Digitization and automation
Despite all the efforts companies are making to improve the performance of their supply chains, relatively few have unlocked the full potential of digital technologies.
Playing a transversal role with the rest of the areas, we will support current disruptive technologies with the use of, among others, the following: Artificial Intelligence, Blockchain, Internet of Things (IoT), Digital Twins, Big Data and Data Analytics, process automation and robotics, Robotics and collaborative robotics, AMR and AGVs and sensorisation.
Digital transformation, a global and inevitable revolution, is driven by the confluence of different technological disruptions, such as Big Data and Artificial Intelligence, unprecedented connectivity through machine-machine and human-machine interaction, automation, augmented reality and blockchain. The digitisation of the supply chain promises to reduce inefficiencies and lower costs while improving flexibility, critical ingredients for reducing the environmental impact of operations.
Logistop aims to improve the sector’s logistics processes through digitalisation based on the following objectives:
- Development of digital transformation activities through the creation of working groups.
- Encourage the development of collaborative digital innovation projects among members.
Lines of action:
- Artificial Intelligence
- Internet of Things (IoT).
- Digital Twins (Digital Twin).
- Big Data and Data AnalyticsProcess automation and robotics.
- Robotics and collaborative robotics
- AMR and AGVs
The digitisation of logistics helps to increase speed, accuracy, safety, reduce costs and increase revenue. In addition, it promotes the sustainability of processes by helping to control waste and enhance opportunities for collaboration between companies. Through digitisation, the best use of logistics resources will also be sought to minimise the impact of the carbon footprint in supply chain management.
To successfully tackle digital transformation requires technology partners with a deep understanding of technology, processes and business models, as well as a broad strategic vision.
Trends in digital transformation
The technological components or foundations for whose development and application to the sector we work at Logistop are:
Artificial Intelligence (AI)
For knowledge extraction from existing data sources. Predictive analysis of demand behaviour, for example, is a direct application of artificial intelligence, which aims to develop techniques that allow computer systems to learn by themselves, i.e. their performance improves with experience. It is closely related to pattern recognition. It is a process of knowledge induction. There are many fields of application within the world of logistics and transport, e.g. demand forecasting, robots (physical or virtual). It draws on huge volumes of historical data and data generated in the present to predict the future.
One of the most interesting applications is the support of process automation RPA (Robot Process Automation Software) for the automation of management processes. AI can help to ensure that repetitive tasks can be done by the systems themselves.
IoT (Internet of Things)
The IoT connects billions of objects for high-speed data transfer, especially in the industrial and logistics environment. IoT systems allow companies to collect and analyse a large amount of data that can be used to improve the overall performance of logistics systems, providing various types of service. It is essential for the automated measurement and control of physical variables. The applications are very varied, from RFID tag measurements, temperature control, vibrations, luminosity, humidity, gas concentration, movement, geographical position and allows to automate by alerts deviations of out-of-tolerance values. Examples of applications include monitoring the temperature of a reefer container with fresh produce, alerting a package if it is knocked or issuing alerts in a warehouse if the oxygen concentration is high or low below tolerance.
These are virtual representations of real elements or processes, digital copies of the physical elements they represent, not only through their mechanical or geometric properties, but also through their behaviour and temporal evolution. It consists of creating a virtual model through the information available on a process, its production or operation exactly the same as the physical model at all levels. It combines technologies such as big data, modelling, sensorisation, connectivity, Internet of Things and Artificial Intelligence. Their application in logistics is diverse, ranging from helping to plan the logistics network, improving warehouse management or suggesting contingency actions in the event of incidents in the supply chain.
technologies help to collect and analyse large amounts of data that are acquired and stored. In logistics processes there are different sources of data from which to capture all the information, from customer orders, transport delivery notes, returns, fleet activity, to the tracking of goods with technologies such as RFID, data from sensors and cameras, etc. Big Data technology makes it possible to identify behavioural patterns and conclusions about the operation of the logistics process, transport, the state of loads, black spots, areas for improvement, etc.
The blockchain technology applied to logistics management will make it possible to store and share cargo information, processes and improve financial operations and contracts, among many other possibilities. In general, the logistics sector uses long and complex systems, some of them paper-based, to manage transactions. Shipping data, contracts, letters of credit and freight agreements are just some of the documents that need to be generated, tracked, handled and processed quickly between numerous parties. In transport and logistics, the application of this technology brings about a complete change in the way value is generated thanks to smart contracts, pieces of software that automatically trigger actions when programmed events occur. The main advantages of blockchain are the management and storage of information in a distributed and decentralised way, guaranteeing the trust and inalterability of data and processes.
Blockchain improves both traceability and data reliability. With this technology, supply chain data is recorded that cannot be altered, for example, who has been involved, when and how in a process (loading, picking, transport, reception, handling); this feature provides reliable traceability values in a way that reduces conflicts, increases trust between actors and ensures and increases the reliability of the system as a whole. Another important feature is that it drastically reduces the time usually spent on document processing.
High-power, high-density and scalable automated warehouses. Shuttle technologies; multilevel shuttle; multilevel AMR; skypod; adapted stacker crane.
High-power, high-density and scalable automated warehouses are, without a doubt, the immediate revolution in logistics, especially for two reasons:
- The powerand scalability in production that makes them attractive in long-term strategic analysis with variability of scenarios.
Something almost impossible a few years ago.
- The ease of adaptation to small or difficult spaces and small size solutions (microfullfilment)and the high stocking density of these warehouses.
There are as many ways of working as there are different needs. We find ourselves at a time of great proliferation of different solutions, but some of them with a low degree of maturity in terms of their capacity to solve certain scenarios.
Robotisation of order picking and product handling
Robotisation in factory production is widespread in almost all sectors and is generally assumed to be very cost-effective despite the complexity of some robotic manufacturing operations. On the other hand, handling operations have two brakes:
- Products very often do not have the necessary level of standardisation.
- The logistics sector, due to inertia, has not generally carried out this type of operation and, therefore, does not generally consider this type of operation and when it does, due to its lack of maturity or knowledge, it demands all kinds of return guarantees.
Handling in logistics operations, including factory logistics, is a revolution that has not yet begun to take off, but given its opportunity to improve productivity and quality, it has all the factors in its favour to occur in many, many scenarios.
All robotisation (unless it is extremely simple and with a very standard product) has a certain degree of uncertainty because of the need in many cases to design a gripper system, make a prototype and subject it to empirical tests before the final one, but, in many cases, the level of uncertainty in this engineering cost is low.
AGVs for stacker cranes and rack pullers. AMRs used in sorting and order picking.
The AGV world in its broad conception is already an ongoing revolution in logistics:
- The use of AGVs with forks for horizontal movements.
- AMR devices for picking at fixed workstations.
There remain, however, many pressing fronts for the maturation of these technologies (pressing because they will be the fuse of a much wider disruptive change for companies):
- The extraction at height from racks and placement of material.
- Height limitations.
- Temperature limitations.
- The ongoing application of artificial intelligence to enable them to interact with their environment.
David Ciprés, Javier Olmos, César Fernández-Pacheco, Leaders of Logistop’s Digitisation and automation Working Group