Research

Jennifer K Ryan

Adaptive supply chains and homeland security/social networks are the two primary areas that encompass the majority of DSES research proposals. Of these two research themes, adaptive supply chains deals with the logistics of deploying finite resources to assemble, transport, sustain and distribute people, goods and information to facilitate the fulfillment of demand associated with economic commerce, national defense, disaster response, and/or humanitarian aid. The focus of our research in this area is on efficient and integrated coupling of supply with distribution network resources from a total integrated systems perspective. The functional scope of Adaptive Supply Chains spans production/procurement, materials management, storage, transport, routing, warehousing, dispatching, delivery, and service. Its contextual scope spans production, transportation, military, health, maritime, and communications systems. All of these systems are characterized by complex interdependencies where methodologies of Industrial and Information Systems Engineering can address major challenges in the ability of supply chains to adapt to evolutionary change and respond to planned and unplanned disruptive events.

This research thrust received a major boost this year when DSES Professor Jennifer K Ryan received a National Science Foundation grant to study Bayesian inventory and replacement models using real-time condition monitoring information. Condition monitoring is defined as the collection of real-time sensor information from a functioning device in order to monitor the condition of that device. Thus, this research will develop methods for incorporating sensor data and prognostic information into service parts inventory management. In many manufacturing industries, increased competition and evolving customer expectations have created an environment in which excellence in after-sales service is critical to the bottom line. The importance of after-sales service has driven many manufacturing firms to focus increased attention on the performance of their distribution networks and, in particular, on the management of their inventory of service parts. This is especially true in the earth moving equipment, machine tool, automotive, telecommunications and semi-conductor manufacturing industries. A major challenge in improving the management of service parts inventories is a lack of coordination between machinery fault diagnosis and inventory decisions. This lack of coordination can lead to increased inventory costs as well as disruptions in production activity. Thus, the on-going research will develop methods for incorporating real-time sensor information obtained through condition monitoring, which can be a critical source of prognostic information, into the inventory management and replacement decisions for service parts, with the goal of improving the management of service parts inventories. Adaptive inventory policies such as those developed in this research will help manufacturers to both increase machine availability and reduce inventory costs. When completed, this research will develop a set of implementable and broadly applicable tools that will be of practical value to manufacturing firms, assisting them in taking advantage of condition monitoring technology to improve their after-sales service and to compete more effectively.