Simulation for Multi Echelon Inventory System

1. Background:
A supply chain system is a network that mediates the flow of entities involved in a product life cycle from production to vending. Such a network consists of nodes and arcs. Nodes represent suppliers, manufacturers, distributors and vendors (e.g. retail stores) as well as their inventory facilities for storing products and transportation facilities for shipping them among nodes. Arcs represent routes connecting the nodes along which goods are transported in a variety of modes. Supply chain inventory management (SCIM) is an integrated approach to the planning and control of inventory throughout the whole network of cooperating organizations from source of supply to the end user. It is mainly focused on the customer demand and aims at improving customer service, increasing product variety and lowering costs. Basically, controlling inventory in a huge network is very crucial and difficult. The management policies such as Multi-echelon or Multi-level or Multi-class means an item moves through more than one step before reaching to the end user. Cost optimization is very important for the supply chain and they successfully achieved good results as compared to traditional model.

The key supply chain echelons are as follows:
The supply echelon feeds raw material or parts to the manufacturing operations.
The production echelon converts raw material and parts to finished product.
The distribution echelon consists of a distribution network (warehouses, distribution centers, and transportation facilities) that move finished products to vendors.
The vendor(retailer) echelon sells products to end-customers

2. Overall objective:

We are developing a model based on the multi-echelon inventory system focusing on improving the rate of lost sales.
It is downstream supply chain model and we have assumed demand and lead times to calculate sales and lost sales at each retailer. The purpose of simulating this model is to suggest the flexible amount of inventory, safety stock, reorder point etc.
We emphasize on retailers who have direct customer relationship, and interrelationship among different retailers is considered with an aim to reduce the lost sales.

3. Methodology:

Initially we are planning to simulate three different models in Arena as follows (Table 1):

S No
Type of Model
Interrelationship details
1
A model that has three retailers without interrelationship

No interrelationship
2
A model that has three retailers with limited interrelationship
The retailers will not share their own inventory to satisfy a customer order.

3
A model that has three retailers with full interrelationship
The retailers can share their own inventory to satisfy a customer order.
Table1: Different models with their interrelationship details

The results are obtained on the basis of number of customer, customer demand, and inventory level of each retailer and also reorder point. We also compared the sales and lost sales of three models. As in the supply chain, inventory management through the stages or echelon is important and to decide the sales at the retailer’s end is very crucial as the demand changes according to the seasonal trend. Customer demand is predicted by several methods such as forecasting, or by asking supply chain experts. The lead time is also predicted by the same methods. The supply chain of the system is shown as follows in Figure 1.

Figure 1: