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BOXBOT SIGNED

A fast and powerful 3D cargo space usage optimization service for logistics industry

Total Cost €

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EC-Contrib. €

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Partnership

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 BOXBOT project word cloud

Explore the words cloud of the BOXBOT project. It provides you a very rough idea of what is the project "BOXBOT" about.

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Project "BOXBOT" data sheet

The following table provides information about the project.

Coordinator
KINE ROBOT SOLUTIONS OY 

Organization address
address: TOINEN LINJA 1
city: TURKU
postcode: 20100
website: www.kine.fi

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Finland [FI]
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.3. (PRIORITY 'Societal challenges)
2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs)
3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies)
 Code Call H2020-SMEInst-2018-2020-1
 Funding Scheme SME-1
 Starting year 2018
 Duration (year-month-day) from 2018-12-01   to  2019-03-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    KINE ROBOT SOLUTIONS OY FI (TURKU) coordinator 50˙000.00

Map

Leaflet | Map data © OpenStreetMap contributors, CC-BY-SA, Imagery © Mapbox

 Project objective

Even though more packages than ever before are today being shipped due the boom in e-commerce, no efficient technology has been developed to optimize cargo space in vehicles such as vans or ships. On average, 40% of the transportation capacity is empty space due to the well-known 3D packing problem in the transportation and logistics industry. Reducing the empty space with just 10% saves millions of euros in the logistics industry and greenhouse gas emissions in the environment. Some optimization space software exists in the market but none is really effective being usually too slow and/or handling only few basic cargo parameters. Thus, end-users opt for manual packing/loading plans often using excel which take a lot of time and underuse space capacity. At BOXBOT, we have developed a multi-objective meta-heuristic algorithm to do fast calculations in seconds using over 30 cargo parameters of mixed loads, operational rules and loading and discharging sequences. Our cloud-based solution is the first effective 3D cargo space optimization service for logistic industry which is able to handle complex packing and loading challenges in short time offering an increasing freight fill rate up to 30% more in vehicles. In 2017, we were selected as one of the top five startups in a global innovation competition organized by Mercedes-Benz Vans for the Startup adVANce program to co-develop our prototype in vans (€120,000). We address customers in the logistic industry from General Cargo Ship owners to Last Mile Delivery operators. We have built a solid ecosystem of partners and stakeholders for the rapid growth of our unique business (e.g. University of Turku, Mercedes-Benz Vans, Cargotec Ltd, Royal Wagenborg). Our mission is to be the leading logistics solutions provider and make our solutions globally available and widely used. Now we are applying to the SME Instrument Phase 1 to carry out a Feasibility Study.

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The information about "BOXBOT" are provided by the European Opendata Portal: CORDIS opendata.

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