- August 12, 2020
- Posted by: netsetadmin
- Category: Artificial Intelligence
Artificial Intelligence can succinctly be stated as the ability of machines to think and reason by themselves. This technology must be understood in a broad sense as when we talk about machines, we can extend it to robots, devices, and/or software or complex systems.
When we refer to thinking and reasoning, we are making a simile regarding the cognitive capacities of our brain, not to the fact that human characteristics are provided to silicon and bits, and when we say by themselves, we mean the characteristics developed and provided by their creators to such machines or systems, not by magic or independent evolution.
Artificial Intelligence’s Ability
The most considerable part that interests us is that AI is the ability of a system to interpret external data, which can be collected directly or indirectly and perform actions, flexible and adaptable, from the knowledge of said data.
Artificial Intelligence is generating many new applications in various sectors and environments and several of them are closely related to the logistics sector.
AI in Logistics: Transformations Occurred for the Good
One of the critical aspects of logistics is having the ability to forecast production and react in time to customer demand. The logistics and transport operators have become technology companies that offer planning and management service to the supply chain.
It is a matter of fewer wheels and more Intelligence!
Data analysis using big data technologies and the use of machine learning are clear bets, but not the only ones. We will no longer be able to face the logistics sector without taking into account the robotics but also portable devices that guarantee ubiquity in intelligent operating environments.
With all the praises being taken by AI, there are many business owners and experts who believe that many other robust technologies will play their individual part in transforming the logistics sphere. They assert that blockchain will be the definitive technology in the tracking and identification of goods and IoT devices will essentially be used for control and security in the supply chain.
And truly, the maturity of all these technologies will undoubtedly facilitate their implementation in a sector that does not want to be left behind in an increasingly digitized industry.
The applications of artificial intelligence in logistics has enabled a radical change in the work systems in the supply chain. Companies have gone from a reactive scheme in which logistics operations are based on multimodal logistics network that serves the main objectives of personalization of services, automation of processes, and optimization of controls.
Digitizations and standardization, in other words, and to a certain extent ‘Artificial Intelligence’, has played a decisive role in maintaining the customer’s supply chain, even during the crisis. There is a live example set by Sixfold who published a gone from a reactive scheme in which logistics operations are based on free live map of border crossing times for trucks to enable Europe’s supply chains to understand expected delays in shipping.
The company’s mission was to provide its customers- globally acting manufacturers, logistics and retailers service providers with real-time and predictive visibility over their shipments, allowing them to be aware of the where the shipments have reached, the approximate time of their arrival at their facilities and crucial delays border checks if any.
[Predictive analysis, allows operators to control the different operations in real-time and help make decisions based on data and facts.]
In industry 4.0, businesses have made groundbreaking developments leveraging Artificial Intelligence and Machine Learning with smart warehouses that combine interconnected technologies to form a feasible ecosystem that manages all business operations, from supply to delivery, via complex AI-ML algorithms.
Many companies have introduced and implemented the concept of smart picking systems which are reliable, flexible, and highly efficient solutions for warehouse management, factories, and supply chains.
Such systems integrate robots, automated management systems, order preparation stations (picking), and a recharging unit.
[The delivery and start-up time for installation of this type is about 3 months.]
The robots, in charge of transporting the racks to the picking station, stand out for their:
- compact size,
- great mechanical resistance,
- high speed,
- precision in movements,
- navigation with QR code,
- anti-collision system,
- automatic battery charging,
- 24-hour non-stop operation hours with automatic charging, and
- multi-robot interactive learning.
The advantages of such robust AI-powered systems are extensive, although their high productivity and scalability stand out; reduction of operating errors and a 50-70% reduction in labor costs.
Another point of interest for current logistics needs is their great flexibility to adapt to the needs of each moment. Thus, the installation can expand the number of robots to cover periods of high turnover, simply by programming and adding new robots to the existing ones.
Their characteristics make the investment risk comparatively lower than other solutions, mainly due to the flexibility of the system. They can even allow relocation to a different warehouse, without the need for great expense for adaptation and start-up. Another interesting aspect is the saving of space in the warehouse, where such robots maximize it and provide savings of up to 30%.
Despite all these witnessed benefits, fully automated warehousing has not been achieved, nevertheless, the days are not too far when the gaps will be filled, bridging machine learning with technological concepts.
[Prefer Reading: “”Emotion Analytics: Can Robots Understand your Feelings?”]
Applications of Artificial Intelligence in Logistics
Many applications of Artificial Intelligence have been implemented and put to use at different unique levels, but still many are in development with a view to reach their full potential in the coming years.
Some practices already established in the sector include the following:
#1 Prediction of Consumption Trends
Artificial intelligence makes use of big data for logistical purposes: it crosses internal information such as sales records with data extracted from forums, social networks, or other Internet sources.
In such a way systems are then capable of issuing deductions on the consumption intention of users, and, thus forecasting the behavior of demand. This serves to start anticipatory logistics and prevent stock-out-of stock or avoid storing excess merchandise.
In this way, the wastage of resources is mitigated.
#2 Automation of Transfer of Products in Warehouse
One of the greatest exponents of AI in logistics is the automated warehouses, that merges two major and fundamental systems robotics applied to warehouse and management software. Together they carry out transport and product placement operations autonomously.
Automatic Pallet Shuttle system, an example of the application of artificial intelligence in logistics.
This shared work generates patterns over time that are continuously analyzed. In this way, artificial intelligence helps to better allocate resources and correct movements in case of variations in the circuits.
#3 Selection of the Most Efficient Transport Routes & Journeys
The coordination of logistics transport is easier with AI and adopts two aspects:
-Management of Intralogistics Movements:
The warehouse management software saves a digital X-ray of an enterprise’s facilities and records all movements. The program processes this data and organizes the movements of goods, whether they are carried out by robots or automatic systems or by operators assisted by handling equipment.
-Management of Freight Transport Fleets
AI technology interprets and incorporates updated traffic information into local systems. With this, the software traces the most suitable routes for the delivery of different types of goods and corrects the itineraries in real-time in case of incidents.
#4 Greater Control of Information in Supply Chains
The automation of processes in the improved supply chain with the presence of artificial intelligence opens the door to the maintenance of inventories in real-time, the issuance of instant supply orders, or the precise tracking of orders, among others.
Furthermore, the integration of data and the improvement of traceability systems allows responding to the user’s needs. For instance, the common question of ‘where the purchased package is located can be nimbly solved with implementing chatbots equipped with the intelligence of AI.
The revolutions brought up by the evergreen technology of decades (AI) in the domain of logistics is highly convincible and appreciable which has lowered the risk of errors, made supply chains work with precision with fewer inefficiencies, eradicated most of the repetitive tasks, and paved the path for strategic decision making.
Thus we can now understand that AI in logistics has optimized processes and has avoided mistakes that humans could probably make or miss and have enabled businesses to predict future opportunities and challenges.
Logistics: Thank You AI!
If you have any queries regarding Artificial Intelligence and its descendants, (machine learning, deep learning, natural language processing, don’t hesitate to get in touch with Appknock, a growing enterprise dealing with cognitive technologies and is a top augmented reality app development company in the town.