برنامه ریزی و کنترل تولید محور مشتری در فروشگاه های شغلی: رویکرد بهینه سازی شبیه سازی

Today, customer centricity becomes the key success factor for the manufacturing companies in gaining sustainable competitive advantage. In this regard, they need advanced production planning and control (PPC) techniques to be more customer focused. This study aims to integrate customer relationship management (CRM) and PPC approaches in order to use manufacturing resources of job shops more effectively in satisfying customers. To this aim, a simulated annealing based simulation optimization approach is proposed. To confirm the viability of the proposed approach, it is applied to a realistic job shop system. In order to accelerate the flow of production, product type based lot splitting is applied. In the scheduling phase, dynamic scheduling is implemented by machine-based dispatching rules. Multiple customer segments with different importance weights, and their expectations and penalties on order completion rate on due date, tardiness and earliness are considered. The aim of the proposed approach is to make near optimal policy decisions regarding the machine-based dispatching rules and number of equal sublots for the products. In this regard, four well-known dispatching rules and five modified versions of these rules which are proposed in this study are employed. Computational experiments are performed by using different dominance relationships between the customer segments, inter-arrival times and level of due date allowance factor. Results of the experiments reveal that integration of CRM and PPC approaches in job shop systems provides more effective use of resources in satisfying customers, and that the proposed approach can easily be implemented in practice.