AGV planning optimization for material supply at production lines

Abstract: In recent years, customers' life stylish and behaviour have been changed and their tendencies become more diverse than before. As well as, market researches show a growing trend of special demands in their inclination. Accordingly, the companies compete to meet market demands for the reason of satisfying and maintaining the loyalty of their customers. This has led researchers to seek flexible methods and optimum solutions in production processes. In this regard, the manufacturing flow is one of the places in which flexibility and optimization can cause improvement is the assembly line. So, to meet the increasing diversity of market demand, assembly line processes must have the flexibility and ability to dynamically change product specifications and features while minimizing the operating and production processes' costs. For this reason, companies use solutions for designing assembly lines based on designing a flexible manufacturing system (FMS) for fast and better managing material feeding and handling. The FMS is a manufacturing method that is developed to easily can compatible with changes in production in the type and quantity of the product that has been manufactured. The performance of an FMS depends on the precise and efficient scheduling of material handling equipment. In this regard, the use of automated guided vehicles (AGV) instead of conveyors in an assembly line provid effectiveness and transformative.The aim of this research is to obtain the optimal numbers of AGVs required for the purpose of material handling at assembly lines. To solve the problem, a mathematical model has been developed. The objective function of the model is the number of AGVs. Accordingly, a set of variables and constraints have been determined have been considered to solve the linear optimization equation. In addition, the influence of workstations’ buffer capacity on material handling activities and the number of AGVs are studied by using this developed mathematical model.In order to evaluate experiments and analysis of the problem, Python programming software and its libraries have been used to calculate rapidly and accurately equations of the model. Preliminary results show that according to the layout of the production line and demand/production planning, as well as determining the size of input and output buffers of workstations, the proposed mathematical model calculates the minimum number of required vehicles and by changing the size of buffers we achieve different results. The aforementioned IT artefact is implemented in the direction of industrial digitalization and can be developed as application software in the eventuality. And further, this master project is desirable to take performance to continue sustainable development principles.