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

2021 ◽  
Vol 51 (1) ◽  
pp. 9-25
Author(s):  
John Heiney ◽  
Ryan Lovrien ◽  
Nicholas Mason ◽  
Irfan Ovacik ◽  
Evan Rash ◽  
...  
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Product Architecture ◽  
Mixed Integer ◽  
Architecture Design ◽  
Product Portfolio ◽  
Supply Chain Planning ◽  
Design Alternatives ◽  
Physics Simulation ◽  
Advanced Analytics

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.

scholarly journals Supply chain optimization with variable demand by considering financial criteria and scenarios

2017 ◽  
Vol 26 (44) ◽  
pp. 21 ◽  
Author(s):  
John Willmer Escobar
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Net Present Value ◽  
Programming Model ◽  
Supply Chain Design ◽  
Mixed Integer ◽  
Supply Network ◽  
Distribution Centers ◽  
Supply Chain Optimization ◽  
Starting Point

This paper contemplates the supply chain design problem of a large-scale company by considering the maximization of the Net Present Value. In particular, the variability of the demand for each type of product at each customer zone has been estimated. As starting point, this paper considers an established supply chain for which the main problem is to determine the decisions regarding expansion of distribution centers. The problem is solved by using a mixed-integer linear programming model, which optimizes the different demand scenarios. The proposed methodology uses a scheme of optimization based on the generation of multiple demand scenarios of the supply network. The model is based on a real case taken from a multinational food company, which supplies to the Colombian and some international markets. The obtained results were compared with the equivalent present costs minimization scheme of the supply network, and showed the importance and efficiency of the proposed approach as an alternative for the supply chain design with stochastic parameters.

scholarly journals Framework for advanced supply chain planning: Large-scale petrochemical companies

2011 ◽  
Vol 8 (3) ◽  
pp. 452-463 ◽  
Author(s):  
Johan J. Louw ◽  
Wessel Pienaar
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supply Chains ◽  
Customer Service ◽  
Large Scale ◽  
Supply Chain Planning ◽  
Proactive Approach ◽  
Logistics Networks ◽  
Advanced Planning ◽  
Decision Making Processes

Most petrochemical companies are undergoing radical changes. The markets being served have expanded globally, customer service expectations have increased, and demand has become much more volatile and hence less predictable. The resulting product supply chains evolve/develop over time, with integrating decision-making processes and advanced planning practices becoming more prominent. A proactive approach with longer time horizons becomes the norm for excellence. Refinery expansion and highly integrated/sophisticated manufacturing technology have also contributed to increased interdependency within and between supply chains (upstream to feed sources, downstream to end consumer, and between logistics networks). These developments resulted in what is termed advance supply chain planning. Notwithstanding its unique differences, the petrochemical industry still has a lot of ground to cover before it can reach some of the advance supply chain planning benefits reported in other industries. This article presents what is believed to be an appropriate supply chain planning approach/framework for decision making in large-scale, integrated petrochemical companies.

scholarly journals Levels of advancement in supply chain planning by large-scale petrochemical companies in South Africa

2011 ◽  
Vol 8 (3) ◽  
pp. 535-547
Author(s):  
Johan J. Louw ◽  
Wessel Pienaar
Keyword(s):  
South Africa ◽  
Supply Chain ◽  
Supply Chains ◽  
South African ◽  
Petrochemical Industry ◽  
Large Scale ◽  
Supply Chain Integration ◽  
Business Strategies ◽  
Value Chains ◽  
Supply Chain Planning

The adoption of a full supply chain approach in the chemical industry is still relatively slow compared to other industries. Although the awareness has been kindled, very few petrochemical companies have advanced to a point where supply chain considerations and influences are proactively taken into account and incorporated in the formulation of corporate- and unit-specific business strategies/tactics, and formally structured and applied. Conventional supply chain integration concepts focus primarily on the internal and external integration of individual supply chains. Due to the highly integrated nature of petrochemical value chains, the related supply chains should also be integrated by taking account of enterprise/industry-wide synergies and interdependencies. Since not much research has been done to indicate the level of advancement in terms of supply chain planning in large-scale, South African-based petrochemical companies, this empirical research is the first of its kind. This research provides useful information regarding an understanding of the petrochemical industry, appropriate supply chain planning practices and the level of advancement in a number of related planning dimensions

scholarly journals Fuzzy Reliability Optimization for 2-Hub Center Problem with Cluster-Based Policy and Application in Cross-Border Supply Chain Network Design Using TS Algorithm

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Chenyi Yan ◽  
Xifu Wang ◽  
Kai Yang
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Reliability Optimization ◽  
Supply Chain Network ◽  
Center Problem ◽  
Fuzzy Reliability ◽  
Hub Location Problem ◽  
Cross Border

As information and communication technology evolves and expands, business and markets are linked to form a complex international network, thus generating plenty of cross-border trading activities in the supply chain network. Through the observations from a typical cross-border supply chain network, this paper introduces the fuzzy reliability-oriented 2-hub center problem with cluster-based policy, which is a special case of the well-studied hub location problem (HLP). This problem differs from the classical HLP in the sense that (i) the hub-and-spoke (H&S) network is grouped into two clusters in advance based on their cross-border geographic features, and (ii) a fuzzy reliability optimization approach based on the possibility measure is developed. The proposed problem is first modeled through a mixed-integer nonlinear programming (MINLP) formulation that maximizes the reliability of the entire cross-border supply chain network. Then, some linearization techniques are implemented to derive a linear model, which can be efficiently solved by exact algorithms run by CPLEX for only small instances. To counteract the difficulty for solving the proposed problem in realistic-sized instances, a tabu search (TS) algorithm with two types of move operators (called “Swap I” and “Swap II”) is further developed. Finally, a series of numerical experiments based on the Turkish network and randomly generated large-scale datasets are set up to verify the applicability of the proposed model as well as the superiority of the TS algorithm compared to the CPLEX.

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