by Gary Mintchell | Aug 26, 2015 | Data Management, Manufacturing IT, Operations Management, Software
Cisco just released the findings of a global study that indicates cloud is moving into a second wave of adoption, with companies no longer focusing just on efficiency and reduced costs, but rather looking to cloud as a platform to fuel innovation, growth and disruption.
The study finds that 53 percent of companies expect cloud to drive increased revenue over the next two years. Unfortunately, this will be challenging for many companies as only 1 percent of organizations have optimized cloud strategies in place while 32 percent have no cloud strategy at all.
The Cisco-sponsored InfoBrief “Don’t Get Left Behind: The Business Benefits of Achieving Greater Cloud Adoption” was developed by International Data Corporation (IDC) and is based on primary market research conducted with executives responsible for IT decisions in 3,400 organizations across 17 countries that are successfully implementing private, public and hybrid clouds in their IT environments.
Nick Earle, Senior Vice President, Global Cloud and Managed Services Sales, Cisco, said, “As we talk with customers interested in moving to the second wave of cloud, they are far more focused on private and hybrid cloud—Primarily because they realize that private and hybrid offer the security, performance, price, control and data protection organizations are looking for during their expanded efforts. This observation, which drove our strategy to build a portfolio of private and hybrid infrastructure and as-a-service solutions, is reflected in the new IDC study, which shows that 44 percent of organizations are either currently using or have plans to implement private cloud and 64 percent of cloud adopters are considering hybrid cloud.”
In the study IDC identifies five levels of cloud maturity: ad hoc, opportunistic, repeatable, managed and optimized. The study found that organizations elevating cloud maturity from the ad hoc, the lowest level to optimized, the highest, results dramatic business benefits, including:
- revenue growth of 10.4 percent
- reduction of IT costs by 77 percent
- shrinking time to provision IT services and applications by 99 percent
- boosting IT department’s ability to meet SLAs by 72 percent
- doubling IT department’s ability to invest in new projects to drive innovation.
The study also quantified the economic benefits the most mature cloud organizations are realizing. Organizations studied are gaining an average of $1.6 million in additional revenue per application deployed on private or public cloud. They are also achieving $1.2 million in cost reduction per cloud-based application.
The revenue increases were largely the result of sales of new products and services, gaining new customers, or selling into new markets. Organizations were able to attribute revenue gains to increased innovation resulting from the shifting of IT resources from traditional maintenance activities to new, more strategic, more innovative initiatives.
Operational cost reductions associated with cloud stem from the advantages to the business of running on a more scalable, reliable, and higher-performing environment. These include improved agility, increased employee productivity, risk mitigation, infrastructure cost savings and open source benefits.
Private Cloud’s Correlation
Private cloud allows better resource use, greater scale, and faster time to respond to requests, but with the added control and security of dedicated resources for a single company.
Adopting hybrid cloud can be more complex than adopting other forms of cloud. It requires workload portability, security, and policy enablement. These requirements were evident in the study, which showed that up to 70 percent of respondents expect to migrate data between public and private clouds (or among multiple cloud providers) and have high security and policy requirements.
Mature Cloud Adoption by Country
Mature cloud adoption varies by country, with the United States and Latin America among the countries with the greatest percentage of organizations with repeatable, managed or optimized cloud strategies, and Japan with the fewest among the countries studied. The study notes the percentage of organizations with mature cloud adoption in each country:
- 34 percent USA
- 29 percent Latin America Region
- 27 percent UK
- 22 percent France
- 21 percent Germany
- 19 percent Australia
- 19 percent Canada
- 18 percent Korea
- 17 percent The Netherlands
- 9 percent Japan
Cloud Adoption by Industry
By industry, manufacturing has the largest percentage of companies in one of the top three adoption categories at 33 percent, followed by IT (30 percent), finance (29 percent), and healthcare (28 percent). The lowest adoption levels by industry were found to be government/education and professional services (at 22 percent each) and retail/wholesale (at 20 percent). By industry, professional services, technology, and transportation, communications, and utilities expected the greatest impact on key performance indicators (KPIs) across the board.
Cisco Business Cloud Advisor Adoption Report, Tool and Workshop
Cisco is helping customers translate the findings of this study into customized reports for customers. These Cisco Business Cloud Advisor engagements come in two formats, a simple, survey-based tool and a more in-depth workshop.
The Adoption Report allows customers to go through a structured survey to determine their own cloud adoption maturity and associated business benefits relative to their industry peers—by industry, company size and geography.
