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Internet of Things

25 posts

Abstract

The Internet of Things is made up of tens of billions of smart devices, like cameras, sensors and mobile devices, all capable of wirelessly communicating with each other and with us. About five billion new things are getting connected on a daily basis. Connected transportation vehicles is the fastest growing category for “smart, connected products”, after handheld devices. Whether it is self-diagnosing engine problems or acting autonomously and optimally, IoT is impacting transportation and enabling completely new possibilities.

Hitachi has long been a major player in the Transportation segment. With revenues of about $9B per year, Hitachi is a prominent Tier 1 supplier to the automotive industry. Hitachi also makes trains, which includes the rolling stock, components, software systems, and more. Hitachi is an R&D powerhouse in transportation as well: in our automotive research labs, Hitachi builds and tests ADAS systems (Advanced Driver Automation Systems), amongst many other cutting-edge technologies. ADAS is the backbone of self-driving cars of the near future.

Like in other industries such as manufacturing, energy and healthcare, Hitachi offers IoT solutions in transportation that provide multiple benefits. Here are five:

 

1.     Finding new revenue

2.     Increasing safety

3.     Getting important, actionable information

4.     Achieving higher efficiencies

5.     Delivering new experiences

 

This article will describe the benefits of IoT technology from Hitachi in these areas. For context, let’s take a quick look at Hitachi’s Automotive Systems Division.

 

Hitachi Automotive Systems

Headquartered in Ibaraki, Japan, Hitachi Automotive Systems develops, manufactures, sells and services transportation related components, industrial machines and systems. It has 40,100 employees in 62 companies at 133 sites throughout Europe, Asia, Japan and the Americas. Specifically, Hitachi Automotive Systems makes:

 

a.     Engine Powertrain Systems

      1. Control Systems
      2. Exhaust, Fuel and Ignition Systems
      3. Engine components and subsystems

b.    Electric Powertrain Systems

      1. Hybrid and Electric Vehicle (EV) Systems

c.     Integrated Vehicle Control Systems

      1. Autonomous Driving Systems
      2. 360 Degree Sensing Systems
      3. Drive Power Transmission, Suspension, Braking and Steering Systems

 

Hitachi actively supplies several components to the world’s top automotive OEMs. We have received five consecutive annual “Supplier Quality Excellence” awards from GM in recognition of our products, with motors, inverters and Lithium-ion battery packs leading our supply to Chevrolet Bolt, Malibu, Saturn Vue and Buick LaCrosse cars. And we have announced plans with Honda to build electric motor drivetrains in China.

 

As more components in automobiles become sensor-enabled, the availability of data from many parts of an automobile has exploded. That, per se, isn’t new: diagnostic data can already be read out by a mechanic using a handheld device. But there is tremendous value in having this data available wirelessly and in real-time, as opposed to at maintenance intervals or at fault occurrence.

 

Traditionally, that data is moved to a computer in the garage or sent to the cloud for analysis, where the mechanic can check against known issues or manufacturers’ recommendations on how and when to fix to what. But we are getting to a stage where this slow, manual process cannot be tolerated and the data needs to be analyzed immediately at “the edge”, in the automobile itself. For example, a self-driving “Connected Automobile” needs to know immediately if that small object approaching the curb is a suitcase that has rolled away or a child. It is edge-enabled data analytics that allows immediate intelligent remedies, recommendations, and actions.

 

Hitachi’s Leadership in Connected Automobiles

Hitachi is a leader in Advanced Driver Automation Systems. Hitachi has a self-driving capable Infiniti Q70, fully equipped with multiple sensors, LiDAR, cameras and computing power, that drives itself. It is owned and operated by Hitachi R&D labs near Detroit, MI. It was displayed at the NEXT 20173 show in Las Vegas this year. (The car was featured in an interview conducted by an analyst firm, featuring Hitachi Vantara’s Chief Marketing Officer, Asim Zaheer – check out the video here!)

