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This paper deals with the study of the dynamic performance of service-manufacturing hybrid supply chain with different forecasting methods. Two forecasting methods in two-echelon hybrid supply chain system are exponential smoothing forecasts (ESF) and moving average forecasts (MAF). Based on Automatic Pipeline Inventory and Order Based Production Control System (APIOBPCS), the Automatic Pipeline Control System of Production and Service in Hybrid Supply Chain (APIOBPSCS) is built using control theory. On this basis, the dynamic responses of two hybrid supply chain systems under step demand input are analyzed by simulation. As the system parameters change, two kinds of hybrid supply chains with different forecasting methods are compared in the performance , the fluctuations of product order rate, works in process (WIP), and actual inventory of product and service pile-up rate. Simulation result shows that the overall influence of hybrid supply chain should be considered according to the different forecasting methods. With selecting corresponding forecasting methods, the reasonable system parameters will be set to improve the overall operation efficiency of hybrid supply chain system. Introduction Service-manufacturing is a new manufacturing mode that manufacturing and service are integrated in [1]. The hybrid supply chain of the service-manufacturing is a blend of product supply chain and service supply chain, that is to say, service flow and material flow are existing at the same time. In hybrid supply chain , we focus on customer demand and provide the customers with a range of associated services through the lifecycle of products [2]. Hence, the hybrid supply chain is combined of customers, service providers and product suppliers. Based on BM enterprise, the two-echelon hybrid supply chain is shown in the Fig.1. Fig. 1 Two-echelon service-manufacturing hybrid supply chain model Transfer function techniques are particularly powerful methods of systems analysis in discrete time. Adelson used z-transforms of second-order exponential smoothing forecasting algorithms within an inventoryand orderbased production control system [3]. John et al. created the APIOBPCS (Automatic Pipeline Inventory and Order Based Production Control System) model that was studied using Laplace transforms and block diagrams [4]. Disney et al. conducted an analysis of APIOBPCS in discrete time using the transfer function techniques [5]. On the basis of the existing research results, we build hybrid supply chain system which is the Automatic Pipeline Inventory and Order Based Production and Service Control System (APIOBPSCS) according to the actual circumstance of BM’s supply chain. Product supplier Service provider Service-maufacturing enterprise Customers Material flow Service flow Product flow & Service flow

Dynamic Performance of Service-manufacturing Hybrid Supply Chain with Two Forecasting Methods