slope final conference - intelligent truck

This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demostration under grant agreement no 604129

www.slopeproject.eu

Intelligent Truck and Logistic Planning

José Ángel Rodríguez ÁlvaroMª Dolores Herrero Tomás

ITENE

SLOPE Final Conference10th November, EIMA 2016, Bologna – Notturno Hall


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Summary

• ITENE• Intelligent truck• iTruck system: Track trucks and loaded logs and send the information into the

SLOPE system• iTruck hardware and software specifications• Testing in a real scenario

• Logistic planning


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About us

• ITENE is a research center specialized in Packaging, Transport and Logistics.

• Mission: Improve business competitiveness through R&D&I projects, Innovative Technological Services to the industrial sector and Dissemination.• Location: Valencia (Spain)• Website: http://www.itene.com/

http://www.itene.com/


Intelligent Truck

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WP3Integration of

novel intelligent harvesting systems

operating in mountain areas. iTruck App

D 3.5Task 3.2 - Processor head selection, purchase and re-engineering of the SLOPE system component

Task 3.6 - Data management backup

Task 3.5 – Intelligent transport truck

Task 3.4 - intelligent processor head

Task 3.3 - Intelligent Cable crane

Task 3.1 - Intelligent tree marking and tree felling/hauling

Task 3.7 – Scientific coordination.


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iTruck


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iTruck state

NO TRUCK SELECTED

TRUCK LOADING ROUTE STARTED ROUTE FINISHED

1 We read the RFID tag of the truck2 We read RFID tags of the logs, and we close the cycle reading another time the RFID truck

3 We send GPS locations on route, we close the route reading a 3rd time the truck RFID tag


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Hardware

Raspberry Pi 2Model B

HUB USB

Edimaxew7811Un

GlobalSat BU-353-$4USB GPSB

BelkinF8T013-1

Huawei E3256 USB GPRS

CAEN R1240I RFID Portable


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General Architecture

USB

USB

USB

USB

GPRS

SLOPE server

GPS

WIFI

Bluetooth

Local database

Portable RFID reader

Raspberry PI

IP. 192.168.42.1

PC control

Fixed RFID reader

Bluetooth


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Hardware

• Raspberry Pi 2 Model B• 900MHz Quad core ARM V7 processor• 1GB of RAM

• GlobalSat BU-353-S4 USB GPS - GPS data acquisition• Huawei E3256 USB GPRS – GPRS connection• Belkin F8T013-1 – Bluetooth USB adapter• Edimax EW-7811Un – Wireless USB adapter• CAEN R1240I – qID – portable RFID reader


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Software

• Raspbian Linux distribution as an operative system. Raspbian is a free operating system based on Debian and optimized for the rpi hardware. • PostgreSQL as a database software. PostgreSQL is

cross platform, open source and free to use.• Python 3 as programming language. Python is a

general-purpose, object-oriented, high-level programming language defined for code readability. Python is free and open source.


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Main Screen

Status of the Rpi systems

Start/stop Close the app

Go to configuration screen

Go to test screen

Log screen


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Test Screen

Test screen to try the different parts of the system and check functionalities.


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Configuration Screen

Configuration screen to set different options of the solution.


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Manual RFID Reader Screen

Manual RFID Screen to control and monitor the activity of the portable RFID reader.


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Versions improvements

• Version 1: Initial integration of all the technologies with our system. • Version 2: Interface optimization and migration to Raspberry pi 2

Model B.• Version 3: Manual RFID reader implementation.• Version 4: Optimization of truck iteration and code documentation.• Version 5: Optimized app logic. App now only stores in SLOPE

database data that is useful to trace.


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Testing

Monte Sover, July 2016


Testing

Annaberg, October 2016

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Logistic planning

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WP 2 Forest information

collection and analysis

Logistic optimization model

D 2.5Task 2.2 - UAV data acquisition and processing

Task 2.6 – Scientific coordination

Task 2.5 – Road and Logistic planning

Task 2.4 - 3D Modelling for harvesting planning

Task 2.3 - On-field digital survey systems

Task 2.1 - Remote sensing and multispectral analysis



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OBJECTIVE:To determine an optimal forest logistic network to respond future demands.

The approach would determine:• Allocation of each buffer to the customer considering

lowest supply costs• Which storage yards to open and how much timber will

flow via these yards during damage events, i.e. when too much timber is produced within a certain period

I



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I• DATA VARIABLES:

• Transport costs.• Volume of wood.• Cost of manipulating.• Demand.• Cost for opening an

storage yard.• Minimum turnover in S.• Maximum capacity in S.

• CONSTRAINTS:• Demand satisfaction.

• Keeping resource limits.

• Flow balancing in storage yards.

• Safety stock.

• Capacity restriction in storage yard.

• OBJECTIVE FUNCTION:• To supply timber at the lowest

supply costs (harvesting, transportation and fixed and variable costs at storage yards):

• DECISION VARIABLES:• Volume to be transported.• Opening a storage yard.


Results

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I• REAL DATA SCENARIO:• Storage yard “S3”

will be opened.• All other timber

transports are carried out directly to the customers.

• Objective value (total supply costs): 72,769 €

• Supplied timber: 25.80 € per m³

• SIMULATED SCENARIOS:• Influence of different customers. Different demand were

tested: 3 scenarios concentrating demand on each customer.• C2 demand implies less costs (more profitable). It could

derive in different prices policies decisions depending on customer.

• Customers’ demand distribution not influence storage area to open (S3).

• If S3 forced to close.• Costs using alternative storage areas not almost affected.

Appropriate contingency plan using S2.• Effect of cost reduction in parts of the process. I.e. reducing

harvesting costs in 30%.• Total cost reduction: 17%. It could help to take decisions on

investments on harvesting technologies.

TESTS


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Contact info

• Juan de Dios Díaz ([email protected])• Emilio Gonzalez ([email protected])• Mª Dolores Herrero ([email protected])• José Ángel Rodríguez ([email protected])

Thanks for your attention!

mailto:[email protected]




slope final conference - intelligent truck

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