This highly advanced Connected Car demo’d several IoT and data analytics features:

 

1. Autonomous Mobility: registered to drive in the state of Michigan, this car can drive itself on pre-designated routes. It uses stereo cameras, LiDAR and sensors to create a 360-degree vision around it. It then uses powerful onboard computers and engine control units to steer its way along a route.

 

2. Vehicle Occupant Health and Safety Analytics: Using data analytics and AI, this demo showcased healthcare analytics and its impact on driving. Using cameras and medical sensors, such as respiration sensors at chest level in the seatbelt, thumbprint sensors on the steering wheel and dashboard cameras aimed at the driver, the vehicle can measure, track, analyze and make critical decisions with regards to occupant safety and security. It can tell when the driver has alcohol in his/her bloodstream, and whether the driver is agitated, angry or sleepy, all key triggers for distracted driving.

 

3. Connected Powertrain for Fuel Economy with Autonomous Cars: Implementing AI and Deep Learning, this demo showed how predictive controls for automotive powertrain enables vehicles (especially autonomous vehicles) to operate at optimized engine and powertrain conditions that improve fuel economy based on actual and forecasted vehicle performance.

 

A Neural Network is fed with input parameters such as sensor information, weather, traffic and GPS data which then calculates and outputs an estimated Drive Cycle. Using supervisory controls, it analyzes and creates an optimized drive cycle1, plotting Actual vs. Predicted speed over time. All this leads to emission reductions, gas savings and helps deliver a comfortable ride, helping reduce an automotive OEM’s CAFÉ (Corporate Average Fuel Efficiency2) rankings.

 

4. Vehicle Failure Prediction and Maintenance: This demo showed an innovative IoT approach that analyzed data from smart components in the vehicle to predict failure of parts, thereby reducing unexpected maintenance and warranty costs.

 

5. Ride Comfort Control using AI: With AI and Machine Learning along with real time interaction with infrastructure, this demo showcased how to improve the ride and comfort of a vehicle based on driver preference (behavior), road conditions, and traffic and vehicle dynamics.

 

6. Fleet Management using big data analytics: Based on a commercial company’s trucking fleet that we’re engaged with, this showcase demonstrated features such as Asset Registration, Fleet Status, Predictive Maintenance, Vehicle Profile, Health and Location, Alerting, Operational Workflow Integration and an interactive fleet analysis4.

 

 

Clearly, Hitachi is extremely well positioned to deliver powerful AI-powered, IoT-enabled solutions for optimizing transportation, based on deep domain knowledge.  Let’s tie in the main benefits of IoT in Smart Transportation with Hitachi’s prowess:

 

1.     Finding new revenue

Older assets that aren’t internet-connected can be retrofitted, which can help them send and share data. As we showed with our self-driving sedan and Fleet Management big-data analytics solution, implementing IoT doesn’t necessitate equipment with built-in internet connectivity. Fleet Management and onboard diagnostics systems are actively used by transport operators, insurance companies, fleet owners and consumers to get realtime updates on vehicle location, health, driver and vehicle status, critical engine parameters, remaining useful life or predicted maintenance insights, and more.

A big challenge in transporting our Infiniti to Las Vegas for the NEXT 2017 show was the transport operator not being able to commit a pickup and drop off time with any accuracy: he lacked reliable advance visibility on which driver would be best located with what type of carrier! Being able to better manage his fleet with real-time driver and vehicle information would lead to higher efficiencies and more profits for that transport operator.

2.     Increasing safety

Data from cameras and sensors can help the car detect the driver as he or she approaches the car, precluding the need for even a car key: the car simply won’t unlock for an unauthorized person. Cameras detect whether the driver is in a capable state to drive. GPS and other services can control the areas the car can be operated in. The days of breaking into a car, hotwiring the ignition wires and driving off across the country are soon going to become as ancient as black and white movies!

3.     Getting important, actionable information

IoT devices connect and send data from sensors in engines, suspensions, tires, cameras, etc. This can be streamed to a cloud, or it can be analyzed “at the edge” itself when necessary. In either case, it’s important information that can lead to actions that help improve safety, efficiency, and lower costs. And as discussed already, IoT enables actionable fleet data with real time location, driver, vehicle, routes, traffic and weather information, live, providing critical information that leads to better operational efficiencies.

