by Gary Mintchell | Jul 10, 2015 | Data Management, News, Operations Management, Software
Here is some news from GE emphasizing one aspect of the Industrial Internet of Things—or the “Industrial Internet” as GE promotes it. This aspect lies in what you do with all the data supplied by those connected devices.
I wish I could figure GE out. It used to be so simple with GE Fanuc (now GE Intelligent Platforms) run like a division almost like a company and GE Sensing supplying sensors for the process industries. Now, there’s GE Software, GE Intelligent Platforms Software, GE Oil & Gas, and a myriad of other entities within the corporate structure. Titles are also increasingly difficult to fathom.
The interesting uptakes on this use of GE software by BP lies in the rejection by BP management of home-grown software and a move to “off-the-shelf” software. I had heard rumblings of BP perhaps moving to standards-based interoperability. It appears that it has settled on single point solution—at least for now.
Home-grown software inevitably leads to bringing in a plethora of integrators and programmers to make the software actually work. Evidently the hope is that by implementing commercial-off-the-shelf software, it can eliminate a huge cost. I’d really be interested to know say about a year down the road how well that paid off.
GE and BP Optimization Project
GE Intelligent Platforms Software announced a new production optimization project to connect all of BP’s oil wells globally to the Industrial Internet. Using GE’s data management software, BP field engineers will gain real-time access to common machine and operational data sets across all wells, arming them with information to make better decisions to improve efficiency, prevent failures and minimize costly downtime. The project will initially be deployed across 650 of BP’s wells, expanding to 4,000 wells across the world over the next several years.
“Based on industry averages, for each week a well is out of commission, operators experience revenue losses of more than $3 million for a subsea well. In today’s low price oil environment, it is increasingly important for customers to embrace Industrial Internet technologies to increase uptime and maximize production. GE understands that our customers want to get the most out of their existing assets, and more productivity leads to more profitability. To help them achieve that, our strategy is simple: Get Connected. Get Insights. Get Optimized,” said Kate Johnson, GE Intelligent Platforms Software CEO and GE Chief Commercial Officer. “By connecting BP’s oil wells around the world, we’re giving them access to better insights that can ultimately drive new efficiencies in their oil fields and increase oil production.”
“This project highlights BP’s commitment to deploying technology that can not only improve efficiency and reduce the complexity of our operations, but that also continuously make them safer and more reliable,” said Peter Griffiths, BP System Optimization Strategist. “In this case, we are delivering a solution on a standard platform that supports BP’s move away from bespoke solutions to-off-the-shelf industry solutions that integrate with our work processes, but without the long-term support costs that a bespoke approach often entails.”
BP’s decision to license this software was driven by its potential to drive efficiency and performance through increased standardization, improved oversight and decision-making. These solutions will allow BP to capture, store, contextualize and visualize data in real time, making it available to the right people at the right time so they can make informed decisions. GE will work closely with BP through the initial phase of this agreement, placing engineers onsite to work through the global implementation.
In the last year, GE has significantly increased its portfolio of Industrial Internet tools for the oil and gas sector to help increase production in a low oil price environment. “Enabling efficiency is the top priority for our customers in the current low oil price environment”, said Lorenzo Simonelli, President & CEO of GE Oil and Gas. “We are pleased to see that customers like BP have welcomed our Industrial Internet solutions as a unique way to tackle this in order to increase production, manage costs and reduce downtime. The combination of tangible infrastructure knowledge and Industrial Internet expertise places us in a unique position to continue to grow this offering in a way which truly delivers for our customers.”
GE has been working closely with BP since 2008, driving data analysis and instrumentation to improve operational reliability at sites including Prudhoe Bay, Alaska, the UK, Norwegian sectors of the North Sea, the Gulf of Mexico, the Caspian Sea and Angola.
by Gary Mintchell | Feb 13, 2015 | Asset Performance Management, Automation, News, Operations Management
Asset performance management joined the Industrial Internet of Things as a key topic at the 2015 ARC Forum in Orlando. Here is a release from Meridium that reflects many of the trends—data collection, analysis, configurable display, mobility.
Meridium Inc., global supplier of asset performance management (APM) software and services, announced the availability of Asset Answers V2.0. The company claims this as the only cloud-based asset performance diagnostics solution that provides comparative analytics, delivering instant visibility into asset data, and supplying organizations with the insights to drive safer, more informed, and more profitable decisions.
