Intel Realizes $25 Billion by Applying Advanced Analytics from Product Architecture Design Through Supply Chain Planning | PERPUSTAKAAN UNIVERSITAS KATOLIK PARAHYANGAN

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Intel Realizes $25 Billion by Applying Advanced Analytics from Product Architecture Design Through Supply Chain Planning

Heiney, John - Nama Orang; Rash, Evan - Nama Orang; Ching, Kalani - Nama Orang; Zhao, Zhenying - Nama Orang; Travis, Harry - Nama Orang; Sarkar, Nandini - Nama Orang; Ovacik, Irfan - Nama Orang; Lovrien, Ryan - Nama Orang; Mason, Nicholas - Nama Orang; Kempf, Karl - Nama Orang; Shirodkar, Shamin - Nama Orang;

Due to its scale, the complexity of its products and manufacturing processes, and the capital-intensive nature of the semiconductor business, efficient product architecture design integrated with supply chain planning is critical to Intel’s success. In response to an exponential increase in complexities, Intel has used advanced analytics to develop an innovative capability that spans product architecture design through supply chain planning with the dual goals of maximizing revenue and minimizing costs. Our approach integrates the generation and optimization of product design alternatives using genetic algorithms and device physics simulation with large-scale supply chain planning using problem decomposition and mixed-integer programming. This corporate-wide capability is fast and effective, enabling analysis of many more business scenarios in much less time than previous solutions, while providing superior results, including faster response time to customers. Implementation of this capability over the majority of Intel’s product portfolio has increased annual revenue by an average of $1.9 billion and reduced annual costs by $1.5 billion, for a total benefit of $25.4 billion since 2009, while also contributing to Intel’s sustainability efforts.

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Informasi Detail

Judul Seri: INFORMS JOURNAL ON APPLIED ANALYTICS; Vol.51 No.1 January-February 2021
No. Panggil: -
Penerbit: : .,
Deskripsi Fisik: p. 9 - 25
Bahasa: English
ISBN/ISSN: -
Klasifikasi: -
Tipe Isi: -
Tipe Media: -
Tipe Pembawa: -
Edisi: -
Subjek: GENETIC ALGORITHMS
MIXED-INTEGER PROGRAMMING
SEMICONDUCTOR MANUFACTURING
PROBLEM DECOMPOSITION
EDELMAN AWARD
PRODUCT DESIGN OPTIMIZATION
SUPPLY CHAIN PLANNING OPTIMIZATION
DESIGN AND PLANNING INTEGRATION
DEVICE PHYSICS SIMULATION
Info Detail Spesifik: https://doi.org/10.1287/inte.2020.1067
Pernyataan Tanggungjawab: John Heiney, Ryan Lovrien, Nicholas Mason, Irfan Ovacik, Evan Rash, Nandini Sarkar, Harry Travis, Zhenying Zhao, Kalani Ching, Shamin Shirodkar, Karl Kempf

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