The Adoption Tool and Workshop allows Cisco and qualified channel partner sales teams to bring a much deeper level of analysis to organizations. The half-day workshop will help organizations better measure the potential impact of cloud adoption on their IT organizations across a broad range of key performance indicators. The recommendations include vendor agnostic guidance regarding how organizations can evolve their cloud journey across a number of domains, including the Intercloud. The Adoption Tool and Workshop are currently being rolled out on a worldwide basis.
The Cisco Business Cloud Advisor Adoption Report, Tool and Workshop are based on the same unbiased primary market research conducted by IDC for the study.
by Gary Mintchell | Aug 19, 2015 | Internet of Things, Operations Management, Technology
The various parts of the Industrial Internet of Things ecosystem—smart devices, networks, databases, cloud, mobile HMI—really so help manufacturing and production operations, maintenance, and engineering perform better.
Fluke has made strategic acquisitions over the past several years that enhances its technology portfolio. It has brought together many of these technologies to make the IIoT useful. In the case of this new product, enhancing preventive maintenance.
Unplanned downtime due to equipment failure can cost manufacturers up to three percent of their revenue, according the U.S. Federal Energy Management Program. Manual methods of tracking equipment health to predict failures are time consuming and prone to errors and incomplete data, while existing computerized maintenance management systems can be costly and complex and often require significant IT resources to implement.
Fluke Connect Assets changes the way equipment maintenance is documented, reported, and managed.
Fluke Connect Assets is a cloud-based wireless system of software and test tools that gives maintenance managers a comprehensive view of all critical equipment — including baseline, historical, and current test tool measurement data, current status, and past inspection data — enabling them to set up and sustain a preventive maintenance (PM) or condition-based maintenance (CBM) system easily with minimal investment.
It features wireless one-step measurement transfer from more than 30 Fluke Connect wireless test tools, eliminating manual recording of measurements so maintenance managers can be more confident that the equipment history is accurate.
The system’s features allow maintenance managers to analyze multiple types of predictive data (for example, electrical, vibration, infrared images) all in one program, side by side, in a visual format that enables easy scanning. In fact, it’s the first software that allows you to compare multiple measurement types in one system, making it easy to see correlations and spot problems. This intuitive display of multiple measurements enhances the productive use of data and the ability to identify a problem, since each measurement type tests a different aspect of equipment health and together they present a more complete picture.
Key features of Fluke Connect Assets include:
- Asset Health dashboard — is a hierarchy based overview of the status of all assets over time, with drill-downs to the individual asset record for more details. This permits managers to identify anomalies or correlations across equipment.
- Asset Analysis – is a record for each piece of equipment that is the single source for all of its maintenance information. Managers and technicians can trend and compare thermal, electrical and vibration data over time for each piece of equipment in order to make optimal repair and replacement decisions.
- Asset Status dashboard — allows managers to quickly scan the most recent status updates for key assets so they can better monitor team and equipment activity.
Entire maintenance teams can capture and share data via their smartphones regardless of their location using AutoRecord measurements to automatically record measurements from Fluke Connect wireless test tools, upload the data to Fluke Cloud storage and then assign it to a specific asset for sharing and analysis. Technicians can collaborate with their colleagues to discuss problems while sharing data and images in real time with ShareLive video calls, speeding up problem solving, decision-making and approvals.
With the Fluke Connect Assets system, maintenance managers and technicians generate more reliable data to make informed decisions about equipment health, reducing unexpected equipment downtime, improving costs, and enhancing the efficiency of their teams.
by Gary Mintchell | Aug 6, 2015 | Automation, Data Management, Internet of Things, Networking, News, Operations Management, Technology
Industrial Internet of Things dominated keynotes and discussions during the annual National Instruments developer gathering known as NI Week.
There was less talk of cyber-physical systems and more discussion of benefits to managers and consumers, as well as the usual engineering target audience.
As usual, many customers and partners appeared on stage showing off some incredible feats of engineering built upon the foundation of NI products.
Dr. James Truchard, president, CEO, and co-founder, established the conference theme in his keynote, “ We have always been concerned with data. LabView is built for data flow as well as control. We have created a platform allowing standardized ways of interacting with the world that we call graphical systems design.”
Eric Starkloff, executive vice president sales and marketing, stated, “We are instrumenting the world. It’s like the Cambrian explosion of data. Diversity of data is evolving at a very rapid rate.”
He continued, “We’ve collected data for years, what has changed—connectivity.”
Jeff Kodosky, NI co-founder and “father of LabView,” devoted much of his presentation to point out the tremendous potential for the industrial Internet of Things—potentially of greater impact than the consumer Internet of Things.
