Elena Ciancimino

On the Bullwhip Avoidance Phase: supply chain collaboration and order smoothing

This paper provides an assessment of the impact of collaboration and smoothing replenishment rules on supply chain operational performance and customer service level. Three supply chain configurations (i.e. Traditional, Information Exchange and Synchronised) in which orders are generated by smoothing (S, R) inventory control policies are studied for different proportional controllers. A supply chain stress test is performed through a sudden and intense change in demand. A structured and extended supply chain assessment framework is adopted. The main conclusions of this paper are the following. (i) The impact of Supply Chain Collaboration on overall supply chain performance is greater than that of order smoothing. Order smoothing mitigates the bullwhip effect, but it may have a negative impact on customer service. Supply Chain Collaboration mitigates the bullwhip effect, provides inventory stability, limits lumpy orders and enhances customer service level. (ii) The negative effect on customer service level of order smoothing is almost eliminated in synchronised supply chains.

On the Bullwhip Avoidance Phase: The Synchronised Supply Chain

The aim of this paper is to analyse the operational response of a Synchronised Supply Chain (SSC). To do so, first a new mathematical model of a SSC is presented. An exhaustive Latin Square design of experiments is adopted in order to perform a boundary variation analysis of the main three parameters of the periodic review smoothing (S,R) order-up-to policy: i.e., lead time, demand smoothing forecasting factor, and proportional controller of the replenishment rule. The model is then evaluated under a variety of performance measures based on internal process benefits and customer benefits. The main results of the analysis are: (I) SSC responds to violent changes in demand by resolving bullwhip effect and by creating stability in inventories under different parameter settings and (II) in a SSC, long production–distribution lead times could significantly affect customer service level. Both results have important consequences for the design and operation of supply chains.

Inventory policies and information sharing in multi-echelon supply chains

The aim of this article is to show how to modify a replenishment rule in relation to the operational information shared by suppliers. More specifically, we present a model of an Automatic Pipeline Variable Inventory and Order-Based Production Control System rule for a multi-echelon supply chain characterised by different increasing levels of shared information. A numerical study is presented to underline the performance differences for three variants of the smoothing order rule in terms of bullwhip reduction, inventory stability and operational and customer responsiveness. Results show how the effectiveness of a smoothing replenishment rule depends on the level of information sharing.

Capacity constrained supply chains: a simulation study

This paper explores the relationship between constrained capacity and supply chain performance. Six capacity constraint levels are studied under different inventory policies and information sharing strategies. The results suggest that an increment of production capacity, used in industry as local approach to manage increasing incoming orders, does not necessarily imply an improvement in customer service. In presence of information distortions, the strategy of augmenting production capacity can lead to satisfy at a higher cost an over-estimated market demand. The collaborative practices provide bullwhip effect dampening and inventory stability, and increase the ability of the structure to avoid this risk.

Modelling the Bullwhip Effect Dampening Practices in a Limited Capacity Production Network

This work infers on the conjoint adoption of collaboration practices and replenishment rules as bullwhip dampening techniques in a limited capacity production network. Continuous time differential equation methodology is adopted to model three supply chain configurations. Results show that theconditio sine qua non for long-term capacity strategy is the management and control of information asynchronies, provided by collaboration practices and ad-hoc decision policies. Furthermore the study reveals the phenomenon of bullwhip rough dampening.

The APIOBPCS Deziel and Eilon parameter configuration in supply chain under progressive information sharing strategies

The aim of this paper is to investigate how different smoothing parameter levels of the Automatic Pipeline Inventory and Order Based Production Control System smoothing replenishment rule impact on the bullwhip dampening efficacy, under progressive information sharing strategies. The main results of this work are: (1) The smoothing parameter variations significantly impact on performance of the supply chains characterised by low information sharing level. (2) As smoothing parameters increase, the supply chain process performance improves and the customer service level worsens. This opposite trend noticeably decreases as information sharing level increases. (3) Amongst the bullwhip dampening techniques, deeper information sharing weights more than the value of smoothing parameters. The analysis is performed through continuous time differential equation modelling.

Supply chain modelling and analysis: an application of Latin square to a repeated coupling of non-linear differential equations

In the last 50 years, Forrester’s system dynamics techniques have been adopted to analyse problems and find solutions for global supply chains. An important topic in production-inventory system modelling is the design of experiment. The aim of this paper is to present an application of a statistical technique of design of experiment, the Latin Square Design, to set a combination of input values for the initial-value problem of non-linear repeated coupling of first-order differential equations modelling a production-inventory system. This design permits to reduce the number of experiments while allowing statistical analysis for testing the significance of the studied parameters.

Up-to-Date Supply Chain Management: The Coordinated (S, R) Order-Up-to

This paper presents the mathematical derivation of a new generation of the most largely used periodic review policy in supply chain: the coordinated (S, R) replenishment rule. We first derive the classical order-up-to model and then we modify it to generate the coordinated decision policy equations. We run a numerical simulation on a serial supply chain model to show differences in the two policies. We conclude on the managerial implications related to coordinated replenishment.

Production Inventory and Enterprise System Implementation: An Ex-ante No-Cost Based Evaluation

The objective of this paper is to present an Enterprise System (ES) ex-ante no-cost based three step evaluation technique, which enables a pre-emptive analysis of the effects of an ES implementation using a system of referenced non financial performance metrics. The innovativeness is in the use of a simulation model fully integrated with the evaluation procedure. Researchers can extend the presented technique to further modelling approaches and test it on different market sectors. The analysis provides practitioners with a measurement system that enables an analysis of the effects of a given ES implementation and can be further employed in financial evaluations.

Avoiding Demand Amplification Phenomenon via Hi-tech Application: A What-If Supply Chain Analysis

The well-known deleterious effect of the amplification of variance of order rates in multi-echelon systems, commonly known as demand amplification phenomenon or bullwhip effect, still presents new challenges and continues to fascinate the operations management community. Recently this research field is focusing on the study of robustness of bullwhip avoidance techniques under uncertainty, as environmental conditions often determine variations in processes, with regards to production and delivery lead time, and variations in the parameters of the decision policies. This work aims at quantifying the efficacy of bullwhip dampening techniques and at verifying this efficacy against variations in the business context. The original value of the research consists in showing that the bullwhip dampening efficacy, provided by hi-tech applications and practices of supply chain collaborations, persists when operational parameters vary within a certain range.