Berkeley, CA -- (ReleaseWire) -- 02/03/2014 -- Will Sobel, CEO of System Insights said, “To achieve a true 4.0 revolution, we will need to instrument and collect huge amounts of data from machine tools and tie the success of the process, quality, into a feedback loop to identify where in the process defects were introduced. The defect detection must be done as close as possible to point at which the defect was introduced so there is the least amount of interference that may make attribution more complex. “
In machine or measurement of critical features is a key requirement. To truly understand the effectiveness of a process, the quality of the process needs to be correlated with the execution of the process and the data collected while the process was being executed. The sensor data combined with the controller and machine tool data will identify the aberration by correlating the operation in the machine with the defect area to determine how to detect and prevent the problem from reoccurring.
The amount of data is truly daunting, but modern cloud based big data technologies allow us to perform large scale computations using distributed analytics and detect patterns in the data to determine subtle correlations. Also, modern signal processing techniques that have been used for speech recognition can be applied to find patterns in various data streams.
“Using modern statistical machine learning and high speed pattern matching – vimana – we can identify the patterns and then predict them in real-time. Industry 4.0 will require a system like vimana to become a reality. It will require real-time monitoring and feedback to the CPS to adjust processes and provide the analytical foundation to transition from a human-machine to a machine-machine control,” shared Sobel.
With full automation there is also a need to have machines monitoring machines to detect failures and predict when maintenance is required. As machines become autonomous, they will also be responsible for measuring and maintaining their health. The single operator per machine who maintains and cares for that piece of equipment will not scale and a single operator may be responsible for multiple machines that are all interconnected. The operator will be responsible for resolving exceptions and performing maintenance as well as making sure the material is available and other physical aspects that are beyond the machines capabilities.
About System Insights
System Insights, (http://www.systeminsights.com) based in Berkeley, California, with offices in Chennai, India, is a leading global supplier of manufacturing software in both machining based, discrete and process industries. The SI flagship product - vimana - delivers predictive analytics solutions to improve clients’ efficiency, productivity, and profitability. vimana provides these data while enabling customers to realize sustainable manufacturing objectives. The vimana software platform delivers a unique combination of Cloud Computing and Big Data capabilities that sets out to revolutionize the economics of manufacturing. System Insights is a proud member of both AMT (Association for Manufacturing Technology) and NTMA (National Tooling and Machining Association). Follow System Insights on Twitter @systeminsights.