## 5 Proposed Methodology
### Process Modelling Methodology  
5.3.1 Types of Input Data  
For the implementation of the model structure and the definition of its parameters, several input data are required. These data are generally of two types: static data, that refer to characteristics of the production system that do not change or are updated periodically, such as machine types, machines, resources, etc. ; and dynamic data, that refer to the scenario considered, such as jobs, products, processes, moving and setup times, maintenance activities, etc. Certain types of data have to be provided to the PSM module by the information system of the production system under study (orders, release dates, time horizon, etc.) and others from modules such as analytics (data connected with breakdowns, setup and processing times) and optimisation (that calculates the schedule or else a heuristic used for this purpose). A superset of types of parameters is necessary in order to construct a model and simulate specific production scenarios (in certain problems, parts of these data can be omitted if events as the transfer of parts are considered of negligible duration or if certain characteristics are studied). This list is specified according to our needs as determined through the interaction with the steel reinforcement installation, and includes the following:  
* Flow charts. They are used to study the connection between machines and moving equipment (resource allocation) and create connections between the entities of the system according to this. * Resources catalogue. It refers to all the resources of the production line as well as the possible use of each one for the production of final products. * Initial inventory for a case. This refers to the initial levels of internal buffers of the system as well as parts in the machines. This practically is part of the initial marking of the net (initial token distribution) and is used to define the initial state of the system together with the states of the machines. * Production orders and jobs. In many cases, a production order is composed of different jobs that need to be processed in different machines and produce parts with different characteristics. Product quantities, due dates, priorities between orders, whether they can be split in suborders, product special features and resources used for each should be known. * Machine families. Machines with similar characteristics that can be used for the performance of certain tasks. In addition, constraints regarding the performance of certain types of processes in machine sets must be included in order not to consider cases that are not applicable. * Product families. Products belonging to a family may have common characteristics as certain processes received, common setup times, machines used for the performance of specific processes, etc. * Schedule per machine. According to this, the number and type of different processes performed in each machine is listed in order to define the exact structure of its model. This is received from the optimisation algorithms and can be different for every machine or common for every production line with respect to the specific characteristics of the case considered. The proposed schedule might be different if the objective function changes. * Machine categories and constraints. The types, multiplicities of machines and the processes performed in each case are fed. In addition, possible constraints that refer to specific machines must be known especially for use during scheduling. * Process duration. The theoretical delays associated to the assignment of each type of process in each machine are listed. Machines typically are different in their speeds, have constraints in parts they can process and have breakdowns that follow different distributions. * Maintenance-related data. These activities can be considered to be of two types, the scheduled ones and the non-scheduled ones that refer to machine breakdowns.