‘Internet of Things’ concept sweeps into industry
The “Internet of Things” is defined as: “the interconnection via the internet of computing devices embedded in everyday objects, enabling them to send and receive data.” The “Industrial Internet of Things” is this definition applied to value-added processes and manufacturing.
At a recent Department of Commerce-hosted international trade/manufacturing conference in Arizona, I had the opportunity to listen to a talk by Bob Witwer, vice president of advanced technology for Honeywell Aerospace’s Engineering and Technology Division. He discussed how this concept is revolutionizing industry across the world, making companies more efficient and profitable.
According to Witwer, we are now in what he refers to Industry 4.0. Industry 1.0 was the phase in the late 1800s where mechanization of labor expanded. Power sources such as steam and electricity were harnessed in the production process, thus allowing production to make a drastic leap forward from just a laborbased platform.
In the Industry 2.0 phase, the assembly line was established, allowing mass production to occur. This is the classic Henry Ford example in which he visited a meat processing plant and saw the systematic butchering and processing of animals into consumable meat and usable byproducts. He adopted this concept in his auto production plants. This was the age of industrialization that occurred roughly a hundred years ago in the U.S.
Industry 3.0, which started in the late 1980s/early 1990s, brought the use of computers and automation. This rapid processing of information allowed more efficient inventory planning. It also allowed companies to automate processes such as payroll that had previously been processed manually.
In the present phase, Industry 4.0, cyber-physical systems are being created to make the transition of data monitoring, data processing and implementation. This is the phase referred to as the “Industrial Internet of Things.” It features the interconnectedness of systems throughout the manufacturing process. This involves utilizing tools such as sensors and cloud computing to connect the entire production. The goal is to generate data analytics and gain a deeper insight into the manufacturing facility or an entire industry. Witwer believes that we are only beginning to see the benefits.
Sensors can be used on every piece of equipment not only to monitor the standard manufacturing process, but also to identify defects early before they go through production. This allows the company to be able to single out problems even if they are still within specifications, and to save on costs up front. Use of this type of technology also allows a company to test in stressful conditions such as weather and high/low temperature environments.
Maintenance is often thought of as a low-tech manual function. In Industry 4.0, companies can use technology to create condition-based maintenance systems that take information from all of the systems to determine sources of failures. This allows a company to be able to keep track of performance and to schedule maintenance. This approach has become standard in the aviation industry.
Better materials management is another objective of the latest phase. Having an interconnected system allows a company to identify every part that it has and to be able to determine tolerances. This allows for “smart” assembly. In a grander scheme, it allows for better asset management so that a production plant can run more efficiently. Ultimately, a better connecting of people to systems occurs or, as Witwer stated, “It can free up people’s hands to make better analyses and decisions. This engages workers.”
Moving forward in the Industry 4.0 phase, challenges do exist. The generation of data can pose a security risk for an organization, which has to determine how to manage and protect this precious resource from elements such as the competition. According to Witwer, companies operating in Industry 4.0 are sitting on a gold mine of information. Cybersecurity, which is protecting data from theft and spoofing, has to be built into any company’s network.
In a more capitalistic sense, a company’s data could hold value for the outside world because it could be extracted and exported to people willing to pay for it. Conversely, a company needs to determine what information from the outside it needs to gather, which can also pose a challenge. According to Witwer, data analytics, or the management of data, is becoming a huge field, “equivalent to what digital electronic engineers were in the 1980s.” Virtually every production plant is tied into a supplier/logistics base. A company also has to integrate its processes with these partners.
While challenges exist, new opportunities are being created to form strategic alliances, build new business models and create new methods of factory operations. These opportunities allow for “deep learning,” in which machines can learn without humans getting involved until the end of the process. According to Witwer, “If you don’t find a way to get started in the ‘Industrial Internet of Things,’ you will regret it. In today’s world, you have to start, measure, learn and repeat.”