Asset Answers 2.0 delivers next-generation APM insights into industrial assets and their health and overall performance, an improved user interface that includes dashboards and enhanced mobility on a variety of handheld devices that provides true anywhere/anytime availability. Since the introduction of Asset Answers to the market, more than 130 sites in the Petrochemicals, Oil & Gas, Power & Utilities, and Manufacturing industries rely on Asset Answers to support continuous improvement initiatives with the ultimate goal of achieving operational excellence.
For example, Dow Chemical was able to collect and analyze reliability audit report data for 25 production units across 4 plants in less than 1 day, saving 175 man-days of effort and remain focused on cost, availability, and reliability optimization for the company. Another Asset Answers client, Profertil, reduced costs for 30 straight months and was able to readily identify and highlight savings of $900,000 and counting.
According to Roy Whitt, Senior Vice President and General Manager for Asset Answers, “For organizations in asset-intensive industries, Asset Answers 2.0 uncovers the true cost, reliability and availability of asset groups and individual pieces of equipment with the click of a mouse. Subscribers can easily view performance criteria across sites and benchmark themselves anonymously against global industry peers. Combining data mining and preconfigured metrics, reliability engineers can investigate equipment data to identify assets that represent the best opportunities for improving maintenance costs and reliability. With access to the objective truth about asset performance, management can act with confidence to intelligently cut costs while increasing production, especially in times of shrinking margins.”
Asset Answers can identify and evaluate better performing equipment manufacturers and highlight predominant failure modes for specific equipment models. With this analysis, Asset Answers also can create opportunities for equipment improvements and automatically track the savings these improvements have provided.
Whitt also added that, “Asset Answers uses comparative analytics or ‘intelligent benchmarking’ that enables organizations to conduct ‘apples to apples’ comparisons of industrial equipment in production units across multiple plants within an organization. That same information helps organizations compare the relative performance of their assets against industry peers to gain a deeper understanding and a competitive advantage, optimize total cost of ownership (TCO) for critical assets and make better asset purchasing decisions.”
This approach both improves collaboration between Reliability, Engineering & Maintenance and also enables continuous and systematic improvement of operations and production output over time. Benefits of Asset Answers 2.0 include:
- A proven, systematic and secure approach to continuous improvement and Operational Excellence
- Improved plant and operator safety
- Mitigated operational and financial risk
- Improved insight into non-financial performance
- Lower asset total cost of ownership (TCO)
by Gary Mintchell | Feb 4, 2015 | Automation, Internet of Things, News, Operations Management, Software, Technology
Predictive technology in the asset performance arena seems to be the trend of the week. I wrote yesterday about a solution. Today brings another announcement. I think I’ll learn more about this one next week at the 2015 ARC Forum in Orlando. (By the way, if you’re there, please look me up.)
The headline for this article came from GE. I’ve heard of predictive maintenance (which many aspire to and few achieve) and condition-based maintenance (similar but, I guess, different). Here they combine the two. Check it out and let me know what you think.
GE’s Measurement & Control business and Meridium Inc. introduce Production Asset Reliability (PAR), an integrated Asset Performance Management (APM) offering for an all-in-one view of equipment health. Combining GE Measurement & Control’s System 1 condition monitoring and diagnostic applications with Meridium’s suite of enterprise performance management and asset strategy solutions, PAR provides a holistic and quantifiable view of operations, maintenance, availability and overall operating performance for production assets.
System 1, GE’s patented condition monitoring software, helps users quickly diagnose potential equipment and instrument health issues which can lead to equipment failure. Meridium’s applications provide structured processes and analytics to identify critical assets and failure modes, calculate equipment reliability and determine downtime impacts. The integrated PAR solution provides an end-to-end process that connects the machine diagnostics to the business context and execution to drive optimized maintenance practices and production loss management for all asset-intensive industries.
“Today’s measurement, monitoring and management systems are disconnected, and, as a result, organizations fail to leverage quality data for actionable insights,” said Art Eunson, general manager for Bently Nevada, GE Measurement & Control, a GE Oil & Gas division. “GE and Meridium’s integrated PAR offering empowers our customers with the ability to connect identification, evaluation and execution for greater asset optimization and productivity.”
Asset intensive organizations are challenged to maximize production, minimize costs, follow regulations and manage risk. To balance the demanding requirements, operators require a more cohesive system that assesses equipment performance and manages the resulting data. GE and Meridium provide this comprehensive solution for customers to effectively measure, monitor and manage each connected asset.
