based in Eagan, Minnesota. truEInnovations was started by two entrepreneurs, Brian Roepke and Dean Brisson in 1999. The company was founded on the basis of bringing a more affordable tool for managing engineering data to the market.
After the asset acquisition of truEInnovations by Autodesk in 2003, Autodesk began to further the integration of the product into the manufacturing product line, starting with Autodesk Inventor.
Autodesk’s Data Management Foundation
For the moment, Autodesk Vault is the foundation of all Autodesk Data Management products. After latest re-branding, Autodesk Vault is a family of PDM products providing a wide range of capabilities started from files vaulting and expanded into areas of Bill of Material Management and Engineering Change Management.
Autodesk is intensively working to provide additional data management features and functions. You can see a short video of Brian Roepke about Autodesk Vault 2011:.
In the following video you can see a new Autodesk Vault 2011 integration with Inventor.
In my view, some of them are very similar to features presented by DS 3DLive and Siemens 3DHD products. See my post – 3DLive, 3DHD, 3D and UI efficiency.
Autodesk and PLM
Steve Wolf of Cyon Research recently published an article on COFES Blog – Who Needs PLM? (). In this article, Steve discussing the latest Autodesk financial results and
The following quote represents Steve’s comparison between Autodesk and other PLM-associated companies.
What’s interesting about Autodesk’s success is that the company’s products consist almost entirely of single-user desktop tools that engineers use to do their jobs faster. Relatively little of Autodesk’s income comes from what its rivals call “product lifecycle management” (PLM) software that combines engineering applications with fiendishly complex enterprise-level software for managing engineering data.
A different opinion presented by CIMData in their latest research paper focusing on how Autodesk will evolve into full-scope PLM provider. I had a chance to discuss this CIMData research before on my blog. This is the PLM think tank link. Take a look on the interesting quote from CIMData website:
… perspective on the transition that Autodesk is executing to transform itself from a supplier of individual PLM-focused point solutions to a supplier of industry-focused solutions that can be the fundamental platform for a company’s overall PLM strategy.
What is my conclusion? I think, Autodesk is going on a very narrow bridge and trying to connect customer’s demands to have a rich scope of data management functions and integration with design tools like Autodesk Inventor. At the same time, Autodesk is trying to avoid getting into positioning data management as a “PLM strategy”. The ugly truth, in my view, is that users are less interested in the TLAs these days and more thinking about products, functions and usability. Just my thoughts…
I want to talk about what I consider as one of the most controversial topics in the industry – PDM vs. PLM. How many times, you had a chance to hear the following question: What is the difference between PDM and PLM? I guess, the only one question can practically compete with this – question [...]
In my view, the majority of organizations are collaborating using pure email. PLM implementation has hard time to compete with email to become first class collaboration tools. I had a chance to see an interesting company DokDok making software for Google Apps that allows you to share documents separately from Gmail. The power of this [...]
I want to talk about Part Numbers. Yes, Part Numbers, again… My previous blog – Part Numbering and the future of identification raised few interesting conversations. So, I decided to open a Pandora box of part numbering. The formal trigger for this conversation was Arena Solutions blog – Three consideration when choosing Part Numbering schema for you. Here is passage that actually made me think about the fact we are doing something wrong:
). Semantic web relies on a set of W3C standard and combines set of specification describing ways to represent and model data such as RDF and OWL. You can read more by navigating to the following 
