A Production Service System With Customer Behavior Under Uncertainty

With the rapid development of manufacturing and the improvement of production technology,the competitiveness of enterprises is not limited to the products themselves,but also to the service level."Service-oriented manufacturing" is a new manufacturing model in which manufacturing and services are integrated,and product economy and service economy are mutually infiltrated.In the context of service-oriented manufacturing,a stochastic production service network model with customer behavior is proposed,in which manufacturing resources are treated as services and can be shared for multiple production nodes.The variety of random factors are considered in this model,including time-varying customer arrivals,customer random abandonment and retrial behavior,uncertainty arrivals of products,and machine unreliability issues.Based on the above factors,a model of a multi-product type production service system with time-varying arrival rates is established.And an aggregation algorithm is developed to reduce the complexity of the performance of the production service system.Unlike the general queuing model,the time-varying arrival of customers and the existence of initial inventory have become difficult to analyze.Then,the nonhomogeneous double-ended queue and nonhomogeneous probabilistic matching queue are used to solve the performance of the model,such as customer waiting time,idle time of products,queue length of customers,and product inventory level.The simulation is used to verify the effectiveness of the algorithm.In order to meet customers' demands with time-varying arrival rate,the delayed-infinite-server approximation and refined delayed-infinite-server modified-offered-load approximation are used to predict the real-time demand of the product.The economic analysis of this model is developed by taking into account the opportunity cost and operational cost of the enterprise.A sharing strategy named nonhomogeneous time interval transportation strategy is put forward,with an aim to diminish the total operational costs while enhancing the overall service level,which determines the dispatch time,number and frequency.In order to verify the validity of the strategy,the nonhomogeneous time interval transportation strategy is applied to three different scenarios: the peak passenger flow,the low passenger flow and the balance period.Finally,the homogeneous time interval transportation strategy and product-type independence nonhomogeneous time interval transportation strategy are compared with the nonhomogeneous time interval transportation strategy on operational cost and performance.Compared with the homogeneous time interval transportation strategy,which is difficult to determine the time and quantity of products,nonhomogeneous time interval transportation strategy provides certain decision-making solutions for enterprises with production services.In order to ensure a sufficient supply of products in the factory,a serial double-rework production system with an inspection machine is presented.The production system is analyzed via a mathematical model,and the production rate of the production line is solved by the aggregation method and the overlapping decomposition algorithm.And the bottleneck identification method is applied to find the bottleneck machine.The effectiveness of the approximation algorithm is verified by simulation.A line-changing strategy is designed to improve the congestion of the production system and reduce the deadlock ratio.The effects of rework line length,system size,buffer capacity and product quality parameters on production system are compared in the line change strategy and original strategy,and economic analysis is conducted to provide a theoretical basis for production system evaluation.