4.     Higher efficiencies

IoT sensors help build smarter, more efficient powertrains, as we’ve demonstrated. They also help perform predictive maintenance, at lower costs and optimal frequency, reducing unnecessary repair costs. Your car can tell you where the nearest tire repair shop is when it’s pressure is running low or changes abruptly. They help to reduce emissions and save fuel. They help deliver useful, immediate data that can help reduce costs and save money by enabling faster responses to opportunities.

5.     Delivering new experiences

New efficiencies due to connectivity and management of unattainable data leads to new experiences and increase comfort. For example, through the use of smarter use of IoT sensors in our suspension systems, the car can predict and detect upcoming road gradients and curves. In real time, it adjusts the stiffness of individual suspensions that adjust on the fly to reduce body roll, leading to a more comfortable drive.

 

Conclusion

Fleet vehicles are essentially becoming computers with wheels, and ADAS-equipped vehicles are, essentially, AI-powered, edge-computing robots. Advances in computing and communication technologies at rapidly lowering costs means that all vehicles will soon be talking with each other, adjusting among themselves to maintain optimum drive cycles, routes and sharing insights. This will lead to incredible new innovations, from vehicles that talk to other appliances, driving themselves to and from required destinations and service centers, to eventually precluding ever needing a driver’s license.

 

But data without context or intelligence is simply bad data. It needs to offer meaningful information, and information must deliver insights for better outcomes. IoT provides a channel – a means to get to key analytics, which, backed by AI and deep industry experience are what’s enabling the transformation in transportation. 

 

Hitachi’s experience building the machines that power the industrial sector combined with their experience building IT systems to deliver deep industry knowledge sets it apart. With a full stack IoT platform available for data blending, powerful machine learning with AI and industry expertise, Lumada’s analytics capabilities are the key providing digital transformative impact in the Transportation industry today. The era of Smart Transportation is upon us, and it’s powered by the internet of things. Follow us at Hitachi Vantara as we lead the way.

 

References:

  1. Driving Cycle: http://www.car-engineer.com/the-different-driving-cycles/
  2. CAFÉ: https://www.nhtsa.gov/laws-regulations/corporate-average-fuel-economy
  3. Hitachi NEXT 2017: http://www.hitachinext.com/
  4. Fleet management analytics: http://www.pentaho.com/big-data-use-cases/minimize-unscheduled-downtime

The internet of things (IoT) continues to evolve as more and more customers across a number of industries seek to achieve digital transformation and improve operational efficiency. Countries such as Germany and Japan are embracing IoT, Robotics and Artificial Intelligence to drive competitive advantages and create new opportunities with Industrie 4.0 and Society 5.0.

IoT mckinsey.png

 

As noted by McKinsey, IoT has a potential economic impact of $4T to $11T per year by 2025, but most notably, the manufacturing sector has the strongest potential to achieve outcomes with IoT. As a matter of fact, the potential impact could be somewhere from $1.2T to $3.7T by 2025 for Factory Operations and Equipment Optimization, according to McKinsey. IDC is also estimating manufacturing to be leading the IoT industry:

 

 

 

Given Manufacturing's position as the leading IoT industry, it's no surprise that manufacturing operations is the IoT use case that will see the largest investment ($102.5 billion) in 2016.”

 

If you look at the manufacturing industry as a whole, there are a number of problems that often bubble up such as quality issues, ever changing demand, production bottlenecks and legacy equipment interoperability. These challenges are why manufacturers are turning to IoT and digital manufacturing.

 

Let's look at some real-world examples of Hitachi working with some of the largest global manufacturers: 

 

Toyota

The world's biggest car manufacturer was looking for a solution to address diversified customer needs and increasing demand at their manufacturing sites. Toyota and Hitachi partnered to deliver a high-efficiency production model for immediate response and improvement in quality and productivity using Lumada and data analytics technologies.  Toyota and Hitachi plan to establish a system that prevents unexpected facility failures and extends the system to other processes for improved maintenance work efficiency.

