Periodic Reporting for period 1 - TRACE (Integration and Harmonization of Logistics Operations)
Periodo di rendicontazione: 2023-06-01 al 2024-11-30
At the EU level, in spite of focusing on the low-carbon economy, synchromodality in logistics operations is unknown in the most regions of Europe. From an environmental perspective, while the majority of attention are on the shipping industry decarbonization, a systemic synergic approach in logistics, hinterland, and transport can significantly promote the environmental performance of freight transport.
There are four drivers that are considered the ones which can accelerate the door-to-door supply chain towards connective networks within a synchromodal framework:
(i) the high and unstable prices of fuel that triggers the necessity for cost-saving transport solutions;
(ii) the enormous rise in overburdened road infrastructure;
(iii) the increasing complexity of the supply chains world-wide that puts extreme pressure on the systems and increases the risk for critical failures and
(iv) increased environment-conscious and public awareness about road traffic side-effects on local communities.
Strict environmental regulations at interregional, and international level such as Paris Agreement, and International Maritime Organization (IMO) members’ agreement to reduce its emissions by at least 50% by 2050 compared to 20081. However, there are challenges for applying the synchromodal transport framework at port hinterlands. First, is networking and collaboration with the core of trust and customer relationship concept. The establishment of such a network is based on mutual respect and trust, as the most important prerequisite for synchromodal processes. Due to the fact that many entities are not willing to cooperate with competitors, a new way of thinking is required to generate a synchromodal network which is concentrated on trust and the advantages of cooperation instead of competition. The second limitation is complexity in planning. Planning and also the simulation of transport routes is vital to create an effective transport network. Items such as new customer preferences, route traffics, and accessible resources of logistics nods should be assessed and examined prior to planning. Monitoring and forecasting are crucial factors for optimization of the transport performances. Accordingly, a freight transport network is to be set up based on the demand mapping and forecasting tools. The third restriction is the connectivity of the existing different ICT systems and data-sharing platforms.
There are four drivers that are considered the ones which can accelerate the door-to-door supply chain towards connective networks within a synchromodal framework:
(i) the high and unstable prices of fuel that triggers the necessity for cost-saving transport solutions;
(ii) the enormous rise in overburdened road infrastructure;
(iii) the increasing complexity of the supply chains world-wide that puts extreme pressure on the systems and increases the risk for critical failures and
(iv) increased environment-conscious and public awareness about road traffic side-effects on local communities.
Strict environmental regulations at interregional, and international level such as Paris Agreement, and International Maritime Organization (IMO) members’ agreement to reduce its emissions by at least 50% by 2050 compared to 20081. However, there are challenges for applying the synchromodal transport framework at port hinterlands. First, is networking and collaboration with the core of trust and customer relationship concept. The establishment of such a network is based on mutual respect and trust, as the most important prerequisite for synchromodal processes. Due to the fact that many entities are not willing to cooperate with competitors, a new way of thinking is required to generate a synchromodal network which is concentrated on trust and the advantages of cooperation instead of competition. The second limitation is complexity in planning. Planning and also the simulation of transport routes is vital to create an effective transport network. Items such as new customer preferences, route traffics, and accessible resources of logistics nods should be assessed and examined prior to planning. Monitoring and forecasting are crucial factors for optimization of the transport performances. Accordingly, a freight transport network is to be set up based on the demand mapping and forecasting tools. The third restriction is the connectivity of the existing different ICT systems and data-sharing platforms.
The main idea is to share the available resources no matter the company they belong, integrate multimodal operations and conclude automated contracts upon the shared resources in real time to face disruptions or the need for logistics optimization/re-scheduling. AI/ML and blockchain are the core technologies that provide multiple opportunities for realizing the aforementioned idea and assist in coordinating different logistic networks. Specifically, predictive capabilities and an efficient event
detection (disruptions, need for sharing resources to meet overloading or partially loaded scenarios) mechanism are helping in the forecasting of the logistics workflows requirements in terms of resources and routes through the analysis of humongous volumes of recorded in real time and historical data. AI functionalities assist in resources
planning, route rescheduling tasks allowing industrial stakeholders to become more proactive and to able to account for complex factors that may affect the operation efficiency in terms of cost, delivery time and energy efficiency.
