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Machine Learning, Manufacturing, Production, And The OODA Loop
U.S. Air Force pilot and researcher John Boyd once proposed a model known as the OODA loop: Observe, Orient, Decide, Act. Boyd suggested that two pilots locked in a battle would constantly need to...
View ArticleHow To Improve Manufacturing Productivity With Predictive Analytics
When you’re in manufacturing, time is money. Factors that cause your production process to go offline cost profitability. But how do you optimize uptime without risking machine breakdowns or...
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Demand Considerations: Bullwhip Effect
Part 1 of the five-part series “Designing Resilient Distribution Networks“ Conventional supply chains can generally be categorized as forecast-driven (push) or demand-driven (pull). Organizations...
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Striking A Balance Between Decision-Making And Execution Capabilities
Part 2 of the five-part series “Designing Resilient Distribution Networks“ In the first article in this series, we explored forecast-driven (push) and demand-driven (pull) supply chains and the...
View ArticleBest Practices For Resilient Distribution Networks
Part 3 of the five-part series “Designing Resilient Distribution Networks“ The two key criteria that determine your supply chain’s effectiveness are time and inventory. Time determines the ability of...
View ArticleStriking A Balance Between Compliance And Agility
Part 4 of the five-part series, “Designing Resilient Distribution Networks“ Once strategies are defined and best practices are selected, it’s key that packaged ERP (enterprise resource planning), SCM...
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