Nowadays the world of the analysis is changing quickly, the reason behind is the development of new intelligence systems able to respond to different questions thanks the improvements of so-called machine learning and the numbers of Data available by Smart Device and IoT. This mix of computing power and Data to be analysed created the opportunity to design new algorithms.
In this forecast is born the concept of Predictive analysis. So far, the aim of the pluralities of systems are designed with the idea of increasing the efficiency of inefficiet processes, based with the data collection and subsequently different way of optimizations. The predictive logistics should be considerate as the evolution of that.
The logistics fields has been involved in particular for the optimization of the booking related to how and where allocate the own distributions capacities. For the major Maritime Companies Line these new models are really attractive, really tangible, delivers ready-to-use capabilities to improve container and vessel fleet utilization. The mining and automatic prediction of network operational events are utilized to improve planning, operational decisions, and network design in order to:
– Increase container flow by predicting container supply and demand at the container and facility level to improve dwell, velocity, and turntime.
– Improve vessel utilization by using predictions to understand container demand and falldown, and which containers will miss cutoff dates.
– Improve street turns with predictive recommendations that match import bound containers to export bookings by location, size, and type.
Also the Terminal and Ports fields are directly interested into the advantages provided by these new types of analysis.In this case the possible applications can be related to levels and container flows by type mode (mother vessel, feeder, barge, etc) enabling efficient labor assignment, equipment use, and yard optimization for improved terminal operations and differentiation for both carrier partners and their shippers in the follows way:
– Improve yard efficiency with flow predictions by mode, alliance partnerships, container type, size, weight, hazardous commodity, origin/destination
– Manage labor efficiency by measuring labor volumes in comparison to container flow over history to build predictions of new configurations of labor resources.
The Analysis studies are always in evolution, thanks to new technologies the possibilities and implications are wider in respect to the recent past, new IoT tools more involved in the different companies’ operations will provided an increase of Big data. The research of the optimum point, with the maximum level of efficiency. How these new studies will impact on the level of employment and ownerships’ revenue, just the time will provide us the correct response.
Source: On the Mos Way