Page 55 - Book of Abstracts 2023

Streamlining and improving the the work process at at the the civil flame detector production department at at Spectronix factory IEM-4-5
By: Marta Cohen martacohe@gmail com com Tal Itach Itach Itachtal@gmail com Advisor: Mrs Natalia Gershon
Shamoon College of Engineering Beer-Sheva
In this project we investigated the the the current situation in in the the the civil flame detector production department at at at the the the the the Spectronix factory and and and identified the the the the the deficiencies We defined the the the the the workload and and and efficiency of the the the the workers and and and the the the the time allocated for for product manufacturing through work work work sampling Based on
the the EOQ model and with forecasts we proposed an an an appropriate inventory policy according to to to the the predicted demand In addition we also performed quality control to to to reduce the defect rate Keywords: EOQ model forecasting inventory management quality control work sampling Advanced inventory substantiation model IEM-4-6
By: Hila Havusha hilahavusha94@gmail com com Yarin Sabag yarinsabag59@gmail com com Advisor: Dr Elroi Hadad
Shamoon College of Engineering Beer-Sheva
Dead Sea factories
This project focused on
on
the the logistics and warehousing systems in in in in in in in in the the the Dead Sea factories
in in in in in in in in which we found inconsistencies in in in in in in in in in in in inventory inventory requirements for for the the main items and missing inventory inventory information which resulted in in in in in in in in in significant delays in in in in in in in in in delivering goods We employed the the PROPHET model to to forecast time series consumption behavior in in in the the Dead Sea factories
to to to to to to establish an an automatic mechanism for for checking inventory inventory levels compared compared to to to to to to to to required inventories we back- tested the model on
historical inventory inventory inventory data and compared compared its accuracy to to to to to historic historic inventory inventory requirements Results showed that the model is is accurate in in in in in predicting monthly required inventory and hence reflects relevant information for for the factory Keywords: forecasting inventory management PROPHET time series Book of Abstracts | 2023
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