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IBP Scenario Modeling for Recovery, Restructuring and Resilience

AIMMS

Our second webinar delved deeper into the technology aspect, focusing on analytical capabilities and scenario modeling. Specifically, we looked at three use cases for scenario modeling using our cloud-based IBP app. The post IBP Scenario Modeling for Recovery, Restructuring and Resilience appeared first on AIMMS SC Blog.

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Scenario Modeling Is Now Crucial for Supply Chain Network Design

AIMMS

How are companies leveraging scenario modeling for network design and optimization ? The good news is many of the survey’s respondents recognize the potential of more advanced optimization solutions. In the context of disruptions like COVID-19, scenario modeling can make considerable difference – Tweet this.

Modeling 361
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Philip Morris Drives Manufacturing Insights Using A Digital Twin

Supply Chain Shaman

In our pandemic research, we interviewed thirty manufacturers. To gain insights, we interviewed Alexandros Skandalakis, Director of Manufacturing Capacity, reporting to operations/manufacturing globally within Philip Morris. We wanted to find a better way to design our network and optimize future manufacturing outcomes.

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Definitions Matter

Supply Chain Shaman

Translation of the demand forecast into planned orders to minimize manufacturing constraints. Use of optimization to consume planned orders into manufacturing scheduling and distribution requirements planning (including inventory optimization of safety stock). The focus is on functional optimization.

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Supply Chain Network Design: The Ultimate Use Cases eBook

Explore the most common use cases for network design and optimization software. Scenario analysis and optimization defined. Modeling your base case. Optimizing your supply chain based on costs and service levels. Optimizing your supply chain based on costs and service levels. Modeling carbon costs.

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Build Political Capital to Drive Supply Chain Planning Success

Supply Chain Shaman

How should a global manufacturer make a decision? In short, the research tells me that the manufacturing industries are stuck. In contrast, for a global manufacturer, the answer is more complex. What is the role of make, source, and deliver? And how can supply chain planning help? What defines a feasible plan?

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Using data and AI to improve manufacturing

SYSPRO Smarter ERP

Using artificial intelligence (AI) in manufacturing can significantly improve productivity, reduce equipment failure, increase production efficiency and help identify new business opportunities. The area of AI that manufacturers need to explore to drive their factories into the future is machine learning (ML). The Industry 4.0