A robust supply chain planning framework for revenue management in the semiconductor industry

High demand uncertainties, long production lead times, and short product life cycles cause high risks for supply chain planning in the semiconductor industry. These affect all industries producing goods containing semiconductors. We present a robust supply chain planning framework for revenue management that consists of stable and flexible solutions for demand steering and dynamic pricing, extending current industry practice in several aspects. We introduce the concept of availabilities and capabilities, as well as various planning processes and process enablers. Based on our framework, we also highlight directions for future research.

[1]  Richard Pibernik,et al.  Advanced available-to-promise: Classification, selected methods and requirements for operations and inventory management , 2005 .

[2]  Dave Bergeron,et al.  More than Moore , 2008, CICC.

[3]  Georgia Perakis,et al.  Dynamic pricing and inventory control: robust vs. stochastic uncertainty models—a computational study , 2010, Ann. Oper. Res..

[4]  K. Talluri,et al.  The Theory and Practice of Revenue Management , 2004 .

[5]  W. T. Huh,et al.  Optimal capacity expansion for multi-product, multi-machine manufacturing systems with stochastic demand , 2004 .

[6]  F. Massey The Kolmogorov-Smirnov Test for Goodness of Fit , 1951 .

[7]  G. Gallego,et al.  Demand learning and dynamic pricing for multi-version products , 2012 .

[8]  Behzad Razavi,et al.  A study of injection pulling and locking in oscillators , 2003, Proceedings of the IEEE 2003 Custom Integrated Circuits Conference, 2003..

[9]  S. David Wu,et al.  Coordinating Strategic Capacity Planning in the Semiconductor Industry , 2003, Oper. Res..

[10]  Robert J. Genetski,et al.  Long-Range Forecasting: From Crystal Ball to Computer , 1981 .

[11]  Chen-Fu Chien,et al.  A two-stage stochastic programming approach for new tape-out allocation decisions for demand fulfillment planning in semiconductor manufacturing , 2013 .

[12]  G. Ryzin,et al.  Optimal dynamic pricing of inventories with stochastic demand over finite horizons , 1994 .

[13]  H. C. Ott,et al.  Granularity dependency of forecast accuracy in semiconductor industry , 2013 .

[14]  Hau L. Lee,et al.  Information distortion in a supply chain: the bullwhip effect , 1997 .

[15]  Stavros T. Ponis,et al.  A hierarchical system for effective coordination of available-to-promise logic mechanisms , 2009 .

[16]  Michael O. Ball,et al.  Optimization-Based Available-To-Promise with Multi-Stage Resource Availability , 2005, Ann. Oper. Res..

[17]  Ronald J. Huefner,et al.  Identifying revenue opportunities via capacity analysis , 2013 .

[18]  G.E. Moore,et al.  Cramming More Components Onto Integrated Circuits , 1998, Proceedings of the IEEE.

[19]  Guillermo Gallego,et al.  Semiconductor inventory management with multiple grade parts and downgrading , 2006 .

[20]  Chien-Yu Chen,et al.  Quantity and Due Date Quoting Available to Promise , 2001, Inf. Syst. Frontiers.

[21]  Francesco Costantino,et al.  A real-time SPC inventory replenishment system to improve supply chain performances , 2015, Expert Syst. Appl..

[22]  Itir Z. Karaesmen,et al.  Revenue management: Models and methods , 2008, 2008 Winter Simulation Conference.

[23]  Herbert Meyr,et al.  Demand Fulfilment and ATP , 2015 .

[24]  R. Soto,et al.  Demand Management in Semiconductor Manufacturing: A Dynamic Pricing Approach Based on Fast Model Predictive Control , 2010, 2010 IEEE Electronics, Robotics and Automotive Mechanics Conference.

[25]  Michael O. Ball,et al.  A MODEL FOR BATCH ADVANCED AVAILABLE‐TO‐PROMISE , 2002 .

[26]  D. Darling,et al.  A Test of Goodness of Fit , 1954 .

[27]  Kai Huang,et al.  Multi-stage Stochastic Programming Models in Production Planning , 2005 .

[28]  Andy Wu,et al.  USING ORDER ADMISSION CONTROL TO MAXIMIZE REVENUE UNDER CAPACITY UTILIZATION REQUIREMENTS IN MTO B2B INDUSTRIES , 2010 .