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How Could a Factory 4.0 Appear?

How Could a Factory 4.0 Appear?

As we enter the second decade of the 21st century, technologies essential to the so-called "4th Industrial Revolution"—including artificial intelligence, sensors collecting real-time data in a so-called "Internet of Things," collaborative robotics, industrial robotic automation, among others—still feel like science fiction. However, they are rapidly maturing.

What may a factory 4.0 resemble, especially when compared to a factory in 2023? We shall examine the potential applications of these new technologies in this essay using Josie, a fictitious owner of a factory 4.0, and her typical day. Although it is theoretical, this essay will create a gateway into the possibility of 4.0 manufacturing using current data and technologies.

Starting the Day: Digital Twin Check-in

Josie opens her phone to find messages from her smart factory informing her that 20 electronic chipset assemblies have been produced throughout the course of the night and are awaiting her approval.

She logs onto the facility's digital twin portal on a tablet as she gets ready for work. She moves to the descriptive view of this digital twin, which displays a graphic depicting the locations of all the factory's assets. She sees a three-dimensional map of the three-story smart factory on the display. Josie closes in on Level 3, where the QC room's circular conveyor is home to the 20 chipsets.

The QC room at this smart factory is equipped with a number of cameras and sensors, allowing product inspection to be done outside of the clean area. Josie jacks into a set of visual inspection cameras by tapping the space in the digital twin. Josie can now see the assemblies up close from her kitchen table thanks to her positions all around the assemblies.

When she is satisfied with the work after checking the initial assembly's soldering and other crucial components, she swipes it to the right, pushing it into packaging. After she consumes her breakfast, she follows the same process for the other 19 chipsets, pausing only for two to receive a second in-person inspection.

The Commute: Mobile Logistics

Josie changes to the informative twin view, which shows all the various operational and sensor-related data for each asset, as she gets into her automobile. She finds three mobile manufacturing cobot cells (MMCCs) that were plugged in overnight while navigating to the main factory floor on Level 2.

When Josie highlights them and looks over their specifications, she discovers that each is going to need preventative maintenance (PM) in the near future. Josie directs them to the maintenance bay on Floor 1 for an early PM, being proactive. She observes them via the digital twin as they independently detach from their stalls, arrange themselves in a straight line, and board the elevator.

Josie switches to the digital twin's predicted vision as she relaxes in her seat and watches the automobile drive itself across a congested motorway. The predictive view, which is concentrated in Level 1 of the smart factory, will assist in scheduling the workday by making predictions about upcoming events including inbound and outbound logistics, manufacturing quotas, and other scheduled events.

Josie notices that four of the ten loading bays on Level 1 are now filled by trailers being loaded for distribution. She also observes that five incoming trailers are anticipated throughout the day, with the first one arriving at 8:30 a.m. This arrangement would typically worry even an operations manager with experience. Josie opens the predictive scheduling tool without hesitation.

The predictive scheduler tool gives predicted fill times for the four docked trailers and displays the status, location, and load size of all inbound assets in real time. She instructs the yard management system (YMS) and transportation management system (TMS) to jointly produce 1,000 possible schedules, arranging the vehicles to avoid needless congestion or delays.

The scheduler gives Josie an optimum sequence with precise times and marked directions for each vehicle after a little while. Josie accepts this timetable and sends the change to his gates and docks so that delivery vehicles will be alerted and given directions automatically.

Punch in: Cobots Roll-out

Arriving at her fancy factory is Josie. She enters the warehouse and shakes hands with a few employees who had just arrived. A group of warehouse cobots are being deployed and set up for the day's job.

A mast and lift cylinder with forklift prongs that lower into a cart on top of an omnidirectional mobile platform make up each warehouse cobot. Imagine a forklift tied to a cart with no driver's seat and a sizable, commercial Roomba underneath it.

The large boxes and barrels kept on the shelves of the warehouse are loaded and unloaded by warehouse cobots, who also transport them to their final destination. 