This leads to less routes, lower operational costs and increases the fuel efficiency of the vehicles. Apart from AI algorithms, blockchain operations facilitate the authentication, shipments traceability and financial operations in real time. Authentication is adopted for all the participating actors as well as shipments for having a continuous traceability during their trip. Additionally, when synchromodal operations or sharing the capacities of different logistics companies are the case, smart contracts and financial management are also performed through the provided distributed ledgers.
The platform and its underlying technologies can support any type of data-intensive ICT services (AI, Business Intelligence, etc.) from cloud to edge. The key functionalities supported by the platform are:
(i) Physical infrastructure and resources;
(ii) Cloud backend infrastructure;
(iii) AI/ML scheduling/optimization modules;
(iv) Blockchain infrastructure;
(v) Integration and harmonization module;
(vi) Events management module;
(vii) security and privacy protocols;
(viii) User interfaces.
detection (disruptions, need for sharing resources to meet overloading or partially loaded scenarios) mechanism are helping in the forecasting of the logistics workflows requirements in terms of resources and routes through the analysis of humongous volumes of recorded in real time and historical data. AI functionalities assist in resources
planning, route rescheduling tasks allowing industrial stakeholders to become more proactive and to able to account for complex factors that may affect the operation efficiency in terms of cost, delivery time and energy efficiency.
This leads to less routes, lower operational costs and increases the fuel efficiency of the vehicles. Apart from AI algorithms, blockchain operations facilitate the authentication, shipments traceability and financial operations in real time. Authentication is adopted for all the participating actors as well as shipments for having a continuous traceability during their trip. Additionally, when synchromodal operations or sharing the capacities of different logistics companies are the case, smart contracts and financial management are also performed through the provided distributed ledgers.
The platform and its underlying technologies can support any type of data-intensive ICT services (AI, Business Intelligence, etc.) from cloud to edge. The key functionalities supported by the platform are:
(i) Physical infrastructure and resources;
(ii) Cloud backend infrastructure;
(iii) AI/ML scheduling/optimization modules;
(iv) Blockchain infrastructure;
(v) Integration and harmonization module;
(vi) Events management module;
(vii) security and privacy protocols;
(viii) User interfaces.
TRACE builds upon and expands the concept of shared logistics by focusing its effort on the following research and innovation aspects:
(i) Multi-source data collection: Data will be collected and harmonised by various sources in real time. Information regarding the traffic conditions, freight location, delivery time requirements, available assets, network condition, available routes, cargo types etc. will be constantly monitored by the platform.
(ii) AI/ML for optimisation: The large volume of data collected will be processed via ML algorithms which will derive the optimal actions for the vehicles in order to optimize the velocity, emissions, the fuel consumption, time of deliver, asset sharing, logistic network merging, resource reuse etc. actions. This process will also be conducted in real-time and will give the operators the opportunity to adjust their planning accordingly.
(iii) Operator emergency controls: TRACE supports the proper interfaces for remote operators which can perform the appropriate actions in case of emergency or in case of re-scheduling.
(iv) Blockchain-based transactions: TRACE will deploy the blockchain technology to maintain the information security between the involved stakeholders, but also to utilise smart contracts as means to enforce the logistic sharing functionality
(i) Multi-source data collection: Data will be collected and harmonised by various sources in real time. Information regarding the traffic conditions, freight location, delivery time requirements, available assets, network condition, available routes, cargo types etc. will be constantly monitored by the platform.
(ii) AI/ML for optimisation: The large volume of data collected will be processed via ML algorithms which will derive the optimal actions for the vehicles in order to optimize the velocity, emissions, the fuel consumption, time of deliver, asset sharing, logistic network merging, resource reuse etc. actions. This process will also be conducted in real-time and will give the operators the opportunity to adjust their planning accordingly.
(iii) Operator emergency controls: TRACE supports the proper interfaces for remote operators which can perform the appropriate actions in case of emergency or in case of re-scheduling.
(iv) Blockchain-based transactions: TRACE will deploy the blockchain technology to maintain the information security between the involved stakeholders, but also to utilise smart contracts as means to enforce the logistic sharing functionality