National Instruments headquartered in Austin offers LabVIEW, a systems engineering software platform and toolkit.
$407
per year
Teamcenter
Score 8.2 out of 10
N/A
Teamcenter is a product lifecycle management system designed to help organizations integrate and standardize product development processes across functional silos.
LabView is a great tool to connect your sensors to your data aquisition hardware. It makes it really easy to set-up a data acquisition routine that meets your individual requirements. I, as an engine researcher, find it very well suited for engine experimentation. For any other programming needs, i.e. not data acquisition, I would not recommend using LabView because of its graphical programming architecture. The architecture makes it a great tool for Data Aquisition but puts at a disadvantage when it comes to other computational tasks, e.g. making a thermodynamic engine model. For those applications having text-based programming is better suited
Teamcenter is growing very well in active workspace as a web-based client, but again, when I'm coming from the manufacturing point of view or a Build of Processes point of view, the software easy plan still needs to improve in a way. Of course, I think they're improving it also in a good way, but it's still not yet matured so from today onwards I can simply ask my users from product resistant to using the plan and push it further. I think there we have to improve more.
It is an easy-to-use tool and integrates many capabilities to manage CAD better than any other tool.
It is used by many companies with a great global presence and that has generated confidence for us when we decided to try it, the results have been satisfactory.
The user interface of this tool is not complex, it is easy to navigate and integrates a lot of functionalities that speed up our work significantly; as well as functionalities such as sectioning, displacing, moving, positioning, transforming, among others that have a lot to do with CAD management.
It works via the web through the browser, so it is not necessary to download any application that takes up space and more resources on the computer.
Because of our current customer needs, we will most likely maintain use of Siemens PLM products for some time. Aside from the initial software cost, we pay for yearly maintenance. Maintaining our yearly maintenance licensing with Siemens, we receive access to all of the latest software releases, as well as premier technical support
As previously mentioned, due to the intense amount of features and modules present in the software, the usability of the software suffers greatly. Many of the features are not used in our context, and many of the modules are not purchased, but the options are still present on the interface leading to a lot of clutter, much of which is never used. The interfaces suffer from a lack of design and tend to feel like a conglomerate of Windows 98 elements.
In the time that we have used Teamcenter we have received a good response from the support team, they have great customer service, we have solved the problems that have arisen very quickly, and they are attentive and answer us if we have any questions.
We chose LabVIEW over MATLAB due to the integration with hardware and the graphical programming interface. Also, the ability to use LabVIEW with FPGAs and real-time processors without having to make large changes to the code base or swapping to a separate programming environment was a big benefit since we don't know what hardware will be suitable for each customer application.
Teamcenter is a more robust and faster application, with better search capability and easier customization. There is a reason you find companies using CATIA as their CAD software with Teamcenter as their PLM application! I don't know anyone who can name a company using NX with Enovia as their PLM!
Teamcenter exhibits commendable scalability, meriting an 8 out of 10. Its architecture accommodates our expanding material science firm seamlessly. With modular expansions and flexible configurations, it adapts well to increased data volumes and user growth. However, while robust, occasional complexities arise during extensive scaling, hindering a perfect score but substantiating a high ranking for its scalability.
