ARCHIVE FOR THE ‘digital-twins’ CATEGORY

In May Innosuisse awarded ZHAW the principle researcher and HSLU as the project management lead in a Smart Twins project (full name is “Digital Twin-based Services in industrial product-service system environments”). Dr Shaun West, Lucerne University, gives us an overview of the project...

Field Service Management is becoming an increasingly complex beast, particularly in the face of increasing customer demands - the solution lies in real-time writes Manuel Grenacher, GM of SAP Field Service Management...

The longer a plant is malfunctioning or down, the more costs companies have to bear. To avoid that, IoT-based solutions such as condition monitoring and predictive maintenance enable organizations to oversee machines in real-time. At the same time, however, these concepts result in increased complexity: In the event of emergency, companies expect that problems with their plants will be remedied immediately.

For service technicians, that means to act fast upon requests: their customers do not only expect high-quality service, but also the speed of service delivery should be up to their expectations. But how to keep up with the increasing demand? Intelligent planning in an ever-growing digitalized world is crucial to companies: it builds the foundation for excellent field service. Thus, on-demand service is no longer sufficient – organizations have to go beyond their conventional methods to handle customer requests.

More than ever, field service software helps to keep up with the pace: technicians are able to receive information that is accurate to the minute and can respond directly. Thanks to modern transformation technologies, upcoming problems can be detected right from the start and inquiries can be processed in real-time. Companies need to be the master of your offered services. Real-time service delivery can be easily implemented, and the result is remarkable: more satisfied customers and an increased turnover.

Requirements For Digital Twins In Service
Sufficient sensors and a systematic evaluation of the data are the essential basis to predict imminent component failures – an approach that is already feasible today. However, technical possibilities are still far from being exhausted right now. Due to ongoing depreciations or for other economic reasons, companies are only gradually investing in plants equipped with modern IoT technology. IoT, however, will become more affordable in the near future. Sensors will therefore spread continuously while at the same time becoming easier to use, more resistant and cheaper.

New concepts for real-time monitoring
Predictive maintenance and condition monitoring are two examples for future-oriented solutions that support service technicians in delivering the right service at the right time. The concepts are able to identify when maintenance work is required by collecting data from the machine itself, previous service calls and connected tools. Under certain circumstances, maintenance can even be conducted by the machine itself without human interaction.

Furthermore, technologies providing predictive maintenance and condition monitoring do not only help to maintain plants, they also steer the technician toward the root cause of the problem: the service specialist knows when a problem will occur and is able to initiate preventive actions – In addition to malfunctions and interruptions of plants being reduced, production capacity increases.

The potential of digital field service and crowd service
If you want to offer high-quality field service to your clients, you cannot avoid digitizing your work processes. With the rise of IoT, a wide range of new solutions have emerged, for example digital field service management solutions. By using such software, service providers can record, sort, and prioritize customer data easily. This helps to quickly assign technicians to customer requests and process them. Digital field service management solutions store information on the current order, the customer history and machines, which leads to a high first-time fix rate. But what to do if a plant unexpectedly shuts down and no technician is available?

A nightmare not only for operators, but also for manufacturers and service-providers. To master this challenge, the implementation of a crowd service approach can help to strategically avoid service shortage. Companies can reach out to their partner ecosystem, which may consist of the enterprise group, subsidiaries, partners or freelancers. In that way, technicians can be sent to the client by using on-demand distribution.

As a result, resources can be bundled, services improved, and customer satisfaction increased. Increased service reach through real-time support Real-time service is not only about being quickly on-site – it is also about giving support via email, video, chat and social media as well as via client portals and mobile applications.

At the same time, many customers want to be actively involved: with the help of self-service portals they can check operational data, view tutorials, request remote support from an external support team, or even make an appointment with a service technician.

Offering clients a range of real-time contact opportunities, and, thus, being available 24/7, ensures a sustainable and positive customer experience.

Manuel Grenacher is General Manager of SAP Field Service Management

Titos Anastassacos from Si2Partners shares with us some interesting insight on Augmented Reality from their recent research-based reports...

Technology is changing field service rapidly.

In the not too distant future Smart Connected Products will be self-diagnosing; Maintenance will become, almost exclusively, predictive; Spare parts will be 3D printed; And humans will interact at a deeper level with machines through Augmented Reality and Digital Twins, whether the machine is in the same room or on the other side of the planet.

The nature of the service business will shift from technical labour and logistics to knowledge management and exchange. Service delivery will change drastically as will the nature of competition and business models.

 

"The nature of the service business will shift from technical labour and logistics to knowledge management and exchange. Service delivery will change drastically as will the nature of competition and business models..."

 

But if the “end-state” medium term can be discerned quite clearly, getting there poses significant challenges.

So, at a Si2 Partners, we developed a series of survey-based management reports, to shine a spotlight into service businesses’ efforts to grasp the opportunities of digitization while dealing with the challenges. We then draw conclusions and recommend the best ways forward. The first report on Augmented Reality is available now, the next report on Predictive Maintenance is due by the end of the year.

