1. 1 Why a simulation meta-model?  D5.4 objective: evaluating the impact of electric faults (and, in more general terms, of risky events) on supply chains performances  Selected methodology to achieve the objective: simulation  Big problem: every time we want to evaluate the impact of risky events on a particular supply chain we need to build a new simulation model (impossible… too time consuming!!!)  To solve this problem we decide to develop an object-oriented simulation meta-model

2. 2 The simulation meta-model (1/2)  It is composed of: an Excel™ interface and an Excel™ database; the interface allows for specifying the network topology and the nodes management policies by entering, for instance, the list of levels characterizing the supply chain and, for each level, the list of nodes belonging to it. All the entered data are recorded into the database an ad hoc SIMAN™ objects library; it contains the objects representing all the possible nodes a supply chain can be composed of (i.e. all the possible combinations of node typologies (retailer, distributor and manufacturer) and management macro-strategies (pull and push)). Each object is described by:  data, the parameters which the object corresponding to the node is characterized by (if the node is included in the supply chain to be modeled and simulated, the values of these parameters have been entered via Excel™ interface and, as a consequence, are recorded into the Excel™ database)  behavior, a SIMAN™ simulation sub-model which, operating on the object data, represents how the corresponding node behaves in the real word and interacts with the other supply chain nodes

3. 3 The simulation meta-model (2/2)  It is composed of: a Visual Basic™ application, which allows for building the ARENA™ simulation model of the supply chain under study. From the Excel™ database the Visual Basic™ application reads the nodes characterizing the supply chain and, for each of them:  (i) it selects the corresponding SIMAN™ object from the ad hoc library;  (ii) it selects from the Excel™ database the values to be assigned to the object data;  (iii) it makes the assignments (i.e. it generates the instance);  (iv) it inserts into the ARENA™ environment the instance, i.e. the SIMAN™ simulation sub-model representing the object behavior which after the assignments operates on the parameterized object data. Once the Visual Basic™ application has completed the above mentioned steps per each node of the supply chain under study, the ARENA™ simulation model is built and experimental campaigns can be performed on it

4. 4 Objects behaviors (1/3) RETAILER PULL RETAILER PUSH

5. 5 Objects behaviors (2/3) DISTRIBUTOR PULL DISTRIBUTOR PUSH

6. 6 Objects behaviors (3/3) MANUFACTURER PULL

7. 7 Next steps  Increase the ad hoc SIMAN™ objects library  Improve the integration between the object-oriented simulation meta-model and the electric faults model  Test the simulation meta-model on a real-life supply chain (7 factories, 10 RDW, 453 consignment points. See “Supply_Chain_test.xls”)  Integrate the object-oriented simulation meta-model and the econometric model