 

Daikin

Daikin, an air conditioning manufacturer, was seeking to achieve consistent quality and improve productivity at production locations worldwide. Daikin turned to Hitachi for a solution that leverages video analytics and sensors to collect real-time actions from the 4M perspective (man, machine, material, method), such as trainer hand movement and changes of base metals and parts. The solution leverages statistical analysis and compares this data with the standard behavior model of skilled technicians. Trainees can now digitally evaluate brazing work and acquire skills in a shorter period of time all while improving the level of work, stabilizing quality and improving productivity.

Daicel

Daciel, a chemical company and supplier to the auto industry, was seeking to further improve its product quality.  The manufacturer chose Hitachi to implement a solution that identified production faults with in-depth data from the 4M perspective.  While difficult to obtain by human observation alone, machine learning has been able to identify deviations in activities that correlated with the faults and avoid future production failures. By taking full advantage of 4M data, Hitachi and Daicel took the solution a step further and developed a management and manufacturing dashboard using IoT to visualize key performance indicators from manufacturing workplaces. This provides plant managers and production line supervisions with prompt decision making capabilities. Daicel intends to deploy the solution at six other global manufacturing locations, thereby improving replicating higher quality and more cost savings several fold.

To learn more about Hitachi Industrial IoT solutions, be sure to visit      https://www.hitachivantara.com/en-us/solutions/iot-insights/industrial-iot.html

Henry Ford, the founder of Ford Motor Company, had a vision to build safe and efficient transportation for everyone. The main challenge in the early 1900’s was how to build affordable car for the masses.  Ford revolutionized manufacturing by building a moving assembly-line for automobile production. The assembly-line reduced the time to build a car from more than 12 hours to 2 hours and 30 minutes. This innovation had a profound impact on manufacturing efficiency and drove down the price of a car from $850 in 1908 to $300 by 1925. Perhaps the most quintessential American car, Ford Model T became the first car to be affordable for the average American worker and ushered in the era of mass production.

 

Manufacturing has come a long way from the assembly line innovation but productivity challenges remain. How can manufacturers increase productivity, improve process efficiency and speed up innovation today? The answer lies in advanced analytics and using real-time data for operational insights. According to Deloitte’s 2016 Global Manufacturing Competitive Index study, manufacturing executives ranked predictive analytics as their number one technology priority.

 

Where does Predictive Analytics fit in the manufacturing world and what is the connection with Industrial IoT? Industrial IoT is  harnessing sensor data and incorporating advanced analytics technologies in industrial sectors such as Manufacturing, Mining and Transportation to increase operational efficiency - the convergence of business IT and manufacturing OT systems. It involves connecting industrial assets to network, business applications and operators to deliver superior outcomes. The core value of Industrial IoT lies in industrial analytics that includes descriptive, predictive and prescriptive analytics  - mining machine data to analyze patterns, predicting future scenarios and generating insights or recommendations that drive operational decisions. Industrial analytics can provide the productivity boost that manufacturing needs, increase asset utilization and improve operational efficiency. Consulting giant McKinsey thinks that industry players are investing significant resources in Industry 4.0 because traditional productivity levers such as Lean and Six Sigma have been exhausted. The next generation of productivity is going to come from digitization of manufacturing with pervasive network connectivity, embedded sensors, cyberphysical systems and data analytics.

 

In the manufacturing world, one key pain point is unplanned downtime. Asset downtime means that manufacturing assets are idle resulting in lost production time. It is mostly associated with equipment breakdown and unscheduled maintenance but other factors such as supply chain disruption, labor shortage or operator error can cause system outage. In the automotive industry, average cost of system downtime can be $1.3 Million/hour. How can industrial analytics eliminate unplanned downtime? Let’s take the case of a critical industrial asset, the air compressor. A compressor is an essential component of the production process and 90% of all companies use compressed air in their operations. By deploying a condition monitoring system that leverages industrial analytics, you can record the parameters of the compressor in real time and observe the performance of the machine through a dashboard on a mobile or computer.  The system will send alerts about conditions that could lead to potential breakdowns and unscheduled stops. By taking an appropriate maintenance action based on real-time data, you can eliminate breakdown, capture data in CMMS system to prevent recurrence and improve system reliability. Advanced techniques such as vibration and spectrum analysis enable you to perform root cause analysis, identify specific component damage and take immediate corrective action.

