Digitalisation and automation of processes for efficient and interconnected logistics
Logistop’s strategic line of Digitalisation and automation of processes for efficient and interconnected logistics aims to boost actions within the platform to promote the exchange of knowledge and collaboration between companies in the field of digitalisation and automation.
Standardisation and cybersecurity
Data is an increasingly valuable resource that can be used to improve the efficiency and competitiveness of products and services. Companies that know how to process and use data intelligently will have great power in the market and will shape the future in an increasingly interconnected and automated environment.
In this strategic line, tasks and activities will be carried out to promote standardisation and establish policies with regard to sharing data and events across organisational boundaries. Tools and platforms for data collection, distribution, management and analysis, information semantics and ontology systems, data access rules, encryption and authentication/authorisation, information exchange through data spaces aligned with initiatives such as GAIA-X, IDSA, FIWARE, etc. will be analysed.
- Alignment with the Common European data spaces strategy.
- Encourage the use of Blockchain technology for data exchange and decentralised collaboration between agents.
- Integration of IoT and Blockchain technologies to improve the management and control of operations.
- The lack of standardisation of operations, packaging and information is a recurring theme in many of the conversations in the industry and among our partners. The working group launches different initiatives to encourage the adoption of standards, promote their use among the logistics community.
Artificial Intelligence and Data Analytics
Artificial intelligence (AI) is increasingly used in the logistics and supply chain sector. It has the potential to optimise processes, reduce costs and time, and significantly improve the quality of products, services and processes.
Supply chains are becoming increasingly complex, as companies develop their objectives by achieving the most efficient flows along the chain. This requires tools such as artificial intelligence (AI) to be integrated into a multivariable system in which aspects such as visibility, flexibility, traceability and security are key.
We will discuss the use cases and advantages of applying AI and data analytics in logistics and supply chain to optimise processes, reduce costs, time and significantly improve the quality of products, services and processes.
- Anticipation is the key to many logistics operations, predictive analysis of demand behaviour is fundamental to optimise processes.
- Designing the most efficient flows possible, i.e., achieving more reliable, faster, better integrated chains that at the same time reduce costs and have less impact on the environment.
- Integration of heterogeneous data sources for the development of multivariate algorithms.
- Development of prediction and optimisation algorithms applicable to logistics planning.
Automation and advanced robotics
We must continue to make industry and logistics more 4.0/5.0 driven, which means even more automated. Collaborative robots, autonomous mobiles, advanced intelligent automation, machine vision, etc. offer much more flexibility than traditional automation infrastructures.
- Avoid and/or reduce tedious operations for operators.
- Efficiency and repeatability of operations.
- Development and evolution of autonomous vehicles in logistics processes.
- Reduction of logistics costs through efficient handling.
- Drastic reduction of errors associated with manual operations.
- Increased safety in operations.
- Reduction of damage in the handling of goods.
- Stock control.
- Optimisation of storage space.
David Ciprés y Javier Olmos, Heads of Innovation for Digitalisation and automation of processes for efficient and interconnected logistics at Logistop