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Workforce scheduling for short lead time environment under uncertain demand

Walschot, Edith (2022) Workforce scheduling for short lead time environment under uncertain demand.

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Abstract:Ceva Heerlen provides the logistic process for their clients within a very short lead time, meaning that the operational workforce schedule needs to be determined without knowing the full demand. An accurate scheduling tool is important as a misjudgement leads to either backlogs or high labour costs. The objective of this research is to gain insight into how a more accurate workforce scheduling tool can be beneficial by including short-term demand forecasting and the estimation of standard times. Forecasting models such as ETS, ARIMA, Naïve, combination, top-down approach and linear regression are assessed based on a validation set, to determine which model predicts the next day's demand the most accurately. The forecasted demand and the standard times are used as input for the workforce schedule model. The workforce schedule translates the expected demand and estimated standard times in required number of operators per task.
Item Type:Essay (Master)
Ceva Logistics, Heerlen, The Netherlands
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:85 business administration, organizational science
Programme:Industrial Engineering and Management MSc (60029)
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