Katircioglu, Kaan (IBM TJ Watson Research Center)

Topics:

Inventory Management in Semiconductor Manufacturing
We present a spreadsheet based multi-echelon inventory model for semiconductor manufacturing. The model enables the analysis of key supply chain performance drivers such as forecast error, cycle time, yield and price changes. It takes into account issues specific to semiconductor manufacturing such as cost reductions, price take-downs, yield uncertainty, multiple grades of products and the effects of downgrading inventory. (Advanced)

High Level Supply Chain Modeling Using Spreadsheets (Tutorial)
This is a tutorial that shows how to model key metrics such as inventory, cycle time, and on time delivery trade-offs using spreadsheets. It is based on some simple techniques that are available in the inventory literature. Using these techniques, one can model multi-echelon and multi-product supply chains quickly on spreadsheets. Such models can be used for various purposes including identification of parameters that impact supply chain performance, comparison of alternative supply chain actions, conducting what-if analyses, and setting inventory policies to achieve desired cost and/or service performance.

A Time-based Approach to Modeling Inventory Problems
We will introduce a time-based approach to modeling and solving a class of inventory problems. This approach does continuous review of inventory and updates the system status continuously. It also enables us to calculate best times to place orders to service the incoming demand units. We will present new optimal policies for some problems obtained by using this approach. We will also present numerous useful measures or quantities and show how to calculate them. We will conclude with comments on the potential opportunities for using this approach. (Advanced)

A Sense and Respond System for Inventory Management in Manufacturing
We will present a framework to manage inventory via a sense and respond approach as implemented in semiconductor manufacturing. The system consists of modules that do monitoring, data processing, analytics and reporting. We will provide example use cases to explain how the system works. We will also mention the difficulties and challenges involved in creating and implementing such a system.

Background:

• B.Sc. Industrial Engineering Bogazici University
• M.Sc. Statistics Simon Fraser University
• Ph.D. Management Science / Logistics University of British Columbia

Dr. Katircioglu is a leading researcher and a consultant in the area of supply chain management, inventory optimization and e-business models at IBM T.J. Watson Research Center through his IBM internal project work, journal articles, conference presentations, and patented inventions. He has over ten years of research and consulting experience in the field of Operations Research, Management Science and Logistics. His expertise covers the areas of inventory management, distribution and manufacturing operations management and planning.

Dr. Katircioglu joined IBM as a Research Staff Member at IBM Thomas J. Watson Research Center in 1996. He began his career in IBM by working in the Manufacturing Models and Analysis Group. He was responsible for leading the development of an advanced simulation model of IBM Microelectronics Division's supply chain for memory products. From 1997 to 2000, Dr. Katircioglu represented IBM in SEMATECH Logistics Forum (SLF), an organization within SEMATECH International that conducts studies and research in semiconductor supply chain and logistics management. During his involvement with SFL, he was a part of a research team that did a detailed survey and analysis of performance drivers in the semiconductor industry. He co-authored reports and published articles. He presented some of the findings as an invited speaker at NIST Workshop in Supply Chain Management Practice and Research in April, 2001. During 1998 and 1999, Dr. Katircioglu worked on a project for IBM Personal Systems Group. He developed a proof of concept for a web enabled configure-to-order supply chain system. In 2000, Dr. Katircioglu developed a technique called Driver Impact Analyses Technique (DIAT) that has been used successfully for analyzing the order fulfillment process of IBM's Personal Systems Division. Using this technique, one can do a quick development of supply chain models using spreadsheets. Currently, Dr. Katircioglu is a part of the team that has been developing a Sense and Respond Inventory Management System for IBM microelectronics.

Dr. Katircioglu's awards include a patent award for the patent entitled "A Method for Estimating Future Replacement and Inventory Levels in Physical Distribution Networks", a Research Division Award for his contributions to Microelectronics Division Strategic Planning, and an Honorable Mention Award, at the INFORMS Student Paper Competition for his paper "A new Optimal Policy for a Unit Demand Inventory Problem", in 1997. Dr. Katircioglu has published several papers, given numerous conference presentations, and has a number of filed patent applications in the field of supply chain management and e-business. He is an active member of the Institute of Operations Research and Management Science (INFORMS), and the Institute of Electrical and Electronics Engineers (IEEE). He is also a member of the American Society of Mechanical Engineers, dedicated to recognizing individuals who have demonstrated achievements in manufacturing engineering. In 2001, he has been selected to serve as a committee member on Semiconductor Factory Automation (SFA) within IEEE Robotics and Automation Society.