Smart Ordering Plan as a Service

Project Information

SOPaaS

Grant agreement ID: 815903

DOI

10.3030/815903

Project closed

EC signature date 2 May 2018

Start date 1 June 2018

End date 30 September 2018

Funded under

• INDUSTRIAL LEADERSHIP - Innovation In SMEs

Total cost

€ 71 429,00

EU contribution

€ 50 000,00

Coordinated by

GENLOTS SA
Switzerland

Periodic Reporting for period 1 - SOPaaS (Smart Ordering Plan as a Service)

Reporting period: 2018-06-01 to 2018-09-30

Summary of the context and overall objectives of the project

SoPaaS, which stands for Smart-Ordering-Platform-as-a-Service, is based on state-of-the-art machine learning algorithms developed by its co-CEO Mr Schenker in his master thesis at Swiss Federal Institute of Technology (ETH Zürich). To deploy SoPaaS, it is necessary to achieve several technical and commercial objectives during the Phase 2, notably comprising the development of SoPaaS optimization to incorporate additional extensions, end user´s validation, and developing a detailed dissemination and communication plan to ensure widespread of our technology through the main stakeholders.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

With the aim of further achieving the target objectives on Phase II, during this Feasibility Study we defined the technical and commercial objectives and validated a) commercial, b) technical & c) financial viability and a present contingent work-plan, risk mitigation strategy and budget.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

SoPaaS solves the industrial question of how much to order and when. Our proprietary machine-learning algorithms unlock untapped savings of 5-10% of total purchasing cost on average, meaning several millions per year for just one manufacturing site. Furthermore, we can introduce environment-friendly considerations as additional factors on the ordering plan calculation.

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