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  • Applying Manufacturing Intelligence to OEE for Real-Time Decision Support

    Best-in-class manufacturing requires complete real-time process performance monitoring and the analytical decision support for process management and improvement. The impact of such an approach is profound as indicated in two recent MESA studies (MESA 2012a, MESA 2012b).

  • Justifying the Manufacturing Intelligence Project

    In today’s competitive markets, the ante for successful manufacturing and supply-chain management keeps growing. The companies that survive and thrive do so by stepping up their ability to keep moving in front of corporate and customer requirements.

  • Control Limits vs. Specification Limits

    We often hear control limits and specification limits discussed as if they are interchangeable. But control limits and specification limits are completely different values and concepts. What is the relationship between control limits and specification limits? Usually there is no relationship whatsoever.

    Control limits are calculated from process data for a particular control chart. An X-bar chart and an Individual measurements chart will have different limits.

  • Implementing a Sustainable MI System

    When a company decides to implement manufacturing intelligence (MI), the goal is a successful long lived project that delivers manufacturing decision support and an ongoing ROI. The question becomes how to identify a dependable, systematic way to guarantee a successful MI implementation.

    Research shows companies spend $50B to $80B dollars on failed IT projects each year. One top reason in the studies is the project fails to achieve the expected business value.

  • Combine OEE and SPC for Real Decision Support

    World class manufacturing requires real-time monitoring and analytical decision support for process management and improvement. As part of this effort Key Performance Indicators (KPI) are often used to focus on the most important measures characterizing the business. Unfortunately, many companies use KPIs as isolated values without analytics and set themselves up for bad decisions.