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SOLUTIONS Volume 11, Issue 4 JULY-AUG 2016 THE MAGAZINE BY PRACTITIONERS FOR PRACTITIONERS INDUSTRIAL INTERNET OF THINGS
SOLUTIONSVolume 11, Issue 4 JULY-AUG 2016THE MAGAZINE BY PRACTITIONERS FOR PRACTITIONERS
INDUSTRIAL INTERNET OF THINGS
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CONTENTSJul-Aug 2016
1 Contributors, Officers & Directors
2 From the Chair Bob Kazar, CMRP, PMP, SMRP Chair
3 Four Ways the Industrial Internet of Things is Transforming Maintenance Chris LeBeau
5 The Future of Inspection Management Loganatha Pandian
9 Industrial Internet of Things and Cybersecurity Howard W Penrose, Ph.D., CMRP
13 Data Analytics: Operational Analytics Can Transform Utilities Richard Irwin
17 Understanding the Effects of IoT Erin Erickson, SMRP Executive Director
19 Your SMRP Government Relations Committee Howard W Penrose, Ph.D., CMRP
23 News
25 Updates
28 SMRP Approved Providers
29 Welcome New Members
31 New CMRPs
34 New CMRTs
36 SMRPCO Sustaining Sponsors
SMRP Solutions (ISN#1552-5082) is published bi-monthly by the Society for Maintenance and
Reliability Professionals, exclusively for SMRP members. The annual subscription rate is $15 for
members, which is included in dues. The Society was incorporated as an Illinois not-for profit
corporation in 1992 for those in the maintenance profession to share practitioner experiences
and network. The Society is dedicated to excellence in maintenance and reliability in all types
of manufacturing and services organizations, and promotes maintenance excellence worldwide.
SMRP’s Mission is to develop and promote leaders in Reliability and Physical Asset Management.
The products featured in SMRP Solutions are not endorsed by SMRP, and SMRP assumes no responsibility in connection with the purchase or use of such products. The opinions expressed in the articles contained in SMRP Solutions are not necessarily those of the editor or SMRP.
Back Issues: The current issue and back issues of SMRP Solutions can be downloaded from the library area of the SMRP Web site. Original versions of the current issue and some back issues of Solutions are available by contacting SMRP Headquarters ($5 per copy for members, $10 per copy for non-members).
SEND ADDRESS CHANGES AND INQUIRIES TO: SMRP Headquarters, 1100 Johnson Ferry Road, Suite 300, Atlanta, GA 30342, 800-950-7354, Fax: 404-252-0774, E-mail: [email protected].
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CONTRIBUTORS AND BOARDCONTRIBUTORS
SMRP OFFICERS & DIRECTORSChair Bob Kazar, CMRP, PMP The Wonderful Company [email protected] 661-432-4951
Vice Chair Larry Hoing, CMRP, CMRT Wells Enterprises [email protected] 712-540-6511
Treasurer Howard Penrose, CMRP MotorDoc, LLC [email protected] 630-310-4568
Secretary Vlad Bacalu, CMRP, CMRT AECOM [email protected] 330-888-5680
Immediate Past Chair Craig Seibold, CMRP, PE Newmont Mining Corp. [email protected] 303-837-6193
Certification Director Bruce Hawkins, CMRP Emerson Process Management [email protected]
843-670-6435
Body of Knowledge Director Paul Casto, CMRP Meridium [email protected] 540-344-9205
Education Director Christopher Mears, CMRP Jacobs Engineering/ATA [email protected] 931-454-5837
Member Services Director Gina Hutto-Kittle, CMRP The Timken Company [email protected] 330-471-7465
Outreach Director Carl Schultz, CMRP Advanced Technology Solutions, Inc. [email protected] 203-733-3333
Chris LeBeau is the global director of IT at Advanced Technology Services, Inc. With over 25 years of unique experience combining broad technical knowledge, Chris holds a thorough understanding of business and the impact of technology to organizational achievement. Chris previously held positions at Cisco Systems, AT&T, IBM and began his career in satellite communications with the U.S. Army Space Command.
Loganatha Pandian is a mechanical engineer with 12 years of experience in the field of reliability and integrity management. He holds a Master of Business Administration (Finance) and is certified in various American Petroleum Institute standards like API 580 (Risk Based Inspection), API 571 (Damage Mechanisms Affecting Fixed Equipment in the Refining and Petrochemical Industries), API 510 (Pressure Vessel Inspection Code) and API 570 (Piping Inspection Code). Loganatha is currently employed as a mechanical integrity consultant with Meridium Inc. He assists clients in setting the vision, direction and strategies for an effective mechanical integrity program.
