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104

2:59 pm
March 8, 2017
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RDI Technologies’ Iris M Lets You See Subtle, Yet Harmful, Machine Motion

Screen Shot 2017-03-08 at 9.05.22 AMRDI Technologies (Knoxville, TN), says “seeing is believing” when it comes to the company’s Iris M powered by Motion Amplification video-processing product and software package. The patented technology measures subtle machinery motion (including deflection, displacement, movement, and vibration) and amplifies that motion to a level that’s visible to the naked eye (see example application video). Every pixel becomes a sensor, creating millions of data points in an instant.

According to RDI, the user simply has to point the camera at an asset, obtain the video data, and push a button to amplify the true motion of the entire field of view. By drawing a box anywhere in the image, he/she can then measure the motion with a time waveform and frequency spectrum.

Editor’s Note: A recently released Stabilization Update software module for the Iris M powered by Motion Amplification package allows users to  stabilize video that contains motion from camera shake due to environments where ground vibration is unavoidable (see video). In addition to automatically stabilizing based on the entire image, this update features an option to draw a Region of Interest (ROI) in the image that the user knows to be stationary. This helps in complicated motion environments.

For more information, CLICK HERE.

58

12:45 pm
March 8, 2017
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Smart Water Infrastructure Continues to Grow, but Real Challenges Persist

smart water markets

The US (39 projects) and the UK (21 projects) were the most active smart water markets during the last half of 2016. Source: Bluefield Research

By Grant Gerke, Contributing Writer, IIoT

A new report from Bluefield Research suggests that a massive smart infrastructure buildout is coming to the water and wastewater industry in the next eight years, with more than $20 billion to be spent in metering, data management, and analytics.

As devices, sensors and cloud solutions become cheaper over the next ten years, there will be a solid investment in this space but the research rings a little hollow to me. The U.S. industry, in particular, is aging and resources are limited but the big challenge may be in the area of system integrators. In a feature article from a couple years ago, I interviewed Roger Knutson, public works director at the biggest water and wastewater department in Minnesota. For Knutson, the real challenge was in overseeing software and plant monitoring upgrades to multiple plants with his own internal staff. System integrators weren’t in the budget.

“So, the real challenge is to maintain the different technologies during that timeframe,” says Knutson. We’re talking about the new and old versions of software running side-by-side at different plants or just at different plants.”

Even the Bluefield research report says that “a significant hurdle will be integrating legacy systems with new software platforms.” However, the challenge may be workflow processes, the less glamorous side of the asset management and IIoT narrative.

Other highlights from the research include:

• Halving non-revenue water– leaks and billing errors– and reducing energy consumption from 20% to 40%.

• The smart water sector is expected to scale to $12 billion in the US and $11 billion in Europe by 2025. Other hotspots for smart water activity include Australia, Singapore and Israel, where water stress and established utility network operators are more receptive to advanced technology adoption.

• European utilities are at the forefront of smart water in terms of operational solutions, while the US leads in terms of metering.

1601Iot_logoFor more IIoT coverage in maintenance and operations, click here! 

155

6:49 pm
February 28, 2017
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Process Operators and Tools May Bridge the Gap to Predictive Maintenance

170228pmartin

Peter Reynolds, contributing analyst for ARC Advisory Group.

Jim Wentzel, dir of Global Reliability at General Mills has been on the conference circuit recently and has been discussing “contextuality” when it comes to manufacturing data in the food industry. In his discussions, Wentzel discusses General Mills “data journey” as a company — their own plants and contract manufacturing plants outside the enterprise — and is pushing for data transparency throughout the entire enterprise eco-system. That means various types of plant and enterprise data, such as plant floor , instrument, machine vibration, supply chain and even other plants mixed together to make efficient decisions.

That means a lot of business units — and external companies per Wentzel— coming together and possible changes in workforce responsibilities. One scenario would be to have process operators provide key insights on equipment health due to a better working knowledge and lifecycle history of a particular asset.

>> View More | Silicon Valley Company Joins the Predictive Maintenance Party

Peter Reynolds, contributing analyst for ARC Advisory Group discusses this scenario with his most recent post, “Predictive Maintenance or Predictive Operations?” Reynolds describes how operations can lean on better tools, processes and how condition-based monitoring goes only so far:

Both Prognostics and Condition-based monitoring are still reactive approaches and have been used widely for decades. Still, many companies struggle with making significant improvements in predicting failures and extending the life of critical assets.

He goes on to write:

Therefore one might come to the conclusion that any predictive maintenance or asset reliability strategy might begin with an overarching operations strategy and weigh heavily on the skills of the process engineer. The process engineer (and not the maintenance and reliability engineer), has the ability to interpret the process data across the spectrum of the process and any assets.

The rub is that operations, maintenance and even IT need to view enterprise via data in one IIoT platform, such as ThingWorx, Element Analytics, or many other offerings that can provide varying analytics to different groups.

>> To read the full post, click here

1601Iot_logoFor more IIoT coverage in maintenance and operations, click here! 

160

4:19 pm
February 23, 2017
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MT Online Podcast: Cloud Computing with Saadi Kermani

 

mtop1Cloud computing/data storage is a way of life for many companies. For many others it’s an unavoidable “future” technology that carries with it some concern, particularly about security.  In this podcast, editorial director Gary L. Parr explores various facets of cloud computing, data storage, and data centers with Saadi Kermani, technology evangelist and business-development manager for the Industrial Information Management business at Schneider Electric. In the conversation they discuss whether users should be concerned about company data security, the need for basic due diligence, and the many advantages of cloud data storage.

