When we think of the “Industrial Revolution” we think of the invention of the steam engine and iron structures such as bridges.  Today scholars and the media have added three more. The second one is the advent of mass production methods with Henry Ford’s Model T, the railroad in transportation and the telegraph in communications. The third one is mass computational power by computers.

Today, we are looking at the Fourth Industrial Revolution. The phrase was first introduced by Klaus Schwab, the executive chairman of the World Economic Forum, in a 2015 article in Foreign Affairs. It includes breakthroughs in emerging technologies in fields such as robotics, artificial intelligence, , the Industrial Internet of Things (IIoT), , fifth-generation wireless technologies,5G, and virtual reality. The blog will explain how each of these will change manufacturing.

The consulting firm Deloitte describes the smart factory as a flexible system that can self-optimize performance across a broader network, self-adapt to and learn from new conditions in real or near-real time, and autonomously run entire production processes.


Griffith “Bill” P. Taylor created the earliest term  “industrial robot” in 1937. It was a crane-like design that used powered by a single electric motor. It had five axes of movement, including a grab and grab rotation. The robot was automated through the use of paper tape with punches in it to energize solenoids creating movement in the control levers.

The first industrial robot of any significance, the “Ultimate,

was installed in the spring of 1961 in the General Motors plant in Ewing Township, NJ.. Its most distinct feature was a grip on a steel armature that eliminated the need for a man to touch car parts just made from molten steel.

Robots, as most people probably know, have had a major impact on car manufacturing . 

Their impact on manufacturing, in general, has created efficiencies from handling raw materials to packaging finished product. They can be programmed to operate 24/7 in lights-out conditions and the equipment is highly programmable for disparate uses

As the factory becomes more self-operating, with less human involvement, it needs  a different type of operational management.  This is where AI comes in. An article by Philip Kishmero in the website CIO lists some things it will do.

Smart maintenance – A study by the Wall Street Journal Custom Sudios show that unplanned downtime costs manufacturers an estimated $50 billion annually and that asset failure is the cause of 42 percent of this unplanned downtime. Predicting the future failure of a part or system is crucial for a manufacturer.   In addition, AI can predict the required maintenance to help extend the remaining useful life of the system..

AI and quality – AI can detect quality issues to make sure that the customer expectations are met

Humans and Robots – The International Federation of Robotics estimates that in 2018 there are over 2 million industrial robots in operation. In theory, as more and more jobs are taken over by robots, workers will be trained for more advanced positions in design, maintenance, and programming.

Gererative design – Using AI with high-performance computing and the cloud, engineers can generate more design options faster. As defined by the New Equipment Digest,  Designers or engineers input design parameters (such as materials, size, weight, strength, manufacturing methods, and cost constraints) into generative design software and the software explores all the possible combinations of a solution, quickly generating hundreds or even thousands of design options. From there, the designers or engineers can filter and select the outcomes to best meet their needs.


One ring to bind them

The Internet of Things, with sensors and controls, from controlling your house to traffic lights and power plant, has a specific Industrial Internet of Things related to the manufacturing and logistics industries. The sectors see it as an effective upgrade

The 5G network allows for up to one million sensors per square kilometer, as well as ultra-low latency (transmission slowdown), which can provide operators with real or near-time data from IIoT sensor-equipped devices to improve productivity. Manufacturers that can capture and crunch this information could produce actionable intelligence that increases productivity. 5G’s low latency and high-bandwidth capabilities can support this increasing data flow.

Aside from increasing throughput, analyzed data can also help reduce downtime. 5G-connected sensors can channel real-time information about equipment performance, ranging from vibration to noise data.

Combined with machine learning algorithms, this data can help companies predict when expensive equipment is about to fail, reducing the likelihood of expensive downtime.

When the network gives us an advanced warning that a piece of specialized equipment needs a repair, augmented reality using low-latency 5G-enabled headsets will make technicians more efficient. Level 1 technicians can travel to a site and have engineers at headquarters guide them through the repair process remotely via 5G networks, using context-sensitive 3D animations to walk them through the necessary steps


Image from Microsoft

While this technology has a major role in computer gaming, an article from the Manufacturing.net website says that a  growing number of manufacturing suppliers, including large automated equipment manufacturers, are utilizing the technology to provide their employees and customers with virtual hands-on instruction for operating machinery, troubleshooting and conducting repairs. One example is Lockheed Martin who uses Microsoft HoloLensheadsets to view holographic renderings of an aircraft’s parts and the instructions on how to assemble them. Microsoft HoloLens offers mixed reality solutions to increase communication and improve efficiency. The AR technology reduced assembly time by 30 percent and digitizing the workflow helped the company increase engineering efficiency to 96 percent.


The true power of the smart factory lies in its ability to evolve and grow along with the changing needs of the organization—whether they be shifting customer demand, expansion into new markets, development of new products or services, more predictive and responsive approaches to operations and maintenance, incorporation of new processes or technologies, or near-real-time changes to production. Because of more powerful computing and analytical capabilities—along with broader ecosystems of smart, connected assets—smart factories can enable organizations to adapt to changes in ways that would have been difficult, if not impossible, to do so before.