“With greater availability of big data and connected assets, there is an end-to-end picture of plant operations waiting to be tapped by organizations from the plant floor to the corporate office in order to stay competitive on a global scale,” said Bonz Hart, Meridium Founder and CEO. “PAR measures performance, quantifies risk and delivers analytics in real-time, providing customers with the insight needed to effect real change, improve efficiency and reduce maintenance costs.”
The Oil & Gas industry demand solutions that can grow with business demand and adapt rapidly to changing technical environments. That is why GE’s industrial solutions such as System 1 are standardizing on GE’s software platform for the Industrial Internet, Predix.
by Gary Mintchell | Jan 26, 2015 | Automation, Commentary, Data Management, Interoperability, Leadership, Manufacturing IT, News, Operations Management, Organizations, Technology, Workforce
[Updated: 1/28/15]
Last week I attended the board meeting of the Smart Manufacturing Leadership Coalition. Sometimes I’m an idealist working with organizations that I think have the potential to make things better for engineers, managers, and manufacturers in general. I derive no income from them, but sometimes you need to give back to the cause. SMLC is one of those organizations. MESA, OMAC, ISA, CSIA, and MIMOSA are other organizations that I’ve either given a platform to or to whom I have dedicated many hours to help get their message out.
In the area of weird coincidence, just as I was preparing to leave the SMLC meeting there came across my computer a press release from an analyst firm called IDC IDC Manufacturing Insights also about smart manufacturing. This British firm that is establishing an American foothold first came to my attention several years ago with a research report on adoption of fieldbuses.
The model is the “Why, What, Who, and How of Smart Manufacturing.” See the image for more information. I find this model interesting. As a student of philosophy, I’m intrigued by the four-part Yin-Yang motif. But as a manufacturing model, I find it somewhat lacking.
IDC insight
According to Robert Parker, group vice president at IDC Manufacturing Insights, “Smart manufacturing programs can deliver financial benefits that are tangible and auditable. More importantly, smart manufacturing transitions the production function from one that is capacity centric to one that is capability centric — able to serve global markets and discerning customers.” A new IDC Manufacturing Insights report, IDC PlanScape: Smart Manufacturing – The Path to the Future Factory (Doc #MI253612), uses the IDC PlanScape methodology to provide the framework for a business strategy related to investment in smart manufacturing.
Parker continues, “Smart manufacturing programs can deliver financial benefits that are tangible and auditable. More importantly, smart manufacturing transitions the production function from one that is capacity centric to one that is capability centric — able to serve global markets and discerning customers.”
The press release adds, “At its core, smart manufacturing is the convergence of data acquisition, analytics, and automated control to improve the overall effectiveness of a company’s factory network.”
Smart manufacturing
This “smart” term is getting thrown around quite a bit. A group of people from academia, manufacturing, and suppliers began discussing “smart manufacturing” in 2010 and incorporated the “Smart Manufacturing Leadership Coalition” in 2012. I attended a meeting for the first time in early 2013.
Early on, SMLC agreed that “the next step change in U.S. manufacturing productivity would come from a broader use of modeling and simulation technology throughout the manufacturing process”.
Another group, this one from Germany with the sponsorship of the German Federal government, is known as Industry 4.0, or the 4th generation of industry. At times its spokespeople discuss the “smart factory.” This group is also investigating the use of modeling and simulation. However, the two groups take somewhat different paths to, hopefully, a similar destination—more effective and profitable manufacturing systems.
Key findings from IDC:
- Use the overall equipment effectiveness (OEE) equation to understand the potential benefits, and tie those benefits to financial metrics such as revenue, costs, and asset levels to justify investment.
- Broaden the OEE beyond individual pieces of equipment to look at the overall impact on product lines, factories, and the whole network of production facilities.
- Technology investment can be separated into capabilities related to connectivity, data acquisition, analytics, and actuation.
- A unifying architecture is required to bring the technology pieces together.
- Move toward an integrated governance model that incorporates both operation technology (OT) and information technology (IT) resources.
- Choose an investment cadence based on the level of executive support for smart manufacturing.
Gary’s view
I’ve told you my affiliations, although I am not a spokesman for any of them. Any views are my own.
