Application of control theoretic principles to manage inventory replenishment in a supply chain

Abstract

Using uncertain real-time information to update supply chain operational policies creates a need for developing dynamic supply chain management capabilities that increase responsiveness to demand and decrease volatility of the replenishment process (popularly known as the Bullwhip Effect). To this end, we explore the use of control theoretic principles to manage the inventory replenishment process in a supply chain under different forecast situations. We study the use of proportional, proportional-integral and proportional-derivative control schemes to determine the conditions under which specific control actions are beneficial. Analytical models and simulation runs are used to study the trade-off between responsiveness to demand and volatility. Our analysis indicates that using proportional control to manage inventory replenishment is suitable for high forecast error situations. Proportional control along with integral control works well in situations where the forecast bias is relatively higher than the forecast error. Proportional control along with derivative control works best in situations with moderate forecast errors.

An analysis of the general benefits of a centralised VMI system based on the EOQ model

“…In addition to the researchers mentioned in Table 1, the following researchers have also analysed the benefits of the VMI system (Disney and Towill 2002b, Sourirajan et al 2008, Bakal and Geunes 2009, Battini et al 2009, Wang 2009, Liu and Ç etinkaya 2010, Borade et al 2011. Zhang et al (2007) developed an integrated VMI, where a joint cost model was built under the assumption of constant demand rate and production.…”

Mathematical Modeling for Infinite and Finite Dimensional Production-Inventory Systems Subject to Demand Fluctuation

“…The application of PDE and ODE are important considering the greater amounts of data and business decisions, which are facing decision-makers. There is a growing interest in using real-time information to improve, support and validate business decision-making [1]. Today's enterprises work towards flexible, reliable and responsive business operations.…”

The extension and exploitation of the inventory and order based production control system archetype from 1982 to 2015

“…Inventory policy refers to the inventory control principles, which consist of the proportional (P), Integral (I) and Derivative (D) approaches. Sourirajan et al (2008) examined the impact of P, PI and PD on the bullwhip effect under different forecasting conditions in a single-echelon supply chain. Using z-transform, they found that the P controller is good for a high forecasting error situation, the PI controller strategy works well in a scenario in which the forecasting bias is higher than the forecasting error and the PD ordering principle delivers excellent performance in the context of moderate forecasting errors.…”