Whatever you can hear about complexity of PLM, there are lot of manufacturing companies that created outstanding PLM implementations. These implementations are helping them to optimize product design, speed up engineering to manufacturing process and do many other innovative things making their engineering and manufacturing uniquely competitive. From my experience, these implementations never came as a result of single PLM platform deployed in a company. It is usually a bunch of projects that are using several PDM / PLM products combined together with code and some homegrown stuff. In some situations these combinations are uniquely representing companies’ needs and ideas. I found it a gold mine of PLM implementations. But, very often, these implementations end up with a single company using it for their internal purposes only.
I think, this is a time for manufacturing industry to learn what other innovative companies are doing in such situations. Airbnb, the company helping people to rent apartments around the globe just made an announcement about open sourcing some portion of Airbnb data management infrastructure. Navigate to the following readwrite article to lean more – Airbnb Opens Data, Machine Learning Code. I found the following passage specially interesting
For Airbnb, which makes money by operating a marketplace for unconventional lodging in people’s homes and apartments, not by selling software, releasing its in-house software projects as open source serves to bolster its image as a technical innovator. There was a lot of talk about the company’s “engineering brand” at OpenAir. Allowing others to examine and use its code should, in theory, help the company recruit engineers and retain its current technical employees by publicizing their coding feats.
If you interested to learn more, navigate to airbnb.io – the destination of all Airbnb open source projects. If you are technical, you can find some very interesting things to experiment over the weekend. My special attention caught Airflow. I guess lot of my PLM friends can be interested by DAG-driven workflow scheduler.
Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
So, what about Open Source PLM you may ask? In the past Open Source PLM was a hot topic. Aras Corp. was the most active company after open source PLM innovation. Aras called it Enterprise Open Source. I don’t think the trend took off, actually. A subset of Aras solutions is available as an open source, but I’m not sure if these solutions can be used with another PLM backbone (which can be an interesting idea, btw).
The Airbnb example made me think about growing trend – innovative web companies are solving their data management problems without specific “enterprise software” vendors. My hunch we need to look more after what companies like Facebook, Twitter, LinkedIn, Airbnb, Uber, Tesla, Local MotorsI etc. are doing and how they are innovating with data.
What if some manufacturing companies will decide to open source their PLM implementations? Would it be something other manufacturing companies can leverage? Recently Tesla open source their patents to be used by other car companies. Maybe PLM implementation can follow the same path too?
What is my conclusion? PLM industry should find a way to innovate beyond the trajectory of large enterprise PLM vendors. The complexity of existing PLM platforms makes it dominant in the market and hard to compete with for smaller players. At the same time, manufacturing companies are suffering with slow ROI and complexity of solutions. Manufacturing companies can open source some of their implementations and create a dent in current big “top three” PLM dominance. Just my thoughts…
Best, Oleg
Image courtesy of KROMKRATHOG at FreeDigitalPhotos.net