 

Picture1.png

 

Industrial analytics can be applied to sensor data coming from the shop floor – CNC machines, motors, pumps, PLC’s and control systems etc. Aggregating and blending structured and unstructured data such as weather, human data, video feed, text allows you to detect patterns, identify correlation and decipher cause-effect relationships. Machine learning algorithms can spot deviation from normal operating condition by monitoring relevant KPI’s such as temperature, pressure, acceleration etc. Industrial analytics enables predictive maintenance, asset remaining useful life (RUL) calculations and offers appropriate maintenance recommendations allowing manufacturers to  improve asset uptime, reduce repair costs and increase operating efficiency.

 

Industrial analytics allows manufacturers to make sense of production data, generate actionable insights and address productivity issues - improve OEE, increase throughput and optimize asset utilization. Advanced analytics can also be applied to improve quality, optimize production scheduling and solve manufacturing pain points. It has the potential to spur innovation by introducing new products and services (XaaS). Moving assembly-line changed the business model for manufacturing cars, Industrial Analytics will be the game changer for manufacturing!

 

References:

 

http://corporate.ford.com/innovation/100-years-moving-assembly-line.html

 

https://www2.deloitte.com/global/en/pages/manufacturing/articles/global-manufacturing-competitiveness-index.html

 

Industry 4.0: How to navigate digitization of the manufacturing sector | McKinsey & Company

Lumada IoT platform helps manufacturing, energy and transportation anticipate the future

By Jagdish Upadhyay, Director Lumada Marketing

 

The internet of things (IoT) is gaining traction across industries where new IT capabilities and connectivity are driving innovation and operational efficiencies. Companies across the Industrial footprint are leading the way with exciting breakthroughs in industrial IoT (IIoT) that use big data, analytics and artificial intelligence (AI) to streamline production, enable predictive maintenance and improve quality across the entire product lifecycle.

 

Hitachi’s Lumada Industrial internet of things (IoT) platform is designed to accelerate your IoT journey. Let’s explore how.

 

Manufacturing

Multiple vehicle recalls have cost automotive companies billions of dollars. Product failures and quality issues are costly and can reduce productivity. The impact is more severe if you’re unable to rapidly discover the root cause.

 

Lumada solves the problem with predictive quality management. Using IoT sensors and 3D cameras, Lumada simultaneously gathers and analyzes human, machine and business data and measures worker movements. It detects assembly-line failures and shortcomings as they happen, and applies corrective action. Real-time predictive analytics identify potentially defective products prior to shipment, and advanced algorithms uncover deviations in work-related activities.

 

This aggregation and integration of data gives your operations a single consistent view for analysis and monitoring. Multilevel traceability pinpoints defective products so you can remove them before they are shipped. After implementing Lumada, manufacturers have achieved significant reduction in production costs and improved product quality and worker productivity.

 

Energy
With world energy consumption expected to rise 28% between 2015 and 2040, utility companies, power producers, and commercial and industrial customers are turning to renewable sources to help meet growing demands.[1] However, renewable energy production fluctuates with weather conditions, making it difficult to predict availability from day to day.

 

Using sensor data, Lumada connects, measures, monitors and manages energy delivery in real time, while algorithms provide insights into weather conditions that impact availability. Machine-learning models prepare generation and trading plans based on market, capacity, demand, weather and pricing data. Lumada reduces downtime by using predictive maintenance to detect potential asset failures, and continually builds intelligence using machine learning and artificial intelligence.