The first public demonstration of AR was in 1998 during ESPN’s coverage of a football game: Generation and display of the yellow first down line. The line stayed fixed within the coordinates of the playing field. It was not physically present on the field and was visible only to the television audience.

But from that simple application, only 15 years later, Gartner was predicting that companies would be increasing their profits by over $1 billion annually -by 2017- through the application of AR in their field service business.

Things, of course, are not so simple. Reducing costs does not directly translate into increased profits.

That depends on prices and we know that digitization tends to make them drop, sometimes to zero -think of what happened to chemical photography. But even if we only consider costs, AR is clearly important, in many ways transformational, technology with a potentially very powerful impact.

So, are companies adopting AR for field service? Our survey showed that they are.

Most expect significant cost savings and productivity improvements through AR, mainly in engineering time and travel cost -and, interestingly, smaller companies are at least as much engaged with the technology as larger ones: Upfront investment can be low, and it can be implemented quickly and stand-alone (at least initially).

Importantly, it may help reduce pressure on scarce, highly qualified, and expensive engineering resources, while simultaneously improving the cost-effective support of remote customers (smaller companies are less likely to have extensive service networks).

Overall, we found that while less than 1/3 of respondents already used AR, and, of those, the majority had introduced it over the past 12 months, another third planned to introduce it over the coming 12 months. This indicates an accelerating trend.

Of course, for users, it has not been all smooth sailing. Challenges are numerous: For example, it turns out that connectivity at customer sites is a significant issue, which hampers the use of the technology. But technical problems are normal at this stage of introduction.

Far more important are managerial challenges.

For example, as always, one size does not fit all: The most commonly reported use case is field technicians receiving AR-based support by experienced engineers from a remote central hub.

 

"Better applications for such cases may be pooling AR-based support, providing technical information through “knowledge-libraries”..."

 

This may help companies with large field service workforces (possibly with high turn-over rates or fewer qualifications) supporting standardized equipment. It is not much help to vendors of highly complex equipment whose field engineers are already highly experienced and qualified themselves.

In fact, it may be even counter-productive, slowing things down or reducing acceptance.

Better applications for such cases may be pooling AR-based support, providing technical information through “knowledge-libraries”, particularly on rarely encountered problems or legacy equipment, or integrating AR with the IoT, so that operational data can provide real-time context to engineers and support for diagnostics.

However, such applications require investment in digital content, something that many AR users have often not considered, as well as a process of experimentation and development.

Another finding is that following implementation of AR, many managements don’t take the necessary action to lock-in the AR benefits by pushing through change in the support and field service processes. For example, few companies eliminate technical manuals and drawings from a field engineer’s toolbox, delaying the necessary adjustments.

And, while many companies market their AR capability to customers, few have developed AR-based offerings. Yet our survey shows that customers would welcome AR-based support if it would help to reduce costs and improve performance, notwithstanding issues of confidentiality or privacy.

The process to integrate AR into a company’s mode of operations and to maximize its benefits will, as for any new technology, be arduous and bumpy. But the impact on costs and productivity is becoming clear. Though most don’t yet formally track it, 72% of our respondents said that AR is on par with or has exceeded expectations.

Augmented Reality in Service: Ready for Prime Time? Visit the Service in Industry Hub Shop to download the flyer or purchase the report. For more information contact titos.anastassacos@si2partners.com or visit Si2Partners

 

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This week GE unveiled expansions to its suite of edge-to-cloud technologies and industrial applications, designed to help its customers build a complete asset strategy.

These additions to the GE Digital portfolio complement the key software applications that drive industrial productivity and extend these benefits through Predix, the application development platform for the Industrial Internet.

To help industrial companies get the most out of their industrial assets and drive better business outcomes, GE Digital today introduced: Predix Edge technologies to accelerate computing at the edge; the Predix platform combined with Microsoft Azure, the cloud for enterprises; new Operations Performance Management software to bridge productivity from assets to operations; enhanced Field Service Management solutions to improve the customer experience; and new platform tools to simplify industrial app development.

“Industrials that unlock data to master asset productivity will be positioned to lead,” said Bill Ruh, Chief Digital Officer of GE and CEO of GE Digital. “To power digital transformation, industrial organizations must understand every stage of the asset lifecycle. The company that designs, builds, operates, maintains and services industrial assets is best equipped to help others with their Industrial IoT journeys. And only GE offers the combination of industrial apps, underpinned by an industrial platform, to ultimately drive customer outcomes.”

 

Edge-to-Cloud Intelligence on Any Industrial Asset, Anywhere

By 2022, Gartner predicts that 75 percent of enterprise data will be created and processed outside the data center or cloud. The ability to compute and manage this information both at the edge and in the cloud are essential for industrial companies to truly optimise their operations.

To help customers accelerate their edge strategies and make any asset an intelligent asset, GE Digital is expanding its Predix Edge capabilities to help run analytics as close to the source of data as possible. Predix Edge gives customers with limited connectivity, latency limitations, regulatory or other constraints a way to deploy applications closer to the originating data – or at the edge.

