EFECTO LATIGO EN LA CADENA DE SUMINISTRO PDF

Este trabajo ilustra no sólo una innovadora forma de estudiar el efecto látigo, o una forma distinta de modelar las cadenas de suministro usando los principios. Se debe a un desajuste en la cadena de suministro entre las Relación entre precio-demanda pueden incrementar o mitigar el efecto látigo. Efecto Latigo Solución CPFR Planeación agregada. Es la sincronización de la estrategia de la cadena de suministro y de competitiva. Causas.

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With models like the one presented here it is possible to studied and compare different companies and different sectors by using experimental input signals, and supply chain performance measures taken from either operations management ort from control theory. In the context of the supply chain dynamics problem, Forresterand Sterman, have explored the impact of time delays. In table 3 we can see the stock movement in the RDCs. This seasonal policy behaves relatively well for the historic demand of the yearbut due to its rigidity, the same performance for the following years is not expected.

The bullwhip effect is attributed mainly to two causes: We have selected for model validation and calibration parameterization the historic demand for the year Therefore, nothing is in process at the end of every week. As can be seen, in the model we have defined four stock positions in the model: Unfortunately, the space here is short to describe those methods in detail but useful references may be found in Villegas When a simulation is ran using historic demand from the yearwe can observe some dynamics resulting from the decision making structure used by the managers and in addition of uncertain demand.

Coverage policies are different for raw materials and finished goods mainly because there is a delay of more than one week from purchase to delivery of materials. In the second part of the paper we use two scenarios to analyse various changes in policies. In the hypothetical infinite order delay pipeline delay nothing happens to the output until the delay time has elapsed. The continuous line represents sales: But during that same week, the purchase manager receives more than 80, units due to a purchase order launched during the middle of the summer.

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They have more thansales points. For instance, the SD model can be extended to study scenarios where more information flows are available, where some conflict of interest affecting the policies between internal and external managers are considered, such as performance measurements. The bullwhip effect can drive wrong decisions when the production or transport capacity is defined.

Therefore, we will consider only the behaviour of the system after the 10 th week. A possible problem to define such a seasonal policy is the uncertainty.

Notice that inventories are approximately half of demand. Extensions of the flagship Pepsi trademark helped to drive growth in a variety of local markets. Much of that innovation focused on carbonated soft drinks Figure 2.

Tatiana Lara

This is a latjgo study about the modelling of a supply chain decision structure of a Mexican bottling company. We shall say that the maximum demand is for efdcto, units, that is, 20, units less than the previous policy, with the advantage of stability for the supplier.

In particular, the volume growth in Russia, China, Brazil and Thailand contributed to advances in market share. As we have said, the purchase policy rule for raw materials implies dramatic amounts of amplification, phase lag and oscillation in the purchase orders.

We have to take into account maintenance, and order in advance when needed. Operations Management, Manchester Busines School.

In Mexico most of the producers are state owned. Every week we check our inventories and pay their invoices. We find that by modelling the information and decision structure of supply chains, it is possible to identify managerial policies and information flows that distort and amplify market demand signals.

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Efecto Latigo by Daniel E Diaz R on Prezi

System Dynamics Review17, 2, pp. We produced that forecast for 4 or 5 months directly, creating the forecast from our sales estimations based on the “last month sales” and we multiplied it by a factor month by month The objective of supply chain dynamics problems is to minimize operational costs derived from those distortions and amplifications by improving managers order policies.

My main problems with Logistics are that they never give me the production programme! Modelling considerations In our case study we work with the main bottler of PepsiCo Beverages International in Mexico: The model is described in mathematical form as follows. The model lays emphasis on the modelling of policies of the supply chain managers that may be based on their own experience or knowledge.

The model shows the main aggregated behaviour of inventories, differences between plan and execution and the resulting service level. If we use sales instead of demand in forecasting we can constrain the market to sell only what we think that we will sell, instead of what the customer wants.

Changes in purchase orders As we have said, the purchase policy rule for raw materials implies dramatic amounts of amplification, phase lag and oscillation in the purchase orders. Because of this new forecast system he decides to reduce the coverage from 1 week to 0. In figure 9 we can also see the existence of a one week delay between the purchase order and supply.

The model can also be used to analyze the congruency of decision makers with fadena the information systems.