November 1, 2023
November 1, 2023

Smart OTEA

Optimizing an automotive wholesaler stock management
Modelling, Simulating and Optimizing the stock of a spare parts wholesaler.

EcoMT Ecomanagement Technology

Energy and Environment

Implement improvements in the OTEA platform, developing an algorithm which predicts incidence risk in the air-conditioning system, taking the machine’s operating mode into account (cooling or heating)

Representation of the forecast of incidents on a map to create a heat map for air conditioning systems.

Proposed model.

Use of the generalized additive models, GAM, to predict response variables from observations:

  • As covariables, for modelling the cooling regime, the maximum daily ambient temperature of the previous day, the average daily climate consumption before opening and the member of the last days with incidents are included.
  • The model for the heating regime includes the number of the last five days with incidents, the average daily temperature and the daily average climate consumption before the opening.

The knowledge foundation that has been created is exploited to represent on the map the geographical distribution of the incidents according to size.

It shows, with a high degree of reliability, which commercial premises could pose problems throughout the day. Through the forecasting of potential incidents, which can be obtained before opening hours, and taking into account the number of machines each shop is equipped with, a list of the stores that are most at serious risk are provided.

Stichting European Service Network of Mathematics For Industry and Innovation.

5052 Goirle, Netherlands