Howard W Penrose, Ph.D., CMRP is the president of MotorDoc® LLC, vice president of MotorSight Corp, and treasurer for SMRP. He also serves as the government relations committee chair and cybersecurity liaison to Homeland Security for SMRP. Howard also serves as a contracted IEEE webmaster/social media specialist since 2007.
Richard Irwin is a senior marketing manager for Bentley System’s operational analytics software, with over 10 years’ experience in working within the analytics industry. Based in the UK, Richard holds a master’s degree in sociology from Aberdeen University and a master’s degree in IT from Heriot Watt, Edinburgh.
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FEATURE
Richard Irwin
DATA ANALYTICS OPERATIONAL ANALYTICS CAN TRANSFORM UTILITIES
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FEATURE
Data is at the heart of digital transformation. With this explosion of data, we are able to create, capture, access, monitor and analyze more and
more data every day. Problems can arise in terms of what data to use, how we can use it properly and how we can turn the data into useful information that affects our decisions across the whole organization. This is where data analytics, and in particular operational analytics, answers those problems.
WHAT IS OPERATIONAL ANALYTICSOperational analytics is an industry-recognized and emerging business process that focuses on improving day-to-day operational performance with the power of sophisticated analytics. It is a process that uses predictive techniques to combine information technology (IT), operational technology (OT) and engineering technology (ET) by transforming historical and real-time data into actionable just-in-time data for improving operational efficiencies. Data aggregation and analysis tools are used to provide clarity and context for decision making and business planning, as well as to provide a platform for organizational strategy. The software that enables this process is configurable and provides day-to-day visibility into the performance of existing assets. It also offers predictive analytical opportunities for utilities to improve their operations. This can be used in conjunction with an existing model to extrapolate relevant information as and when it is required, extending asset performance modeling capabilities for real-time operations.
OTHER FORMS OF ANALYTICSThere are many forms of analytics that perform well within their own right. Descriptive and diagnostic analytics provide insight into what happened and why it happened, but nothing about what will happen in the future. Predictive analytics takes that a step further. Traditional business intelligence provides users with conventional and dashboard reporting in near- to real-time. A solution that combines the level of reporting for management, the data mining capability and the predictive capacity offered to forecast events and opportunities is then needed. Operational analytics offers descriptive, diagnostic and predictive analytics for a complete analytical solution (see Figure 1).
Figure 1. The complete operational analytics solution
OPERATIONAL ANALYTICS AND UTILITIESOrganizations generate a large amount of data. This has been accelerated with the arrival of the Industrial Internet of Things (IIoT) and the explosion of big data, where the deployment of millions of smart meters and other grid devices is generating an ever larger amount of data. Managing, interpreting and turning this data into actionable information is where operational analytics comes to prominence, giving utilities the ability to collect, analyze and act on the information they receive. Gartner predicts that by 2021, 1 million Internet of Thing (IoT) devices will be purchased and installed every single hour1 – so the need to start harnessing the IoT starts now. Not only will data grow in volume and size, but it will also vary in type due to the large variety of data sources. This is why aligning OT with IT and ET is so important (refer to Figure 2).
Figure 2. The data convergence of operational, IT and engineering data can bring many benefits, such as improved performance, reduced costs
and risk, and greater flexibility.
HOW IT AND OT CONVERGENCE CAN HELP UTILITIES Operational analytics help utility companies drive operational efficiency by providing a broader view of their assets and how they’re performing. With assets spread over a wide geographical area, it’s important to have all of the available information in one place to give you a clear and concise picture of health, condition and performance, right down to the component level. By monitoring a variety of parameters connected to health and condition, decisions can be made earlier via analytics to help determine how likely it is that a failure or significant event will occur, enabling time for a contingency plan to be activated.
BRINGING VISIBILITY TO THE OPERATIONOperational analytics capabilities have been used to help users gain extra visibility into their assets’ performance, effectiveness and efficiency across transmission and distribution. Within substations, operational analytics have been used to monitor the condition of transformers
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FEATUREusing sensors to measure a variety of parameters, alerting engineers to any problem that may arise due to oil temperatures, dissolved gas anomalies and more. In the field, the lifecycle of transmission towers can be extended by calculating and modeling the life span using corrosion, environmental, geospatial and maintenance history data, to name a few. Additionally, line inspections can be improved by using handheld devices to upload and download inspection data live from the field. Asset health indexing empowers utilities with the proof to make defensible asset investment decisions, formulating asset life extension strategies where possible to do so safely and reliably.