So, here is my take on this report. This is not meant to blast IDC. They have developed a model that they can take to clients to discuss manufacturing strategies. I’m sure that some good would come out of that—at least if executives at the company take the direction seriously and actually back good manufacturing. However, the ideas started my thought process.
Following are some ideas that I’ve worked with and developed over the past few years.
- To begin (picky point), I wish they had picked another name in order to avoid confusion over what “smart manufacturing” is.
- While there are a lot of good points within their model, I’d suggest looking beyond just OEE. That is a nice metric, but it is often too open to vagaries in definition and data collection at the source.
- Many companies, indeed, are working toward that IT/OT convergence—and much has been done. Cisco, for example, partners with many automation suppliers.
- SMLC is working on a comprehensive framework and platform (also check out the Smart Manufacturing blog). Meanwhile, I’d also reference the work of MIMOSA (OpenO&M and the Oil & Gas Interoperability Pilot see here and here).
- I’d suggest that IDC take a look into modeling, simulation, and cyber-physical systems. There is also much work being done on “systems of systems” that bring in standards and systems that already exist to a higher order system.
I have not built a model, but I’d look carefully into dataflows and workflows. Can we use standards that already exist to move data from design to operations and maintenance? Can we define workflows—even going outside the plant into the supply chain? Several companies are doing some really good work on analytics and visualization that must be incorporated.
The future looks to be comprised of building models from the immense amounts of data we’re collecting and then simulating scenarios before applying new strategies. Then iterating. So, I’d propose companies thinking about their larger processes (ISA 95 can be a great start) and start building.
These thoughts are a main theme of this blog. Look for more developments in future posts.
by Gary Mintchell | Nov 10, 2014 | Automation, Data Management, Manufacturing IT, News, Operations Management, Organizations, Standards, Technology
Collaboration works. Engineers and IT architects have been donating time to projects that stand to decrease the time from building large critical physical infrastructure assets to the operate and maintain phase. The resulting system could benefit owner/operators of those assets to the tune of millions of dollars.
Much of the work has been under the radar, but also much has been accomplished. MIMOSA, the “Operations and Maintenance Information Open System Alliance” a 501(c)6 non-profit industry association, focuses on enabling industry solutions leveraging supplier neutral, open standards. The methodology is to establish an interoperable industrial ecosystem for Commercial Off The Shelf (COTS) solutions components provided by major industry suppliers.
As I wrote a few weeks ago, the most amazing thing about MIMOSA, the organization, and the Oil&Gas Interoperability Pilot (OGI Pilot) specifically, is the amount of progress they have made over the past few years. Some of the work has been ongoing for over a decade. Emphases have shifted over time reflecting the needs of the moment and the readiness of technology.
The premise of the work going on is that major productivity gains critical physical infrastructure design, build, operate and maintain depend on transitioning to an interoperable, componentized architecture with shared supplier-neutral industry information models, information and utility services.
Large enterprises are now spending 15x or more of license fees on integration efforts. The standards-based interoperability model will dramatically reduce these direct costs while also improving quality, security and sustainability.
This boils down to the core problem of lack of interoperability between key people, processes and systems.
Here are just some of the accomplishments:
- Achieved a better strategic alignment with the PCA and Fiatech organizations
- Built a broader consensus around downstream system architecture demonstrated through OGI Pilot
- Beginning to expand from its downstream work to working with the Oil & Gas Standards Leadership Council on upstream solutions as well
The long-running OGI Pilot program builds out a test bed and pilots the ecosystem of data standards. The pilot provides for a continuous gap analysis and drove out the need for a standardized data sheet. The pilot started with a process flow diagram (PFD) and worked out the P&ID including most of the schematic for the P&ID schema that are variations of ISO 15926. The next part of the project is to develop all the data sheets that describe all the parts in detail. That’s the reason for the Industry Standard Data Sheet project (ISDD). That will pick up mechanical, electronic, and thermodynamic information. Then the project returns to the PFD to pick streams data.
Thus far, the project has focused on the CAPEX side of the system. Work is now returning to the OPEX (operations and maintenance) side.
This all returns focus to the OpenO&M Initiative to bring testable interoperability for Business Object Document (BOD) architecture from OAGIS.
Everything is built upon real implementation specifications including PRODML (production markup language), B2MML (business to manufacturing markup language), MIMOSA, CCOM-ML (Common conceptual Object Model), ISBM (information service bus model), CIR (common interoperability registry), OPC UA.