One last thought brought home by Marketing Vice President John Graff involved the leveraging the power of the Industrial Internet of Things for predictive maintenance. “It can save 30% on maintenance and 45% on downtime according to US DOE. This led to a discussion of the test bed with IBM that I wrote about last week.
Product announcement
The most significant of the products announced this week was LabView 2015. The theme of the product release is, “write code faster; write faster code.”
Stated in the press release, the latest version of LabVIEW delivers speed improvements, development shortcuts, and debugging tools.
“Using LabVIEW and the LabVIEW RIO architecture allowed us to reduce the time of developing and testing a new robot control algorithm to just one week, compared to one month with a text-based approach. We are able to prototype with software and hardware faster and adapt to rapidly changing control requirements quicker,” said DongJin Hyun, Senior Research Engineer (Ph.D.), Central Advanced Research and Engineering Institute, Hyundai Motor Group
LabVIEW 2015 further equips engineers with support for advanced hardware such as the quad-core Performance CompactRIO and CompactDAQ Controllers, 8-core PXI Controller, and High Voltage System SMU.
LabVIEW 2015 also reduces the learning curve for employing a software-designed approach to quickly create powerful, flexible, and reliable systems. With three application-specific suites that include a year of unlimited training and certification benefits, developers have unprecedented access to software and training resources to build better systems faster.
Following is a list of features:
• Open code faster—open large libraries up to 8X faster and eliminate prompts to locate missing module subVIs
• Write code faster—execute common programming tasks faster with seven new time-saving right-click plugins and develop your own additional plugins to maximize your productivity
• Debug code faster—examine arrays and strings in auto-scaling probe watch windows and document findings with hyperlink and hashtag support in comments
• Deploy code faster—offload your FPGA compilations to the LabVIEW FPGA Compile Cloud service included with your Standard Service Program membership
LabVIEW 2015 is extended by the LabVIEW Tools Network, which has been enriched by IP both from NI and third-party providers. The new Advanced Plotting Toolkit by Heliosphere Research furnishes developers with powerful programmatic plotting tools to create professional data visualizations. The RTI DDS Toolkit by Real-Time Innovations enables IoT applications with scalable peer-to-peer data communication. Additionally, application-specific libraries for biomedical, GPU analysis, and Multicore Analysis and Sparse Matrix applications are now available free of charge.
by Gary Mintchell | Jul 30, 2015 | Commentary, Manufacturing IT, News, Operations Management, Software
OK, so I was wrong. Well, I was right and wrong.
My analysis of the Schneider acquisition of Invensys (Foxboro, Wonderware, et. al.) centered on European competition. Namely that as Schneider assembled a large industrial technology powerhouse it was looking at Siemens and ABB—its next-door rivals.
Schneider was already a competitor in the electrical power industry. Acquiring the process automation technologies business with Invensys brought it into more complete competition with ABB.
Software
On the other hand, I thought that Schneider might divest the software business partly because it never really had very much in the way of software.
OK, I was wrong.
Schneider announced last week that “it has reached a preliminary, non-binding agreement with AVEVA Group PLC (“AVEVA”) on the key terms and conditions of a combination of selected Schneider Electric industrial software assets and AVEVA (forming the “Enlarged AVEVA Group”).
On the surface this appears to be a strange marriage. In fact, my friend Walt Boyes did an anti-Schneider rant on his blog this morning. Amongst the rumors he alluded to about Schneider management and how Clayton Christensen’s analysis of acquisitions predicted that the acquisition would go south, he also misunderstood, I think, the implications of this move.
AVEVA is a construction engineering software company. It provides the front-end engineering for plants that Foxboro, Triconix, Avantis, and other ex-Invensys brands operate and maintain.
Design to operate
The upshot is that Schneider should be able to provide an end-to-end solution for process industries similar to what Siemens has done for discrete manufacturing with the integration of UGS and the Siemens PLM division.
By the way, this latter is an example of how a large company can beneficially absorb an acquisition. The merger has worked very well. Other European companies have closely watched this acquisition model. I believe that Schneider will have learned from it.
I wonder what implications for the OpenO&M Initiative and the OGI Pilot program—an ongoing effort to use standards to move data from the engineering design database to the operations & maintenance database. AVEVA was a key player.
Transaction details
It is expected that the proposed transaction would:
1. create a global leader in industrial software, with a unique portfolio of asset management solutions from design & build to operations, with both scale and a distinct market position to address critical customer requirements along the full asset life cycle in key industrial and infrastructure markets;
2. unlock additional value at enlarged AVEVA and Schneider Electric through the potential for material revenue and costs synergies, leveraging on complementary end-markets exposures, customer bases and product portfolios;
3. establish a ‘best in class’ management team and increased brand profile for attracting further talent; and
4. realize the full value of the contributed industrial software assets.