The risk of failure increases due to age and condition of assets. It’s essential to know how assets are performing at all times. For example, monitoring the level of dissolved gasses and the temperature of the cooling oil that circulates within transformers identifies potential problems quickly (see Figure 4). This allows assets to be taken off line or operated on in a safe window, reducing costly failures and unplanned maintenance expenditure. This also ensures the integrity and availability of the grid. Failures within the grid also incur costly cleanups, high-level investigations and loss of reputation with customers.
Figure 4. Typical power dashboard displaying transfix gas levels and alarm status.
CASE STUDY EXAMPLEA large electricity transmission company in the UK had several hundred substation transformers situated in England and Wales, 100 of which identified as being “at risk” for failure due to their age and/or condition. The determination of the failure risk is achieved through the monitoring of the dissolved gasses in the cooling oil, which circulates within each transformer. This gas is analyzed by using Hydran units of varying age and capability, where only a small percentage of the units had logging capabilities to enable the company to remotely
gather readings for analysis. The company was therefore incapable of correctly identifying impending failures and trends to predict future problems.
Using remote devices throughout their substations to collect data from Hydran dissolved gas monitoring systems, data was transmitted by GPRS to a web server for display and analysis. By taking data from assets within over 40 substations and monitoring these levels using multiple techniques, engineers are warned of any potential failures in plenty of time in the form of SMS or email. These are sent in accordance to alarm levels that have been set for various measurable parameters within each transformer, such as Dralim Oil analysis, SF6 gas levels and DTS (the measurement of temperature along the length of a transmission line through use of optical fibers). Users have the ability to view any transformer via a treeview structure or layout by asset or route. They can also view assets on a geographic basis through the OS maps incorporated into the system.
Immediate benefits resulted in a reduction in OPEX, where the more data they received from their assets meant an increase in targeted risk management and enhanced business decision making; maintenance regimes were more informed and organized, and a
reduction in the cost of retrofitting of condition monitoring could also be implemented. With the aid of analytics to monitor and analyze the condition and performance, transformers that are diagnosed with potential failure can be proactively taken off line, which will help avoid expensive cleanup costs – with no loss to the grid. Further solutions included using the data for inspection records, as well as line surveys using handheld devices. Bringing in weather data has also been of significant benefit to help spot the relationship between current
transformers and the environment.
Another strategy used was predicting the corrosion rate of the steel tower network to determine the life of a network through the degradation of the structures. The company required a strategy that would enable them to identify problem lines and individual towers based on their location and history, and use the data to determine the best intervention programs of painting, bar or tower replacement, as well as generate the best strategies for financial expenditure. This was created through a care and risk evaluation model. The model took into account all aspects of condition that affects the degradation of steel, zinc, and organic coatings on all above ground steelwork. This includes temperature,
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FEATUREhumidity, time of wetness, pollution in the form of air-borne sulfur dioxide, location in altitude, proximity to sea, lakes, reservoirs, rivers, minor and major roads, and history, including installation date, coating records and maintenance history. The model is then used to calculate the long-term risk of the towers, and display them color
coded individually on a map within the dashboard (refer to Figure 5). This marked the first time it was possible to predict the expected condition of transmission towers across a selection of the network. This allowed preventive and replacement strategies to be planned and costed across a long-term strategy.
A. FIGURES AND TABLES
Figure 3. Typical power dashboard displaying transformer condition monitoring parameters and asset attribute details which can be used to calculate the overall Asset Health Index (AHI) score for transformer assets.
Figure 5. Example of the corrosion index showing the likelihood that towers will corrode due to emissions from nearby power station.
REFERENCE 1 Top Strategic Predictions for 2016 and Beyond: The Future Is a Digital Thing, G00291252, 2 Oct 2015
DAN ANDERSONChair, Communications Committee Life Cycle Engineering [email protected] 843-414-4866
1100 JOHNSON FERRY ROAD, SUITE 300 ATLANTA, GA 30342
www.smrp.org
SOLUTIONS EDITORIAL DEPARTMENTCAITLIN NORTONCommunications Specialist 678-298-1177 [email protected]
RANDY SPOONCommunications Specialist 678-303-3017 [email protected]
ERIN ERICKSONExecutive Director 720-881-6118 [email protected]
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