## 5 Applicability on Various Technologies
### Reconfigurable Manufacturing System for Car Manufacturing  
This study deals with the deployment of RMS in the automotive industry, namely at the PSA company [50]. This study was conducted as a PhD, co-supervised by the company itself and a laboratory. In the context of assembling various engines, where the pressure on the cost of the manufacturing system is strong, the double objectives are to satisfy customer demand while using an optimized means of production. Hence the need to define the best strategy design and reconfiguration of the manufacturing system, in order to respond to a variable demand, in the objective of incremental investment [51]. **Step II:** the lever definition was defined in a coordinated way. A questionnaire was established in order to gather as many opinions as possible in terms of the expectations of decision-makers. The main lever identified here deals with some unpredictable variability in the demand of different references of manufactured products. **Step I2:** The paradigm that was identified here was the RMS. Indeed, the culture of flow shops in the automotive industry, the volume of production, and the possibility of producing in (smaller and smaller) batches makes it possible to investigate the possibility to stop the system, reconfigure it, and run production with an interesting return on investment. More precisely, this study deals with reconfigurable assembly systems (RAS). **Step I3:** The automotive industry generally implies large factories, including several autonomous workshops. In this context, the choice was made here to focus on an assembly line for combustion engines, representing twenty stations, automatic or collaborative, making the operator and robotic resources work in the same space. Two types of engines are assembled on this line: a three-cylinder petrol engine and a four-cylinder diesel engine. Each station contains between one and thirteen assembly tasks, performed sequentially or in parallel, in a time less than or equal to the rate. The tasks are carried out by robotic arms or an operator. **Step P4:** A set of five performance indicators were identified [50] to discriminate the reconfiguration solutions: scalability, defined as the product between a factor representing the range of reconfiguration and the size of the volume increment, time and cost factors, and a parameter corresponding to the number of modules added in the system to achieve the increment; convertibility, defined as the ability of the system to switch quickly between the production of different products within the same product family or between product families; modularity, which corresponds to the property of the system to be divided between sub-units and to integrate new sub-units; integrability, which corresponds to the ability to include new components on the line using adapted interfaces; and customization, which assesses the ease of switching from one product to another through the selection of appropriate elements of the system. A weighted function enables to calculate a single score for every solution. The weights are determined during interviews with the decision-makers. **Step P5:** The configuration giving the lowest scores on each of the previous indicators was determined as the initial configuration of the line before the study. The production lines were organized in a continuous flow (flowshop layout), consisting in a succession of workstations between which products circulate on fixed conveyors. Each workstation is dedicated to a sequence of assembly tasks and a type of product. The product characteristics, tasks to be carried out, and the allocated resources are fixed before the line is started. The model is centered on the workstation, which is characterized by the resources, assembly tasks, and its location in the plant. **Step P6:** The upper bound of the solution was determined with an evaluation of the potential sequence of configurations giving the best performances with a reconfiguration time set equal to 0.