Machines have already begun making factories their dominion. Walk into any modern factory of modern times, and you will certainly come across a myriad of devices working in tandem, all autonomously. Automation is a thing of history now. What calls the shots in the factories of the future is the artificial intelligence that drives the machines to function all by themselves. And when production can become autonomous, why can’t the logistics inside the factories? Do we need humans inside the factory floor, carrying goods from one place to another and just being an agent of transportation, when there is so much more than a human can do? Yes, the future of manufacturing won’t need human intervention anymore, as AI-driven intralogistics will bring in complete autonomy in the factory operations, while human operators will simply need to monitor the performance of the movable and immovable assets.
Yes, tomorrow our world won’t need humans to operate forklifts and to manage warehouses too. Forget autonomous manufacturing of products, even the logistics will be taken care of by the self-minding vehicles operating inside the production floor. And we won’t need any more training for the human person in the factories, you can rather say that the training costs will dip sharply as a piece of code will be enough to train the robotic personnel to execute their operations effectively.
If your mind has already begun digging into what all technological drivers will enable such smart factories, then here it is. The emerging technologies like AI, deep learning, 5G, IoT, and computer vision will breathe life into autonomous intralogistics and will empower the autonomous systems that will control the factories of the future. Don’t be surprised if you find drones hovering across the length and breadth of the airspace inside the factories. The connected ecosystem will take the future of manufacturing beyond imagination.
Self-navigating robots
I know this is not something too transformative. We already have robots moving inside the factories, taking goods from one place to another. The future of manufacturing will have the mini-robots pick goods from one site and move them to an inventory storage location. These robots will work in tandem and will be able to coordinate among themselves, just so that democratized intelligence can come into play. In case one robot goes down, the backend control system will detect the malfunction and then all the other robots will coordinate among themselves by exchanging information, to decide which robot(s) must take up the additional responsibility of the failed robot. The coordinates of the failed robot will be quickly checked and a drone will be dispatched to reach the location and lift the malfunctioned robot from its location so that it does not become an obstruction in the operations.
Today, the robots also follow a guide, like a line to follow or a path encoded in them. However, going forward, the robots are certainly going to chart their course. They will be sapient enough to figure out where to move, how to move, and when to move. We shall delve deeper into the robot movements in a later section. However, gone are the days when we would have to monitor how the robots would move. The future of manufacturing will have the robots navigating all by themselves, once informed of the starting point and the destination.
Autonomous Forklifts
The factories of today have humans controlling the forklifts and stacking goods on the shelves. This not only adds to preventable manual labor but also leads to training expenses each time new human personnel reports to work. The future of manufacturing is not going to be the same. The factories of the future are going to utilize humans for a much more valuable role, rather than a task that can be automated.
Autonomous forklifts are the future of smart factories. Connected to an ecosystem, they will move around the production floor and will pick items from one place to deliver them to another. The forklifts will move around autonomously with sensors all around them. The moment they encounter a fellow forklift, the collision avoidance algorithm will kick into action and halt the two forklifts. Moreover, the forklifts will also assess the weight of each unit of goods and will decide the number of packages it can lift at once. Computer vision will help to evaluate the dimensions of the object by calculating their major axis and minor axis, to precisely calculate their size and their weight. Once done, the packages will be stacked by a machine, which will communicate with the forklift to command it when to lift the stack. Also, while stacking, in case the forklifts detect weight above the permissible limit, then the stacking machine will be alerted to stop the stacking for a moment and begin stacking the packages once the next forklift appears.
Navigation of the autonomous forklifts will also incorporate an algorithm so that they move in tandem between the source and destination. Moreover, democratized intelligence will come into the picture again, as a malfunctioning forklift will alert the backend system so that another recovery vehicle can reach the place and move the forklift to the maintenance center. Moreover, another forklift will take up the responsibility of the stack of the failed forklift. Autonomous maintenance procedures will be set into action for repairing the malfunctioned forklift.
Wait? Are we forgetting something? I guess so! We are missing the ‘predictive maintenance’ aspect. Yes, if a forklift begins experiencing some technical glitches, it can quickly relay the information to the edge computing system, and the needful decision will be taken very close to the forklifts. No latency, no delay in decisions. Instantaneous decisions will drive predictive maintenance routines. Furthermore, asset prognostics will also keep evaluating the remaining life of the forklifts and when a forklift approaches its end of life, the factory control system can automatically place an order for a new forklift to be deployed on the factory floor. This will ensure that a new forklift is ready for replacing a failed one, thereby ensuring no hindrances in the operations.
In-Factory Navigation
‘How will the forklifts and the robots navigate inside the factory’ remains a question in this blog. Are we going to have line-follower robots or bots following each other like sheep? Well, the answer is ‘Maps’. Yes, the robots are going to read maps inside the factories of the future, just the way we read Google Maps on the roads. The forklifts and the bots will have in-factory maps that will help them navigate on specific routes and detect if any particular route is blocked. In the latter case, the robots will use routing algorithms to quickly figure out an alternative route to reach their destination.
Using maps and routing mechanisms, the forklifts will reach the warehouse. Once the Warehouse Management System detects an incoming forklift, the barcode on the packages will be scanned and the correct shelf spaces along with their locations will be transmitted to the forklift. With the coordinates of all the shelves in place, a route through all of them will be developed using the shortest path algorithm or minimum time algorithm. And lo, behold! The forklifts will carry the goods to their rightful place in no time.
Heat maps developed out of the movement and clustering of forklifts will also give insights into which products are getting stacked more than the average and which areas need more space for movement of the forklifts to avoid jams on the routes.
5G to drive connected ecosystems
Connected ecosystems need high-speed communication between the entities in the IoT network. Performance of connected systems and edge analytics will depend on high-fidelity communication, which can also handle the enormous amount of data being produced and churned for insights. 5G comes as the driver of such communication and factory ecosystems will be connected over 5G networks to ensure that IoT data production, communication, consumption, and interpretation happens seamlessly without the communication network getting overwhelmed.
Drones in the air
Manufactured goods don’t need to be transported to and from the warehouse only by forklifts. The drones can take the intralogistics paradigm notches higher than what we have discussed so far. Drones can easily pick the stacks of similar items from the dispatch center and fly off to the warehouse. While entering the warehouse, they pause for two seconds at a barcode checkpoint, and based on the product code they are carrying, they can be informed of which shelf space to place them at. A route gets autonomously created in the drones’ system and they simply fly the packages to the shelf and place them at the right location.
The collision avoidance algorithms and democratized intelligence can very well work for the drones ecosystem too, just the way it works for the forklifts.
In a nutshell
The future of manufacturing is going to undergo unprecedented transformation by the next decade. And much of what we seem to intuitively believe lies in the capacity of humans alone will soon pass into the able hands of technology. AI, drones, edge analytics, 5G, and in-factory navigation will all be the new reality of tomorrow. AI-driven intralogistics is the Idea74 of tomorrow.