 

 

Transportation

As urban populations continue to grow, leaders around the world look for solutions to traffic congestion, inadequate parking and public transit, and an aging transportation infrastructure. From proactively managing shipping orders to enhancing business intelligence for airlines, to optimizing automobile traffic flows in cities, Lumada is reinventing transportation operations.

 

Lumada collects data to provide real-time monitoring of train performance, for example, and provides insights to optimize maintenance practices and overall operations. Predictive maintenance identifies malfunctioning door hinges, worn brakes, and transmission problems and other issues, so repairs occur before they impact passenger services.

 

 

Unique Flexibility for Industries: On-premises, in the Cloud or Both

Some organizations are not comfortable moving all your applications to the cloud, while others are now 100% cloud-based. No matter where you are, Lumada is flexible. It can run on the edge (on-premises), as a hybrid cloud or fully in the cloud. In addition to the examples described here, there are many innovative ways industries can put the power of Lumada to work creating smarter, more efficient and productive solutions.

 

Watch Lumada IoT Platform in action

https://youtu.be/Qy7OoH7uFn8



[1] U.S. Energy Administration. International Energy Outlook 2017. https://www.eia.gov/outlooks/ieo/

The Five Pillars of Lumada

 

End-to-end IoT ecosystem integrates advanced analytics, AI and machine learning to deliver transformative insights

By Rob Tiffany – CTO, Lumada

 

Your competitors are trying to accelerate their digital transformation just like you are. Choosing the right IoT platform for your business will get you there quickly. Lumada gives you the intelligence, composability, security and flexibility to drive innovation and continuous improvement while keeping you ahead of your competitors. Let’s take a moment to look at the five pillars of Lumada’s end-to-end IoT ecosystem and what they can do for you.

 

Pillar One: Lumada Edge

With sensors creating mountains of data from smart machines and applications, you need to easily integrate all this information into your business operations. With data prioritization, filtering and real-time edge analytics, Lumada makes it easy to securely speed data integration. This means whether it’s a terabyte a day from your fabrication lab or a terabyte an hour from an autonomous vehicle—it all has to be integrated while reducing costs and latency. And that’s not all: Lumada edge provides a complete, real-time view of asset status so you can put the right information in the hands of right people without compromising security.

 

Pillar Two: Lumada Core

Managing assets and integrating data from assets into business systems is key to the success of any IoT initiative. Lumada core streamlines this process by connecting assets, collecting data and using open APIs to make information available for analysis—and provides centralized identity and access management via secure credentials across your assets, edge gateways and services. Using asset avatars, Lumada core provides a 360-degree view of all your physical assets in real time, so you can activate automation at the edge while sending sensor information to an analytics system in your central office.

 

Pillar Three: Lumada Analytics

Lumada analytics uses machine learning and data mining tools to uncover patterns in equipment and device data, and fine tunes your assets for better operational efficiency. You can make more informed, data-driven decisions and use predictive and preventive maintenance measures to avoid costly breakdowns and delays. Lumada is composable, so you can keep your in-house analytic systems, and integrate Lumada analytics with your business applications.

 

Pillar Four: Lumada Studio

To effectively monitor connected IoT devices across your organization, you need a real-time dashboard. Lumada studio provides a graphical environment for creating interactive web-based dashboards and user-defined reports, and for managing alerts and notifications. You use plug-ins to connect to data sources and applications, and retrieve and blend human, machine, and business data from anywhere to optimize performance based on real-time insights.

 

Pillar Five: Lumada Foundry

Lumada foundry provides the underlying framework for the Lumada IoT platform. This platform-as-a-service foundation for Lumada is based on a distributed microservices architecture. With Lumada foundry, you can easily deploy, upgrade and scale services like security and support for software residing on-premises or in the cloud.

 

Get on the Road to IoT Success with Lumada

 

Enterprises are already deploying IoT solutions to leverage data across their organizations and gaining insights that help them innovate faster, respond to new opportunities, improve operations, reduce costs and gain market share. But without an end-to-end IoT platform that streamlines the entire process—from asset integration and management to data collection and analytics—many companies struggle to get the IoT benefits they’re looking for.