Enhancements include:

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• Predix Edge Manager allows customers to support large fleets of edge devices – up to 200,000 connected devices from a single console.
•  Predix Machine enables microservice-based applications to run at the edge on customers’ virtualized data center infrastructure or on server-class hardware from GE or its partners. This also supports Predix Edge Manager, which was previously available only as a cloud service.
• Predix complex event processing (CEP) allows for faster and more efficient analytics and other event processing at extreme low latency, available at the edge in Q1 2018.[/unordered_list]

These edge solutions can help companies move from intelligent asset management to automation to insights-led machine learning across a distributed system. One example is EdgeLINC, a comprehensive edge-to-cloud solution from GE Transportation integrated with Predix Edge Manager, Predix Machine and Asset Performance Management applications. EdgeLINC enables efficient device management, configuration and streaming analytics even when machines, such as rail assets, are constantly moving in and out of communication.

Predix Platform on Microsoft Azure

GE Digital and Microsoft are bringing together the advanced industrial platform services of Predix with the flexible, enterprise-proven services of Microsoft Azure. Available in North America starting Q4 2017 and expanding globally in 2018, this partnership extends the accessibility of Predix to Microsoft’s global cloud footprint, including data sovereignty, hybrid capabilities and advanced developer and data services, enabling customers around the world to capture intelligence from their industrial assets.

The partnership helps businesses better connect their information technology (IT) systems with their operational technology (OT) by bringing a company’s systems – and data – together in a shared environment. While IT and OT have traditionally existed in silos, Microsoft and GE are bridging this gap and giving industrial customers a way to more easily improve performance, increase operational efficiency and accelerate the shift from automation to intelligence.

 

Advanced Applications to Make the Industrial Internet More Actionable

Understanding how an asset operates and its maintenance needs is critical to mitigating risk and improving productivity. Alongside its Asset Performance Management (APM) software, the core application deriving value from industrial assets, GE Digital introduced a complementary application that improves the operational performance of assets – like pumps, valves and heat exchangers – and drives a comprehensive asset management strategy.

This new Operations Performance Management (OPM) solution helps industrials increase revenue and margins, optimise the throughput of industrial processes and make their sites more profitable. OPM uses real-time and historical data – along with advanced analytics – to help customers make better operational decisions. The solution provides an early warning if industrial processes deviate from plan, arms operators with the information and time to troubleshoot operational issues and helps them take preventative actions to meet business goals.

GE Digital’s OPM software initially targets the mining industry and will expand to additional industries early next year.

The OPM solution has already helped customers achieve significant improvements to revenue and profit including:

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• A platinum operator increased overall throughput by 10 percent, consistently reaching maximum design capacity and increasing recovery by 1.5 percent.
• A large mining company achieved a 5.5 percent increase in throughput while consuming 2 percent less power
• A gold producer realised a 1.5 percent increase in recovery while reducing equipment-related costs through improved process efficiency.
  [/unordered_list]

Enhanced Field Service Management Solutions

With service technicians looking to embrace technology to improve their productivity and deliver a better experience for customers, ServiceMax from GE Digital, the leading field service management (FSM) solution, announced several enhancements to its FSM suite – enabling even greater efficiencies and bringing advanced analytics to service operations.

Artificial intelligence-enabled predictive service times now integrate the Apache Spark AI engine to improve service time estimates. Additionally, a new application integration solution enables service providers to launch and share FSM data with third-party mobile applications installed on the same device. New capabilities in schedule optimisation allow for dependent job scheduling between work orders for multiple visits aimed at improving first-time fix rates. As part of GE Digital’s FSM portfolio, these new features allow operators to minimise downtime, optimise costs, reduce risk and improve productivity for your services team.

Advanced App and Digital Twin Solutions

GE Digital also introduced Predix Studio to help companies build and scale their own industrial applications and extend its Asset Performance Management (APM) suite, Available in Q1 2018, Predix Studio simplifies the development process by giving customers the ability to extend applications and empower industrial subject matters experts – or citizen developers – to build apps in a low-code, high-productivity environment. A vital demographic, citizen developers comprise controls and reliability engineers, OT operators and line of business users with domain expertise but little or no coding experience. Using a mix of AI and machine learning, Predix Studio automates the heavy lifting of creating Industrial IoT apps – opening app development to an entirely new kind of developer. 

To help customers capitalise on new growth opportunities, GE created the Digital Twin Analytics Workbench, a solution that applies a library of algorithms and templates to make it faster and easier for companies to build their own digital twins on Predix. GE’s experience in managing industrial assets has generated hundreds of millions of hours of machine data and a deep understanding of how machines perform in various conditions. Modelling that physical data into digital twin models allows GE to deliver applications that better predict and improve the performance of physical machines.

 

The Analytics Workbench, currently a technology preview from GE Power, can be used to augment existing digital twins with new data streams. For example, power producers using drones to inspect wind turbine blades, pipelines or fuel reserves can integrate visual inspection data into the digital twins they already use to manage generation assets and grid infrastructure. The Analytics Workbench also helps users implement machine learning capabilities that allow those models to improve themselves over time.

Unveiled as part of GE’s Minds + Machines conference, these solutions from GE Digital are designed to help customers successfully advance their digital industrial transformation journeys while realizing real and immediate benefits to their bottom lines.

 

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