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Demand driven material requirements planning (DDMRP) (Master thesis)

Ζδρατσίδης, Αθανάσιος/ Zdratskidis, Athanasios

Demand-Driven Material Requirements Planning (DDMRP) is a newly established methodology in the field of Production & Inventory Management, which responds better than the "classic" control systems to the modern, changing trends and needs of the global market. The DDMRP inventory replenishment method generally outperforms existing replenishment models, exhibiting a lower average inventory. However, the subjective parameterization introduced by the new methodology creates large discrepancies in the calculation of the safety stock that inevitably affects the key objective of reducing the average inventory. This paper aims to extensively present the DDMRP model through a systematic review of existing scholarly publications and to strengthen the conclusions of the empirical research by Lee & Rim (2019). They propose an alternative mathematical model for calculating the safety stock that avoids subjective coefficient selection, yielding a lower inventory than DDMRP and classical replenishment models. The validation of the improved performance of the proposed model over existing replenishment models is performed by conducting comparative simulation experiments. The performance of the new mathematical model is further verified by proceeding to a similar simulation, amplifying the uncertainty in demand and lead time. Despite the clear increase in the average inventory in all models, due to the increase in volatility, the alternative Lee & Rim model leads to lower average inventory than both the original DDMRP model and the classical model in almost all cases. The classical replenishment model, unable to absorb large variations in demand and lead time, leads to much higher average inventory than the two DDMRP models confirming their better adaptation to high volatility.