 

Hitachi brings decades of OT and IT experience to the Lumada IoT platform. We understand the challenges of connecting everything and the opportunities that arise when organizations illuminate their data. Whether you’re just getting started with your IoT initiative or already transforming your business, Lumada will help simplify and accelerate your IoT success.

 

See how you can put Lumada to work for your business and maximize the value of your data with our intelligent IoT platform.

 

Watch the video

Learn more about Lumada

Self-maintaining operations, human-machine collaboration and more.

By Jagdish Upadhyay, Director Lumada Product Marketing

 

While the Industrial IoT era is already redefining manufacturing, its benefits to business and society are only just beginning. Did you know…

  • Businesses are on track to have 3.1 billion connected devices this year.[1]
  • 2.6 million industrial robots are expected to be working in factories by 2019.[2]
  • Analysts estimate IIoT could add US$14.2 trillion to the global economy by 2030.[3]

 

With the latest wave of artificial intelligence (AI) driving IIoT, manufacturers will shift to outcome-based services to create new levels of competitiveness as customers require measurable results from the products they buy. Your operations will need to be forward-thinking, responsive, accurate and reliable to compete in this scenario. How will you get there? By getting more value from your data.

 

The Opportunity Lies in Your Data

 

Some people are calling data the new currency. Powered by AI, analytics and algorithms, IIoT is unleashing data-driven insights across the manufacturing value chain. It’s this huge amount of data generated by connected machines that holds the real value of IIoT. Data sent from machine sensors can be used to detect impending machine failures and product quality issues in real time. It can also predict outcomes and inform the supply chain about demand for aftermarket parts.

 

A World Economic Forum report identified key areas of opportunity enabled by data derived from the IIoT:[4]

  • Vastly improved operational efficiency, such as improved uptime and asset utilization, through predictive maintenance and remote management.
  • The emergence of an outcome economy fueled by software-driven services, innovations in hardware, and the increased visibility into products, processes, customers and partners.
  • New connected ecosystems, coalescing around software platforms that blur traditional industry boundaries.
  • Collaboration between humans and machines, which will result in unprecedented levels of productivity and more engaging work experiences.

 

A New World Awaits Thanks to IoT

 

We’re only beginning to see the benefits of integrating AI with IoT. As machine and deep learning technologies mature, we’ll see dramatic new capabilities. IoT will further improve industrial efficiency with advances like self-maintaining power grids and production systems, and self-healing engines that diagnose and repair issues for trucks on the road and jets in the air. Instead of simply producing products, manufacturers will use data from connected devices to deliver measurable results for customers. New business models will also arise to support the product-service hybrids. IoT platforms will capture, aggregate, and integrate data into the new ecosystems, and partners will collaborate to implement these digital business models to create new kinds of value.

 

IoT is creating career opportunities even as robotics and smart factories replace many human jobs. We can anticipate new jobs such as deployment specialists who will provide the seamless interoperability between disparate machines and physical systems across businesses and industries. Educational institutions will provide programs to support new workforce requirements. For example, the first degree programs for cybersecurity are being developed so that highly-skilled technicians can protect your data and operations throughout the ecosystem.

 

The digital world is clearly transforming the way we work and interact with society and the environment. By connecting the systems and processes that have long operated independently, the IoT revolution has the potential to create safer, smarter, healthier and more sustainable lives for all of us.


 


[1] Gartner. Gartner Says 8.4 Billion Connected "Things" Will Be in Use in 2017, Up 31 Percent From 2016. February 7, 2017.

[2] International Federation of Robotics. World Robotics Report 2016.

[3] Accenture. Winning with the Industrial Internet of Things. 2015.

[4] World Economic Forum. Industrial Internet of Things: Unleashing the Potential of Connected Products and Services. January 2015.

Collaborate to solve new problems and identify new opportunities

By Björn Andersson, Senior Director, Global IoT Marketing

 

Forbes calls co-creation the “secret sauce to success.” With greater competition, rapidly-changing markets and the need to respond instantly to consumer feedback, traditional approaches to innovation are no longer adequate to keep your business ahead of the pack.

