Shang-Tae Yee

Establishment of product offering and production leveling principles via supply chain simulation under order-to-delivery environment

In support of the order-to-delivery (OTD) business initiative, a simulation framework has been developed at GM R and D. The OTD simulation program is aimed at simulating the behavior of the OTD supply chain using detailed inputs associated with demand, supply, and production processes. Customer demand variation is a key source of uncertainty in GMs supply chain. Early capture of customer demand fluctuation enables GM to effectively reduce aggregate mismatch between production and sales and appropriate time series models have been suggested to capture demand patterns based on actual data. The vehicle model and option mix with a given demand variation influences the performance of the OTD supply chain and provides a means to establish certain principles determining the extent of product offering and the scope of production leveling. Analyzing the impact of the model and option mix on primary supply chain performance measures, such as customer wait time, condition mismatch, and parts usage, capacitates reduction of the mismatch between demand and production and stabilizes supply chain operations.

Simulation anywhere any time: Web-based simulation implementation for evaluating order-to-delivery systems and processes

GM Enterprise Systems Laboratory (GMESL) has developed a standalone single user simulation program for evaluating and predicting order-to-delivery (OTD) systems and processes. In order for more people to be able to access this simulator, to share the simulation results, and to analyze simulation collaboratively, we have designed, developed and implemented an Internet-based three-tiered client/server framework, which consists of the three tiers: database, execution and user interface. The corresponding components are: database server, execution server, and Web based user interface. The relational database server enables users to interact with the persistent data sets for simulation study and maintains data integrity. The multi-agent based execution server guarantees stable user responsiveness by virtue of the multi-agent flexible architecture, accordingly achieving a high level of processing scalability. Finally the Web-based graphical user interface helps users to easily conduct the simulation study from anywhere at any time, and the visual simulation analysis tool helps users to make decisions effectively.

Dynamic shipment planning in an automobile shipment yard using real-time radio frequency identification (RFID) information

Wireless communication technology has been increasingly adopted in various business environments of supply chains. Radio frequency identification technology provides real-time information of vehicle movements and, associated shipment operations can benefit from it for better, efficient load makeup. A Markov decision process model is proposed for dynamically building the shipment loads using real-time information of the wireless tracking system. Simulation results demonstrate the superior performance of dynamic decision approach compared to conventional shipment practices in terms of reducing vehicle dwell time, improving customer fulfillment, and increasing utilization of the transportation carriers.

Delivery Supply Chain Planning Using Radio Frequency Identification (RFID)-Enabled Dynamic Optimization

For the past few years, many companies have investigated potential of radio frequency identification (RFID) technologies by conducting pilot project. Whereas successful cases were reported for supply chains, companies experienced under-achievement of their target on return on investment (ROI) due to various reasons. First of all, RFID hardware itself would be limited in satisfying functionality and performance of user requirements. The RFID hardware has been mature because RFID vendors have made a lot of effort to develop more robust RFID tags and readers. Except for harsh manufacturing environment, RFID hardware can be satisfactorily implemented right through RF design and calibration. Second, RFID would have been applied to inappropriate applications. In order to take a competitive advantage, some companies rushed to implement the RFID by selecting improper applications. The RFID is effective in an environment where materials, work-in-process and finished products are moving dynamically. Third, no sufficient planning and analysis would have been conducted as to the use of RFID data, the impact of RFID on other business processes and the connectivity to related information systems. This can lessen business benefits of the RFID capability.

Multiagent-Based Dynamic Deployment Planning in RTLS-Enabled Automotive Shipment Yard

Real-time vehicle location information enables to facilitate more efficient decision-making in dynamic automotive shipment yard environment. This paper proposes a multiagent-based decentralized decision-making model for the vehicle deployment planning in a shipment yard. A multiagent architecture is designed to facilitate decentralized algorithms and coordinate different agents dynamically. The results of computational experiments show that the proposed deployment model outperforms a current deployment practice with respect to the deployment performance measures.