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This topic traces the progress from Industry 1.0 to Industry 4.0, and describes the promises and challenges of Industry 4.0.
The progression of industrial advancement can be divided into four broadly themed periods:
Industry 1.0 |
The Industrial Revolution was the transition in Europe and the United States from largely agrarian economies to new manufacturing-based economies. This revolution, starting around 1760, was largely driven by the invention of the steam engine. |
Industry 2.0 |
The Second Industrial Revolution, starting around 1840, was characterized by the move from steam power to electrification for assembly line methods, and a focus on productivity. |
Industry 3.0 |
The Third Industrial Revolution, or Digital Revolution, was characterized by the introduction of computers and electronics for automation, starting in the late 1950s. |
Industry 4.0 |
Today, the world is in the Fourth Industrial Revolution, which is characterized by the rise of digital artificial intelligence (AI) and data-driven processes. |
The big promise of Industry 4.0 is that the rapidly expanding list of smart initiatives includes not only smart factories, but also to name a few:
The Fourth Industrial Revolution creates a vision for the future that is dependent upon solving a bold set of technology development and integration challenges. Realization of the Industry 4.0 vision requires at a minimum:
The progress in both initiative 1 and 2 above has been impressive. The number of deployed smart machines, additional sensors for data collection, and automated processes has improved productivity and safety in almost every industrial setting. This trend continues and expands as ROI benefits are documented, and older equipment and facilities are replaced.
The focus of this document is primarily initiatives 3 and 4 above. Continued progress on new software applications that use data driven models requires a cost-effective way to get data off the edge and into a data center. The data center is where data is accessible to specialized personnel and tools. Most industrial facilities can deliver a virtual tsunami of data. However, only a fraction of the available streams of telemetry is used regularly. There must be investment that is focused on improving data management between the edge and core or cloud before initiative 4 above can be realized.
The commercial software industry and the open-source software communities have made tremendous advancements in big data storage solutions and data science tools for model development. The movement of data from source to processing plant, and the movement of applications that are developed in a central plant back to the edge, are complex problems for most organizations developing Industry 4.0 capabilities. The tools and techniques used by the Internet scale technology companies like Uber, Facebook, Google, and Microsoft are now accessible to the pioneers of Industry 4.0. The biggest remaining challenge is building better bridges between the data producers at the edge and the big data technology in the data center.
Over 250 years elapsed between the inventions of the steam engine and the first modern digital computer - the defining technologies for Industry 1.0 and Industry 3.0. Advances in the design of the physical stock that is used in industry drove many of the productivity gains throughout those early periods.
With the advent of Industry 3.0, software became a new source of automation control and productivity gains. The importance of the programmable logic controller, which was introduced with the digital era, is still preeminent today. Hundreds of new models are available, with dozens of programming languages, and readily available books and training.
Industry 4.0 is even more software-driven, but now the focus is on the interface of cyber systems to physical equipment. All of the technology that is required to transform factories into smart factories is available now.
The exact cost and ROI of transforming industrial facilities is uncertain. So, the cost of large-scale replacement of traditional software systems with Industry 4.0 systems would certainly be too great and disruptive. The transition to Industry 4.0 will be incremental. Any new systems must interface with many of the software systems providing functionality in response to requirements defined some 20 to 40 years ago.
Industrial plants of every age that are trying to maintain high uptime availability and low operational overhead must determine if the cost is worth the ROI.