Supply chain dynamics

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2003.Includes bibliographical references (p. 121-123).The strong bargaining power of major retailers and the higher requirements for speed, service excellence and customization have significantly contributed to transform the Supply Chain Management. These increasing challenges call for an integrated and dynamic Supply Chain Management and for a better integration and alignment with key customers, in order to reduce the firm's time-to-market and build competitive advantage. The thesis aims at providing the partner company, a major player in the consumer goods industry, with a more robust and efficient vendor managed inventory practice, so that the partner can determine the optimum inventory level to satisfy turnover, service level and lead time requirements, whereas minimizing lost sales and total costs in the system. The team developed a Supply Chain Dynamics framework to help the partner to establish new service level strategies, strongly oriented to the strategic importance of its products and customers, and to map the key system-wide drivers that impact the overall number of inventory turns, service level and total costs. Additionally, in order to run simulations and estimate the outcomes of the proposed recommendations, the team developed a "Multi-Echelon" simulator and used a commercial "Supply Chain Dynamics" simulator.by Ricardo Wagner Lopes Barbosa [and] Edward Fan.M.Eng.in Logistic

A multi-echelon supply chain model for strategic inventory assessment through the deployment of kanbans

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2008.Includes bibliographical references (leaves 100-102).As global competition in the manufacturing space grows, so do corporations' needs for sophisticated and optimized management systems to enable continuous flows of information and materials across the many tiers within their supply chains. With the complexities introduced by the variability in the demand for finished goods as well as by the variability in lead-time of transportation, procurement, production and administrative activities, corporations have turned to quantitative modeling of their supply chains to address these issues. Based on the data of a heavy machinery manufacturer headquartered in the US, this research introduces a robust model for the deployment of strategic inventory buffers across a multi-echelon manufacturing system. Specifically, this study establishes a replenishment policy for inventory using a multiple bin, or Kanban, system for each part number in the assembly of products from our sponsors tractor line. We employ a numerical simulation to evaluate and optimize the various inventory deployment scenarios. Utilizing several thousand runs of the simulation, we derive a generalized treatment for each part number based on an econometric function of the parameters associated with lead-time, order frequency, inventory value and order costing. The pilot for the simulation focuses on the parts data for three earthmoving products across eight echelons, but scales to n products across m echelons. Our results show that this approach predicted the optimal quantities of Kanbans for 95% of parts to a level of accuracy +/- 3 bins.by Philip J. Hodge and Joshua D. Lemaitre.M.Eng.in Logistic

A Study of the Impact of Information Blackouts on the Bullwhip Effect of a Supply Chain Using Discrete-Event Simulations

This study adds to the supply chain management literature by introducing and investigating information blackouts, sudden and short-duration failure of the information flow. This study aims to contribute to the literature in following ways: first, to define information blackouts in a supply chain. Second, to investigate the response of supply chains to information blackouts using discrete-event simulation. Prior research has focused more on analyzing systemic disruptions to supply chains from well-known sources. We expect the results of this study to be useful to supply chain managers in disaster prone areas

An enhanced approximation mathematical model inventorying items in a multi-echelon system under a continuous review policy with probabilistic demand and lead-time

An inventory system attempts to balance between overstock and understock to reduce the total cost and achieve customer demand in a timely manner. The inventory system is like a hidden entity in a supply chain, where a large complete network synchronizes a series of interrelated processes for a manufacturer, in order to transform raw materials into final products and distribute them to customers. The optimality of inventory and allocation policies in a supply chain for a cement industry is still unknown for many types of multi-echelon inventory systems. In multi-echelon networks, complexity exists when the inventory issues appear in multiple tiers and whose performances are significantly affected by the demand and lead-time. Hence, the objective of this research is to develop an enhanced approximation mathematical model in a multi-echelon inventory system under a continuous review policy subject to probabilistic demand and lead-time. The probability distribution function of demand during lead-time is established by developing a new Simulation Model of Demand During Lead-Time (SMDDL) using simulation procedures. The model is able to forecast future demand and demand during lead-time. The obtained demand during lead-time is used to develop a Serial Multi-echelon Inventory (SMEI) model by deriving the inventory cost function to compute performance measures of the cement inventory system. Based on the performance measures, a modified distribution multi-echelon inventory (DMEI) model with the First Come First Serve (FCFS) rule (DMEI-FCFS) is derived to determine the best expected waiting time and expected number of retailers in the system based on a mean arrival rate and a mean service rate. This research established five new distribution functions for the demand during lead-time. The distribution functions improve the performance measures, which contribute in reducing the expected waiting time in the system. Overall, the approximation model provides accurate time span to overcome shortage of cement inventory, which in turn fulfil customer satisfaction