In Saadi’s current role at Schneider electric, he enables industrial customers and partners to realize the benefits of lower operational costs, optimized assets and streamlined processes through the use of advanced analytics, KPIs, and real-time access to industrial process data delivered through a set of online managed services. Previously, he was the product manager for Wonderware SmartGlance and Wonderware Online, in addition to being a key contributor to the strategic definition and deployment of cloud hosted solutions for Wonderware. Prior to that role, he was stationed in Europe, providing strategic account management as a technical account manager for the Global Software Customer Support division.

165

7:14 pm
February 22, 2017
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MindShare Design Acquires CMMS Provider WorkStraight

Screen Shot 2017-02-22 at 12.56.44 PMMindShare Design, Inc., (Oakland, CA) has announced the acquisition of WorkStraight (Newport Beach, CA), a growing player in the computerized maintenance management software (CMMS) arena.

Screen Shot 2017-02-22 at 12.45.44 PMWorkStraight’s software solutions are used in a wide range of operations to manage, monitor, and control maintenance operations, resources, field marketing, construction, and more. Its web-based, Software-as-a-Service (SaaS) solution can be accessed on PCs, smartphones, tablets, and other browser-based devices.

According to the two companies, MindShare Design’s suite of business-acceleration tools, software, and data expertise combined with WorkStraight’s work-order management product represents a critical convergence in the marketing and ultimate delivery of solutions that ensure uptime and maximize return on assets for maintenance and operations managers.

For more information on Mindshare Design, CLICK HERE.

To learn more about WorkStraight’s solutions, CLICK HERE.

 

154

7:05 pm
February 16, 2017
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Silicon Valley Company Joins the Predictive Maintenance Party

predictive maintenance platform

Source: Element Analytics

Silicon Valley-backed Element Analytics formally announced their industrial software analytics solution, Element Platform, to the market last month. The San Francisco-based Element Analytics is taking aim at the oil and gas, chemical, utility and mining industries while partnering with OSIsoft and Microsoft’s Partner Network.

The platform and the solution is a good fit for those industries, as those fields tend to rely on proprietary automation and equipment platforms that need optimization. Oil and gas, specifically, moved their strategy from offshore to their current installed base to find profitability and most producers are understanding the need for infrastructure improvement. From the press release, the Element Platform works with OSIsoft’s technology in moving unstructured, operational sensor data from “silos” to a cloud-based analytics platform, where asset models help predict downtime for physical equipment.

Related Content | How to Start a Predictive Maintenance Program

“Industrial operators face no shortage of data, says David Mount, Kleiner Perkins’ Green Growth Fund partner and co-founder of Element Analytics. Mounds of data exist, but getting the data to a ready state is core to making it analyzable, predictive and actionable.”

Predictive maintenance technology has been slow to be adopted due to operational and production conflicts, but recent IIoT solutions live on separate platforms. This allows for control platfom updates, like security patches to occur, while not interrupting asset management programs.

The Element platform also uses Microsoft Azure and Cortana Intelligence for the cloud-based analytics.

For more information, visit www.elementanalytics.com

1601Iot_logoFor more IIoT coverage in maintenance and operations, click here! 

210

11:34 pm
February 8, 2017
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Emerson Introduces ‘Industry First’ WirelessHART Power Meter

Screen Shot 2017-02-08 at 4.31.12 PMEmerson (Mansfield, OH) has introduced what it says is “industry’s first” WirelessHART Power Meter. Part of the company’s pervasive-sensing portfolio, the device provides electrical demand- and consumption-measurement through a secure and reliable network for a range of applications, including, those found in processing, industrial, cold-chain storage facilities, and data centers, among others.

Screen Shot 2017-02-08 at 4.31.31 PMHow It Works
Incorporating WirelessHART technology in a revenue-grade wireless power meter, the new product is said to be capable of delivering a unique measurement solution that will greatly improve energy efficiency and sustainability.

WirelessHART technology, coupled with the power meter’s small physical footprint, simplifies and speeds installation of the unit and allows sites to monitor voltage, current, power, energy, and other electrical parameters on single- and three-phase electrical systems in real-time with revenue-grade accuracy. Real-time monitoring of electricity consumption and instantaneous demand enables more granular energy management and effective equipment monitoring, securely and reliably.

For more information, CLICK HERE.

 

 

237

3:56 pm
February 8, 2017
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How to Start a Predictive Maintenance Program

IIoT motorsDevice and equipment advances, on display in our MT IIoT web section, is past the early adoption stage, but operations and maintenance (O&M) teams are still wrapping their arms around predictive maintenance programs. A recent interview with ARC Advisory’s Ralph Rio via SAP’s Enterprise Asset Management discusses this very issue and more.

Excerpt below:

Q: So how do people begin moving toward predictive maintenance – how do they get there?

Ralph Rio: The first thing people need to do is to educate themselves to understand what is available from a technology standpoint. People just entering this area are no longer “early adopters” so there is plenty of information out there. Get comfortable with the platforms and the business processes.

Sometimes technology education is coming from your machine builder (OEM) with improved data acquisition capabilities. From this post, “Are Smaller IIoT Applications The Next Wave for End Users?” and discussion with Erl Campbell at Aventics, MT found out how this is working:

“By actually monitoring the spool position, the machine can track exactly how each valve performed during a motion cycle: where that valve started, whether it fully shifted or only partially shifted, and its final position. These data points help machine builders and end-user operators correct issues that may affect overall packaging quality and integrity,” the white paper states (written by Erl Campbell.

Campbell added in a recent interview that the company is working on whether the (valve) reliability data should communicate with the factory floor or maintenance. Is it going to be some kind of wireless communication or will techs plug into the manifold and download that data?

>> For more on how to create a predictive maintenance program with Ralph Rio

1601Iot_logoFor more IIoT coverage in maintenance and operations, click here! 

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