The age of Industrial Internet has given a new direction to acquire deep insight and visibility into the assets and operations of a company by integrating middleware, machine sensors, storage systems, cloud compute and associated software applications. The whole idea therefore is to formulate a method of transforming traditional operational process of business as the new IIOT offer the facility to receive feedback data, which eventually give deep insights through advanced analytical process.
Gain in business are achieved by gaining operational efficiency and acceleration in productivity, all which enabled to tackle unplanned downtime and increased efficiency, to reflect on the profits. Although the technologies and techniques used in existing machine-to-machine (M2M) technologies in today's industrial environments may look similar to the IIoT, the scale of operation is vastly different.
For instance, with the aid of Big Data in IIOT systems, large set of data streams can be analyzed online through cloud-hosted advanced analytics. Additionally, vast quantities of data can be stored in distributed cloud storage systems for future analytics performed in batch formats. These massive batch job analytics can glean information and statistics, from data that would never previously been possible because of the relatively tiny sampling pools or simply due to more powerful or refined algorithms. Process engineers can then use the results of the analytics to optimize operations and provide the information that the executives can transform to knowledge, in order to boost productivity and efficiency and reduce operational costs.
HOW CAN DATA ANALYTEC HELP IN DIGITALLY TRANSFORMING YOUR INDUSTRY?
Thorough understanding of the current situation of a manufacturing / production unit via an in-depth AS-IS Study > Define a new approach to adapt to the transformation [2B Phase].
Gather historical data of the production unit and Build Proof of Concept [POC] >
Strategize a policy to roll out the new model in the production unit
Installation of hardware, such as, sensors, RFID whatever applicable to strategic points to ensure gathering of raw data > Implementation of network and security layer >Develop real-time application to review current operation > Develop predictive models for inspection and take preventive measures.
Get advance alerts on potential failure points and real time insights about manufacturing bottle-necks >Get seamless updates via dashboards on Enterprise Applications >Inform maintenance staff in advance and avoid unproductive down-time / production back-log which result in revenue loss > Execute with confidence >
Klaus Martin Schwab, Founder and Executive Chairman of the World Economic Forum, attributed Industry 4.0 as a factor of social, economic, cultural and political upheavals that will unfold over the 21st century. Considering the widespread availability of digital technologies which were a by-product of Industry 3.0, the Fourth Industrial Evolution will rely upon the convergence of digital, physical and biological innovations.
With the rise of steam-powered factories during Industry 1.0 to the scaling of mass production and manufacturing in Industry 2.0 followed by global digitization in Industry 3.0, the new epoch of Industry 4.0 has been leveraging hi-end technologies like Robotics, Artificial Intelligence, 3D printing has created a whole new perspective the way humans exchange, create and distribute value.
This progression will profoundly transform institutions, industries, and individuals. More importantly, this phase of blitz-scaling will be guided by the choices that people make today. The world in 50 to 100 years from now will owe a lot of its character to how we think about, invest in, and deploy these powerful new technologies for the betterment of life.
The moment of change has come. It is here. It is already happening. Are you part of this?
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