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.

One of Logistop’s objectives in this area is to carry out technological surveillance and state of the art work in Spain, Europe and the world to identify trends of interest.

In the strategic line of digitisation and automation of processes for efficient and interconnected logistics, we work to:

  1. Dynamise actions within the platform to promote the exchange of knowledge and collaboration between companies.
  2. Generate consortiums to create proposals for new sustainable and collaborative projects.
  3. Collaboration with other working groups to identify research needs that can be covered through digitalisation and automation.

In today’s global marketplace, companies need systems that make them able to deliver products on time, maintain market credibility and introduce new products and services faster than the competition.

Historically, technological innovations aimed primarily at production processes, bringing greater digitisation and automation, have been seen as the main drivers of sustainable economic development and productivity growth. Collaboration between logistics companies needs to be encouraged to share information and encourage the use of digital platforms to develop standards that facilitate the deployment of collaborative and sustainable logistics projects.

Automation is evolving in a way that places increasing importance on flexibility, i.e. the ability of a system to adapt to changing market demands in terms of variations or changes in product and product quantity. Consequently, the importance of flexibility is progressively emerging in logistics automation, with a strong focus on the integration of automated systems with other flexible devices, such as flexible manufacturing systems (FMS) and AGVs.

This digital transformation of the sector can bring many advantages to individual companies and, above all, opens up new horizons for operations with a greater degree of collaboration. Greater homogenisation of processes is being sought to simplify operations and streamline information management in the chain.

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.

Key issues:

  • 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.

Key issues:

  • 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.

Digital Twin and IoT

In recent years there has been a boom in the use of digital twins (DG) in different sectors, logistics among them. The term digital twin is very broad and has many interpretations for Logistop’s different partners. There is interest in knowing what exactly it is and how it works, having a clear definition, what the value proposition of this type of technology is in the sector, etc.

IoT is used to optimise supply chain operations by facilitating the exchange of data between devices and users. This will enable companies to react more quickly and effectively to market changes. It is used to collect data from sensors and other devices, which are used to optimise supply chain operations. This facilitates the exchange of data between devices and users, enabling companies to react more quickly and effectively to changes in their markets.

Logistop will discuss the future and the trends that help the industry to make processes more efficient and sustainable.

Key issues:

  • Incorporate real-time information to represent and analyse an organisation’s operations.
  • Twins not only for their mechanical or logical properties, but also for their behaviour and possible future evolutions (scenarios).
  • Construction of virtual relational models, through standards that allow the aggregation of different models and interaction with other services.
  • Sharing of models between various agents in the same logistics environment (e.g. in a port, in a city, etc.).
  • Integration with other technological services: Big data, IoT, Artificial Intelligence.
  • Optimising data exchange between devices and users. This will allow companies to react more quickly and effectively to market changes.
  • Flexibility: Rapid integration of data from sensors and other devices, which are used to optimise operations in the supply chain.

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.

Key issues:

  • 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.
See calendar of events.

David Ciprés y Javier Olmos, Heads of Innovation for Digitalisation and automation of processes for efficient and interconnected logistics  at Logistop