Caronte - So I can mainly speak to National Instruments approach through an integrated software and hardware platform for HMI and motion control. Through the use of LabVIEW software environment and our Reconfigurable I/O hardware we provide a single hardware and software platform to learn. You can learn more at ni.com/motion.
Sorry for the confusion, here is my previous answer to Otto's question:
It seems as though, especially in dealing with exisiting systems, that the industrial automation world is still fragmented if you look at a global prespective and I believe that is why it is important to have a universal protocol/communications medium between all the vendors. Again I go back to OPC and the new OPC UA protocol as one method to unify a diverse system through software.
I categorize automation software debugging into two categories - those debugging tools that most often help during the development process and those that help when the software is deployed to the end hardware. In the development process debugging tools such as breakpoints, probes, and stepping tools are important to efficiently debug the functional behavior of your application. Then when you are ready for deployment there are debugging tools that hook into your application and tell you the developer how your program is executing in its actual environment (memory usage, harddrive usage, etc.).
Both these types of tools are important to have when developing an automation software application.
Ah ok, yeah for CEP we have seen a number of customers utilize historians for both long term and short term trending for process optimizations as well as for monitoring of their machine life cycles. A good example from one of our customers Conical Mill can be found in this case study: http://sine.ni.com/cs/app/doc/p/id/cs-13377
We have definitely seen more interest in our products and in the industry for PLM - for instance with machine condition monitoring for predictive mantainence. For PDM, again as I mentioned in the audio protion of this program, around the idea of standardizing automation data and collecting it realtime to make more realtime decision.
My understanding is that CEP is about taking event and historical information from historians and other resources on the plant floor and using analytics to understand impacts and predict failures and such.
Based on what you're seeing, how prevelant it is today for engineering platforms like PLM and PDM to be tightly coupled with manufacturing and automation systems? Is this still more of a pipedream or are companies making headway bridging these two worlds?
Rob - if you look at the last five years we have seen a surge of operating systems and technologies come from the moblie/tablet world - such as Android, Apple's iOS, and Microsofts new Windows 8 operating systems. The focus of all of these environments is to make multi-touch user interfaces easier to use. I see this transitioning into the HMI world as well. So from a software prespective the automation applications will need a variety of HMI implementations to service the expectations of the users.
To answer your question Ann. Just as you have seen in all aspects of our life - such as our cars - automation systems and processes are being optimized further through the integration of more sensors, emebedded computers and FPGA which then funnel their information to centralize data servers. These servers than can provide information to HMIs as well as to anaylsis tools.
It seems as though, especially in dealing with exisiting systems, that the industrial automation world is still fragmented if you look at a global prespective and I believe that is why it is important to have a universal protocol/communications medium between all the vendors. Again I go back to OPC and the new OPC UA protocol as one method to unify a diverse system.
We have seen machine vision be used in other applications such as security and in conjuction with motion to better automate systems. This also goes back to the critical nature softare plays communicating between these different elements. But in general we still see inspection play a large part of the machine vision applications.
HI this is Ann, I had trouble logging in. What do you think about the increasing integration of machine vision in the automated factory, not just for inspection, but possibly also other uses? How about what I've read is better vision technologies on portable platforms like Beth mentioned?
One issue is that whilst business logic in terms of ERP and data wharehousing etc. is well organised and protected, manufacturing software is not, whether it be comtrol logic SCADA or MES. Their is little or no virulization, no centralised servers and version control not well managed. What are your thoughts on how this can be improved?
Welcome. Today's radio show begins at 2pm eastern. Please type in your questions at the best ones will be fed to our guest during the first 30 minutes, which constitutes the live RADIO discussion portion of the show. At 2:30 pm, our guest, Jonah Paul, will come onto this instant chat and answer your questions directly.
IMPORTANT NOTE: IF YOUR COMPANY BLOCKS LIVE STREAMING AUDIO -- as a number of companies do -- YOU WILL NOT BE ABLE TO HEAR THE BROADCAST LIVE when it begins at 2pm eastern, in a streaming audio player which appears at the top of this page at that time. You will have to come back and access it as an archive. The archive is posted later today. However, you may want to still stick around for the live chat with our guest; he will dive in at the 2;30 pm EDT mark.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.