Data Mining and Predictive Modeling for Condition-based Maintenance

  • Source: SAS Institute
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Today’s military logistics agencies must sustain diverse fleets of costly, complex, and indispensible weapon systems and platforms. Modern predictive maintenance solutions can integrate with existing IT infrastructures to collect and transmit data from various platforms to a centralized condition-based maintenance (CBM) database. Learn more about how these solutions enable better-informed decisions regarding specific maintenance actions.

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VoIP Introduction

VoIP uses internet protocol data packets to transfer voice, fax, and other data over the shared network, rather than the traditional public switched telephone network (PSTN), which is based on copper wires carrying analog voice data over the dedicated circuits. VoIP, in contrast to PSTN, uses what is called packet-switched telephony, whereby the voice information travels to its destination in individual network packets across the Internet that are assembled and then converted to voice. Learn the... Read More

Selecting ERP Software for the Mining Industry

  • Source: IFS
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Most ERP products have been designed from repetitive manufacturing, and thus lack the powerful asset management and project management functionality that mining companies require. But ERP is becoming a higher priority for these organizations. This white paper offers tips on selecting ERP software for the mining industry. Learn how you can you select ERP that can handle the entire mining project and asset lifecycle. Read More

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Safe and Reliable Asset Management in Nuclear Power Plants

  • Source: IFS
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This white paper presents an overview of IFS Applications for asset management of nuclear power plants, including corrective, preventive, and condition-based maintenance functionality for safe work management in a hazardous environment. Also included are asset lifecycle management tools to track changes to the assets that affect operational limits and conditions (OLCs). Read More

Achieving Business Intelligence in Midsize Companies

  • Source: IBM
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