Each employee attaches a data-link, a kind of short-range transponder that resembles a walkie-talkie, from their assigned cobot to their belt so that the cobot may follow them from a safe distance. Warehouse cobots are controlled by their human managers while being less autonomous than other cobots in Josie's workplace since they are more adaptable to the dynamic nature of inventory management.

Josie rides the elevator up to Level 2, where she reunites with the assembly line with the help of one of the MMCCs she sent for maintenance. She takes in the remarkable piece of equipment; unlike warehouse cobots, mobile cobot cells are significantly larger and more sophisticated. 

Each cell is around the size of a full-sized bed and is equipped with a cobot support arm, a workstation for human employees, and a piece of modular equipment designed specifically for the task that each cell is assigned. Josie notes that this MMCC is a soldering cobot since it has a soldering gun attached to the end of its seven-axis arm and is carrying big spools of wire solder.

Josie observes the cobot return to its position in the production line as the liftgate to Level 2 opens. Its arm starts to solder components that are coming down the production line once it has parked itself in the appropriate location, which is indicated by a box drawn on the floor. The MMCC can offer autonomous manufacturing for straightforward, one-step processes without the need for a human supervisor.

Josie observes a technician approach the cobot, board it, and stand behind the steering wheel as she makes her way to her office. The technician parks it further down the line, switches to manual drive, and then grabs the robotic arm's soldering gun. With the help of the cobot's haptic feedback arm, the technician uses the workstation to begin work on a complicated electronic assembly.

Josie enters her workplace and quickly gets to work on the tasks for the day.

End of the Day: Lights Out

Josie is about to depart her smart factory after a long day of emails, conversations, planning, and process optimizations, but not before she checks in with the digital twin one final time.

She evaluates the day's work and the condition of the production lines. 152 electronic assemblies were created, checked, and packaged during the workday, and 10% of the warehouse inventory was sent to distribution. She also notices that they need to replace their internal supplies of indium, a metal required for their products. She makes a notification for the procurement specialists so they are aware of how much to order and where to send it as soon as possible tomorrow.

Workers hang up their hardhats while simple soldering, assembling, packaging, and many other jobs that do not require a person are still being carried out on the production line by cobots. The cobots are all scheduled to park themselves in their charging ports at 2 AM by Josie as she makes her way to the elevator. She waits until everyone has left the factory floor before turning out the lights. Cobots operate without the need for lights, although it is unusual to hear spinning servo motors and occasionally see a flash of metal in the shadows.

Digital twins are lovely, but nothing beats the human eye, Josie thinks as she descends to Level 1 and takes one final stroll through the warehouse. She observes a concentration of product on one side of the warehouse, which could make staff' efforts at unshelving difficult. She notifies other users on her digital twin to start distributing these items among shelves tomorrow. As she exits the storage facility and gets into her vehicle, Josie wirelessly activates the factory's security system.

After-Work Firefighting

Josie receives a late email from one of her prime contractors requesting an instant design change as the car turns on and starts to navigate to her house. Normally, revisions entail a total overhaul of the assembly lines, a halt in production, and difficulties for everyone involved—but not for Josie.

She downloads the revised designs into the twin and asks for a report on how this will affect the manufacturing timeline. An new assembly line, materials list, and cobot organization layout are generated after a short while. A straightforward, actionable list of activities to retool the production line for this new iteration is then provided by the digital twin dashboard, which Josie can begin carrying out tomorrow.

She finally puts the tablet aside after being relieved that the fire was effectively put out. The fact that operations managers in the past were so cut off from their factories is almost inconceivable, and Josie couldn't comprehend how challenging this position must have been before the development of this technology. She is relieved to be able to leave her smart factory job when she pulls up to her home, and she feels secure knowing that a vast network of sensors, robotics, automation, and control systems are working to benefit her even while she sleeps.

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