When it comes to plant digitalization efforts, plant operators are directly involved managing a somewhat daunting list of tasks. Factories and industrial facilities can be enormous in size and scope, with high-powered machinery and huge footprints to cover. The image of a foreman walking the line, checking dials and readouts, is simply impossible for a facility that covers multiple acres. By the time the operator gets to one end of the factory, something at the other end might have already changed.
Until fairly recently, monitoring a plant’s conditions had to be performed by a team member who was able to be physically close to the machinery and equipment. Industrial digitalization and the industrial internet of things have leveraged the falling cost of sensors and expansion of industrial wireless networking to bring that information from every part of a factory floor to the control room. Some plant operations, in response to huge amounts of ground to cover, have gone as far as developing indoor positioning systems to track equipment on the factory floor.
Industrial digitalization allows a plant operator or manager to finally utilize the at-a-glance information environment that pilots have enjoyed since the 1970s. Plant digitalization, in which every part of plant operations is monitored, controlled, and even simulated digitally, is one development resulting from earlier industrial digitalization efforts.
One advantage of plant digitalization is reducing redundancies in personnel and hence, decreased costs. For plant operations that rely on direct human monitoring of equipment, there is an inefficient duplication of effort and skill due to the expertise required in both the observing operator and the manager making decisions about plant operations. Both parties needed to know what the readings on the dials mean in order to communicate effectively. A plant with sensors networked to a central location doesn’t require a local human operator to spend time checking settings and levels.
Another advantage of plant digitalization comes from awareness in maintenance needs provided by a thoroughly sensorized facility. For example, with inexpensive, networked sensors, every motor on a conveyor belt can be monitored in real-time, alerting operators to developing problems such as excess vibration, increased temperature, or belt slipping. Taking a problematic motor off the line during a pause in production might be cheaper than letting it break and have products pile up on the floor if the motor fails. Before plant digitalization, many of these issues went unnoticed until they caused equipment failure.
Plant digitalization serves as an enabling technology for many other smart enterprise technologies. The live stream of equipment data can be linked to process simulation software to provide important real-time updates to a digital model of a process. These data are also important for building digital twins, in which an asset or process is closely modeled in software. With a fully digitalized plant, the operations data required to implement digital twin technology is being collected for every asset. By feeding these data into digital twin software, a faithful representation of an asset can be modeled in software.
CThe sheer volume of information being produced on a day-to-day basis meets one of the most important requirements for building and deploying industrial AI. When contemporary artificial intelligence software is deployed, it must be trained on historical operations data. The artificial intelligence software searches these data for patterns and relationships, and the more data on which the program can train, the more robust the industrial AI will be. Day in and day out, a company practicing plant digitalization is establishing a trove of information that can be utilized by this powerful tool.
Given how many advantages plant digitalization can provide a company, it is important to understand why a firm might be reluctant to implement these changes. One reason might be because management and operators already think they have a digital plant; after all, each machine has a computer that controls it. Unless this information is being brought together and being used to drive decision-making, then the company hasn’t achieved plant digitalization.
Additionally, initial setup costs might be high. When Toyota implemented a digital tracking system and allowed its software to recommend changes to an already lean supply chain, the car maker did not see a return on their investment for nearly 14 months. Most businesses have neither the luxury of time nor the capital on hand to be so patient.
Plant digitalization requires a new, broader kind of expertise. It’s extremely important for plant owners and operators to make sure that the employee with the expertise is the one with the authority to implement any required changes. This source of conflict is to be expected; it would be difficult for an operator who has seen dangerous equipment failures to accept recommendations made by a team member looking at a computer screen.
How does plant digitalization differ from digitization?
During the 1980s, microprocessors and electronics reached a price -point where it became affordable to replace the electric and hydraulic controls on most equipment. This “swapping out” of analog controls and readouts to digital solutions is referred to as plant digitization.
Plant digitalization differs from industrial digital transformation and involves networking all the assets throughout a plant and connecting the data streams to the decision-making process rather than simply replacing existing systems.