Mitigating the Bullwhip Effect and Enhancing Supply Chain Performance through Demand Information Sharing: An ARENA Simulation Study

The supply chain is a network of organizations that collaborate and leverage their resources to deliver products or services to end-customers. In today's globalized and competitive market, organizations must specialize and form partnerships to gain a competitive edge. To thrive in their respective industries, organizations need to prioritize supply chain coordination, as it is integral to their business processes.   Supply chain management focuses on the collaboration of organizations within the supply chain. However, when each echelon member optimizes their goals without considering the network's impact, it leads to suboptimal performance and inefficiencies. This phenomenon is known as the Bullwhip effect, where order variability increases as it moves upstream in the supply chain. The lack of coordination, unincorporated material and information flows, and absence of ordering rules contribute to poor supply chain dynamics. To improve supply chain performance, it is crucial to align organizational activities. Previous research has proposed solutions to mitigate the Bullwhip effect, which has been a topic of intense study for many decades. This research aims to investigate the causes and mitigations of the Bullwhip effect based on existing research. Additionally, the paper utilizes ARENA simulation to examine the impact of sharing end-customer demand information. As far as we are aware, no study has been conducted to deeply simulate the bullwhip effect using the ARENA simulation. Previous studies have investigated this phenomenon, but without delving into its intricacies. The simulation results offer potential strategies to mitigate the Bullwhip effect through demand information sharing. Keywords: Supply Chain Management, Bullwhip effect, Inventory management, ARENA simulation, Information sharing, forecasting technique, Demand variability. DOI: 10.7176/JESD/14-14-07 Publication date:August 31st 202

The impact of the supply chain structure on bullwhip effect

The aim of this paper is to study how the structural factors of supply chain networks, (i.e. the number of echelons, the number of nodes and the distribution of links) impact on its dynamics performance (i.e. bullwhip effect). To do so, we systematically model multiple structures according to a robust design of experiments and simulate such structures under two different market demand scenarios. The former emulates a stationary condition of the market, while the latter reproduce the extreme volatility and impetuous alteration of the market produced by the current economic recession. Results contribute to the scientific debate on supply chain dynamics by showing how the advocated number of echelons is not the only structural factor that exacerbates the bullwhip effect. In particular, under a sudden shock in market demand, the number of nodes and the divergence of the supply chain network affect the supply chain performance.Ministerio de Economía y Competitividad DPI2013-44461-P/DP

A rolling horizon simulation approach for managing demand with lead time variability

[EN] This paper proposes a rolling horizon (RH) approach to deal with management problems under dynamic demand in planning horizons with variable lead times using system dynamics (SD) simulation. Thus, the nature of dynamic RH solutions entails no inconveniences to contemplate planning horizons with unpredictable demands. This is mainly because information is periodically updated and replanning is done in time. Therefore, inventory and logistic costs may be lower. For the first time, an RH is applied for demand management with variable lead times along with SD simulation models, which allowed the use of lot-sizing techniques to be evaluated (Wagner-Whitin and Silver-Meal). The basic scenario is based on a real-world example from an automotive single-level SC composed of a first-tier supplier and a car assembler that contemplates uncertain demands while planning the RH and 216 subscenarios by modifying constant and variable lead times, holding costs and order costs, combined with lot-sizing techniques. Twenty-eight more replications comprising 504 new subscenarios with variable lead times are generated to represent a relative variation coefficient of the initial demand. We conclude that our RH simulation approach, along with lot-sizing techniques, can generate more sustainable planning results in total costs, fill rates and bullwhip effect terms.This work was supported by the European Commission Horizon 2020 project Diverfarming [grant number 728003].Campuzano Bolarin, F.; Mula, J.; Díaz-Madroñero Boluda, FM.; Legaz-Aparicio, Á. (2020). A rolling horizon simulation approach for managing demand with lead time variability. 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