The enlarged AVEVA would have combined revenues and Adjusted EBITA of c. £534 million and c. £130 million, respectively. It is expected that the Enlarged AVEVA Group will continue to be admitted to listing on the Official List of the UK Listing Authority and to trade on the London Stock Exchange plc’s main market for listed securities. Schneider Electric intends to comply with the Listing Rules of the UKLA. As part of the transaction, Schneider Electric would contribute a selection of its industrial software assets to AVEVA and make a cash payment of £550m to AVEVA, (which would subsequently be distributed to AVEVA shareholders excluding Schneider Electric) in exchange for the issuance of new AVEVA shares, giving Schneider Electric a majority stake of 53.5% in the Enlarged AVEVA Group on a fully-diluted basis. Schneider Electric would fully consolidate the business in its Group financials.
In addition to any consultation procedures involving the personnel’s representative bodies that may be required, the transaction remains subject to, amongst other things, the completion of mutual due diligence to the satisfaction of both parties, agreement on the terms of legal documentation, the approval of the respective Boards of Schneider Electric and AVEVA, AVEVA shareholder approval and relevant anti-trust and regulatory approvals (if required). In accordance with the applicable law and regulation of the United Kingdom, a more detailed public announcement has been released today and is available on the AVEVA and Schneider Electric websites as well as on the AMF (French regulatory authority) website.
A further announcement will be made as and when appropriate.
by Gary Mintchell | Jul 24, 2015 | Asset Performance Management, Automation, Data Management, Industrial Computers, Internet of Things, Operations Management, Technology
Representatives of National Instruments (NI) and IBM recently discussed their collaboration on a test bed demonstrating the possibilities for using Internet of Things (IoT) technologies for taking companies from Condition Monitoring to Predictive Maintenance.
Chris O’Connor, IBM General Manager of IoT who works with divisions such as Maximo told me this is a new business unit that is built around IoT. There are about 6,000 clients. The explosion of data coming from devices means that industry must change from data centers to IoT. “For us, this entails the analysis of sensors information, aggregating the information, then constructing lifecycles. This will help world adopt IoT.”
The collaboration from condition monitoring and analytics changes questions manufacturers can answer such as, can I gain competitive advantage, can I offer better warranty, change frequency of maintenance.
Jamie Smith, NI’s Director of Embedded Systems, said the test bed project will roll out in multiple phases. It demonstrates the interoperability between two industry leaders including edge computing capability from NI to IBM’s cloud technology and analytics. Therefore, users can progress from condition monitoring to predictive maintenance.
The test bed consists of a motor and a couple of fans. Various failure modes are introduced. The first go consists of NI CompactRIO communicating via MQTT to IBM. Now that the proof has been completed, other companies in the Industrial Internet Consortium have been invited to join the collaboration. “All they need to do is contribute time and resources to it,” added Smith.
The next step according to Smith is insuring that it’s end to end secure. They are working with IIC to do security assessment. They will then look at more robust assets—most likely power generation assets—hoping to work with someone with large turbines or pumps to continue to demonstrate the technology and benefits.
Following is a description from the statement on the Web.
The Condition Monitoring and Predictive Maintenance Testbed (CM/PM) will demonstrate the value and benefits of continuously monitoring industrial equipment to detect early signs of performance degradation or failure. CM/PM will also use modern analytical technologies to allow organizations to not only detect problems but proactively recommend actions for operations and maintenance personnel to correct the problem.
Condition Monitoring (CM) is the use of sensors in equipment to gather data and enable users to centrally monitor the data in real-time. Predictive Maintenance (PM) applies analytical models and rules against the data to proactively predict an impending issue; then deliver recommendations to operations, maintenance and IT departments to address the issue.
These capabilities enable new ways to monitor the operation of the equipment – such as turbines and generators – and processes and to adopt proactive maintenance and repair procedures rather than fixed schedule-based procedures, potentially saving money on maintenance and repair, and saving cost and lost productivity of downtime caused by equipment failures.
Furthermore, combining sensor data from multiple pieces of equipment and/or multiple processes can provide deeper insight into the overall impact of faulty or sub-optimal equipment, allowing organizations to identify and resolve problems before they impact operations and improve the quality and efficiency of industrial processes.
Through this testbed, the testbed leaders IBM and National Instruments will explore the application of a variety of analytics technologies for condition monitoring and predictive maintenance. The testbed application will initially be deployed to a power plant facility where performance and progress will be reported on, additional energy equipment will be added and new models will be developed. It will then be expanded to adjacent, as yet to be determined, industries.
