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Implementing a sustainable intelligent manufacturing (MI) system

When the company decided to implement Intelligent Manufacturing (MI) system, the usual goal is to achieve a long-term return on investment, the success of the project to provide intelligent decision support manufacturing. The question is how to find a reliable, systematic approach to ensure the success of Intelligent Manufacturing (MI) system it?

 

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Recasting a High-end Foundry into a Data-driven Manufacturer

Palmer Foundry in Massachusetts designs and manufactures high-end, precision aluminum castings for numerous industries, including semiconductor, automotive, energy, aerospace, robotics and many more.  Each project requires demanding specifications and diligent control of raw materials and processes.

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NEW: Turning Oceans of Data into Real-time, Actionable Manufacturing Intelligence

Making data work for Dow

Data islands, or data silos, are common in many industries, but perhaps more so in manufacturing. The complexity of products and production lines requires multiple types of processes and equipment, each often with their own database and data storage system. While data can be extracted, it does not become information until it can be analyzed. And without an aggregated system to analyze and deliver relevant information, the value of the data is lost to the organization.

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Better Quality Across the Board

The UK’s largest manufacturer of plasterboard and dry lining systems uses NWA Quality Information System™ to implement consistent quality processes and improved productivity in plants throughout the UK.

Plasterboard is an unsung hero of the modern construction industry. By replacing wet plaster wall rendering with dry wall lining systems, builders reduce labor input and, as other work can continue as soon as the plasterboard is installed, they achieve valuable reductions in time on site.

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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.

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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.

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Start-up Time Reduction

Startup Time – The Yield and Efficiency Thief

Modern manufacturing strategy aims to make product to order. If the manufacturer is in a JIT supply chain this is even more critical.  Properly done, this approach improves productivity, reduces inventory and cuts lead time.

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