Inventory Control System Based on Control Charts to Improve Supply Chain Performances

Abstract

Inventory replenishment rules have been recognized as a major cause of the bullwhip effect and inventory instability in multi-echelon supply chains. There is a trade-off between bullwhip effect and inventory stability where mitigating the bullwhip effect through order smoothing might increase inventory instability. Therefore, there is a substantial need for inventory control policies that can cope with supply chains dynamics. This paper attempts to formulate an inventory control system based on a statistical control chart approach to handle the trade-off between order variability amplification and inventory stability. The proposed replenishment system, namely IR-SPC, incorporates individual control charts to control both the inventory position and the placed orders. A simulation study has been conducted to evaluate and compare the IR-SPC with a generalized order-up-to that has order smoothing mechanism. The comparisons showed that the IR-SPC outperforms both the smoothing order-up-to policy and the Min-Max inventory policy in terms of bullwhip effect and inventory performances.

The impact of information sharing on ordering policies to improve supply chain performances

“…the practice of frequently updating the demand forecasts and subsequently adjusting the parameters of the inventory replenishment rules (ordering policies) (Dejonckheere et al, 2004;Lee & Wu, 2006;Hoberg, Bradley, & Thonemann, 2007;Costantino et al, 2015b). Specifically, ordering policies have been recognized as a major cause of the bullwhip effect (Dejonckheere et al, 2004;Costantino, Di Gravio, Shaban, & Tronci, 2014b, 2014c, 2014d, 2015a. Jakšič and Rusjan (2008) demonstrated that certain ordering policies could be inducers of the bullwhip effect, while others inherently lower demand variability.…”

“…This ordering policy (smoothing replenishment rule) is a good solution especially when production costs are highly sensitive to orders variability (Dejonckheere et al, 2004;Disney & Lambrecht, 2008). Recently, some researchers have employed control charts to develop alternative smoothing inventory replenishment systems to mitigate/avoid the bullwhip effect, showing a superior performance to the traditional Order-Up-To policy (Costantino et al, 2014b, Costantino, Di Gravio, Shaban, & Tronci, 2014d, 2015a. The smoothing in these systems is realized with avoiding the over/under-reaction to inventory position variation through a target smoothing zone constructed around the centerline of inventory position control chart, instead of relying on a single target level as traditional Order-Up-To ordering policy.…”

A Novel Hybrid Artificial Intelligence Based Methodology for the Inventory Routing Problem

“…Simulation allows the user to change parameters easily within the method. The outcomes for different alternatives are evaluated in the supply chain via simulation [26][27][28].…”

Coordinating of multi-echelon supply chains through the generalized (R, S) policy

“…11 Therefore, others have attempted to develop and investigate smoothing ordering policies that can limit the bullwhip effect through order smoothing. 4,11,23 The generalized (R, S) policy is a smoothing ordering policy that is adapted from the classical (R, S) ordering policy by adding smoothing parameters to regulate the response to demand changes and thus allowing order smoothing. 11 In this regard, the proposed coordination approach (Info-Smooth) can be tuned to allow not only information sharing but also order smoothing.…”