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asset condition management

 AT&T Announces Cloud-enabled IoT Asset Management Solution for Rapid Deployment of Asset Tracking

AT&T Announces Cloud-enabled IoT Asset Management Solution for Rapid Deployment of Asset Tracking

AT&T teams with Microsoft for use of Microsoft Azure services to deliver Asset Management - Operations Center

Wrench Time Wonder

Question: What is the quickest way to improve wrench time?

Answer: Short repairs during PMs (defined as short but complete repairs on problems found during PMs that are done during the PM).

To see how this works let's list the activities of a PM from soup to nuts.

Activity
Get job assignment
Move truck (equipment) from yard (dead line) to bay
...
Travel to job with materials and tools (field and infrastructure)
Quick safety walk down
Perform work (this is the only real wrench time)
Clean up work area on truck
Unlock, un-Tag
Move truck to go line, return to operations
Return tools and excess materials
Do paperwork, work order, closing comments
 Introducing the FLIR Duo Pro R Thermal Visible Commercial Drone Camera

Introducing the FLIR Duo Pro R Thermal Visible Commercial Drone Camera

Today, FLIR unveiled its most advanced commercial drone camera and aerial mapping system, the dual sensor FLIR Duo Pro R.

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 OSIsoft Partners With Petasense to Help Industrial Customers Launch IIoT-based Predictive Maint

OSIsoft Partners With Petasense to Help Industrial Customers Launch IIoT-based Predictive Maint

Petasense, which has logged over 25 billion vibration readings, enables PI System customers to better monitor critical rotating machinery and other systems

The Evolution of Proactive and Condition Based Maintenance: Get More Out of Your Data

The Evolution of Proactive and Condition Based Maintenance: Get More Out of Your Data

The RELIABILITY Conference Learning Session - 40:54 
by Frederic Baudart, Fluke Corporation

How maintenance teams are using tiered maintenance, wireless tools and IIoT data management to get around the barriers to predictive maintenance implementation.

The combination of tiered maintenance, wireless tools/sensors and integrated technician/manager data management is allowing teams to move past long-standing barriers to predictive maintenance implementation. By reducing the level of difficulty and therefore the perceived degree of change and hardship, these techniques allow teams to implement a scaled approach to reliability, reflective of available resources and priorities. This paper evaluates how tiered maintenance is being applied and where it’s successful; examines the role that ease-of-use and automatic data capture plays regarding wireless thermal, vibration and electrical test tools and sensors; and assesses the workflows between technician and manager, with IIoT-facilitated data management and communication at the core.

Internet of Condition Monitoring Community - Special Interest Group Founders Meeting

Companies’ explosive focus on improving financial performance through leveraged (i.e., fixed) asset optimization has become even more fiery with the rapid adoption of the Industrial Internet, which enables multitudes of devices and equipment to be connected. The result of this combination is accelerating levels of asset management innovations and creativity not seen in the industrial asset space from both a products and services perspective.

 Seeq R18 Introduces Publishing Features for Visual Analytics

Seeq R18 Introduces Publishing Features for Visual Analytics

New publishing and cloud platform support for process insights expands Seeq leadership in visual analytics for IIoT and process manufacturing data.

4 Tips to Help Avoid Soft Foot in Your Machines

Soft foot can severely affect the operating condition of a machine, which will undoubtedly shorten its life expectancy. Here are a few simple tips to help avoid soft foot in your machines:

Tip ...

 August - September 2017

August - September 2017

Click to read all articles from this issue. You can also download the full PDF.

Minimize Costs Through Machine Learning

Minimize Costs Through Machine Learning

Machine learning is an approach of exploring and building algorithms that enable computers to continuously learn and adapt.

With utilities, unknown failures and the maintenance that goes into fixing them can add up at lightning speeds. A recent study conducted by GlobalData Power estimates that expenditures for wind turbine maintenance have been projected to rise from $9.25 billion to $17 billion by 2020.

 Frazier Reliability Solutions Announces New Website Launching

Frazier Reliability Solutions Announces New Website Launching

Texas-based specialists with over 20 years' experience in state of the art inspection, nondestructive testing, and equipment reliability technologies for industrial clients around the world, announces its revitalized online presence via GoFrazier.com.

Inertial Roller Alignment for the Blown Film Industry

Roller alignment is one of the most critical aspects of running a high quality product in the web processing industry. Our PARALIGN roll alignment device uses gyroscopic technology to bring this

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 GE Digital Launches Acceleration Plans to Drive Return on Industrial IoT Investment

GE Digital Launches Acceleration Plans to Drive Return on Industrial IoT Investment

Tiered offerings provide Support, Education, Adoption Services and Managed Services help drive digital transformation

 Petasense Named a Top-10 Machine Learning Startup by Google

Petasense Named a Top-10 Machine Learning Startup by Google

IIoT Startup, Petasense uses machine learning to predict equipment health

Predictive Maintenance at General Motors

Predictive Maintenance at General Motors

IMC-2016 Learning Zone - 46:16
by Gordon Andrews and Mark Bringold, General Motors

Reinvigorating Predictive Maintenance at General Motors

Topics include:

  • Predictive tools used at Vehicle, Powertrain, and Stamping Operations
    • Infra-red
    • Vibration Analysis
    • Ultrasound
    • Motor Circuit Analysis
  • Case Studies
    • GM Saginaw Metal Casting, Mark Bringol, UAW (SME)
    • Other Plants
 SKF Microlog Analyzer CMXA 51 Certified and Approved by MHSA for Use in Hazardous ‘Gassy’ Areas

SKF Microlog Analyzer CMXA 51 Certified and Approved by MHSA for Use in Hazardous ‘Gassy’ Areas

The SKF Microlog Analyzer CMXA 51 has been certified and approved by the U.S. Department of Labor’s Mine Safety and Health Administration (MSHA) for use in hazardous “gassy” areas of all coal mine operations in the United States.

 Senseye Celebrates Prognostics at Scale Milestone of Over 1,000 Machines

Senseye Celebrates Prognostics at Scale Milestone of Over 1,000 Machines

Senseye, the Uptime as a Service leader today announced that it has reached a significant prognostics-at-scale milestone of automatically monitoring over 1,000 machines at a single customer site for early signs of mechanical damage and failure; using machine learning to help the client to avoid unplanned downtime, without relying on expensive consultants.

PM and Scheduled or Condition-Based Acoustic Lubrication

PM and Scheduled or Condition-Based Acoustic Lubrication

Acoustic lubrication has taken off with afterburners lit (old aviation phrase). During the 2017 RELIABILITY Conference™ hosted by Reliabilityweb.com®, several representatives from various organizations remarked at how well their acoustic lubrication program had made such a difference. As an example, the cost savings by way of reduced man-hours using time-based lubrication and the amount of grease not purchased are two reasons.