 

That’s why organizations across industry sectors are bringing partners into their ecosystem to co-create new products and services that deliver value in novel and innovative ways.

 

   Innovation has been turned inside out.

Companies are embracing co-creation as a new way of innovating.”

– Longitude Research

 

Co-Creation Brings Challenges—But Offers Huge Rewards
Successful co-creation starts with companies making a significant cultural shift that encourages open collaboration. This means sharing ideas at an early stage with customers and supply-chain partners to employees, academic institutions and government organizations.

 

The internet of things (IoT) is key to driving the innovation ecosystem of co-creation. By enabling more integration of connected devices and sharing the data with partners, co-creation builds on the expertise of your enterprise to better envision, develop, deploy and operate the best possible solutions.

 

But that’s not all. A 2017 survey by Longitude Research involving 554 executives across a range of companies found that more than half of respondents embrace co-creation as a new way of innovating—and many of these organizations have already achieved real benefits.

 

Screen Shot 2017-10-16 at 1.58.14 PM.png

  • 57% said co-creation has transformed their organization’s approach to innovation.
  • 52% said co-creation has reduced the cost of developing products and services.
  • 51% said co-creation has improved financial performance.
  • 61% use co-creation to produce successful new products, services and commercial opportunities.

 

Hitachi’s Co-Creation Approach
Hitachi has created a rich co-creation ecosystem that includes our many Hitachi Group companies, technology partners, system integrators, Hitachi Lumada IoT Platform and solution cores, and our Global Center for Social Innovation. Together, we work with your organization to jointly create a unique solution and solve your specific challenge.

 

Our comprehensive co-creation services begin with establishing a complete understanding of your data and the problem to solve. Next, our data scientists build an analytics model using your sample data, we create prototypes and evaluate their performance with production data before we deploy your custom solution.

 

As we jointly develop, test and deploy your IoT solution, you'll benefit from our expertise and your own, as well as other intelligence and perspectives. That's how co-creation generates better results. Hitachi remains your collaborator in managing and supporting your IoT solutions, and we can iterate the co-creation process to further optimize and transform your business.

 

Screen Shot 2017-10-16 at 2.43.12 PM.png

Source: Longitude Research

 

200 Co-Creation Projects and Counting
Companies across industries are embracing IoT to drive innovation—and co-creation enables organizations to innovate and gain more value faster, more reliably and more cost-effectively than ever before. Hitachi has already partnered with companies on more than 200 projects to successfully co-create on different levels, and we can do the same for you.

 

Learn more about co-creation in the IoT era: Watch the video.

 

Explore how co-creation is being adopted across industry sectors: Read the report.

42! The answer to life, universe and EVERYTHING!

If only everything would be as easy...

 

IoT, Industrie 4.0, Predictive Maintenance and the use of data in different areas of industry is a
big topic nowadays.

 

In our webinar series The Hitchhikers Guide to IoT we give you insights into the world of IoT
and how Hitachi can help to focus on the right solution and learn from best practices.

 

TitleDateSpeakerRegistration Link
IoT is everywhere, but DON’T PANIC. 6 Considerations to make them successful.

on-demand

Christian Dornacher

Director, Storage & Analytics Solutions EMEA

HDS

www.brighttalk.com/webcast/12821/252753
IoT, Big Data & Moving from Data to Knowledge

on-demand

Wael Elrifai

Sr. Director of Sales Engineering, EMEA & APAC

Pentaho a Hitachi Group Company

 

Related Blog: www.pentaho.com/blog/author/wael-elrifai

www.brighttalk.com/webcast/12821/256425
IoT – Tools and Technologies to build the IoT Stack

on-demand

Christian Dornacher

Director, Storage &
Analytics Solutions EMEA

HDS

www.brighttalk.com/webcast/12821/255439
IoT – Critical
Success Factors
on-demand

Christian Dornacher

Director, Storage &
Analytics Solutions EMEA

HDS

www.brighttalk.com/webcast/12821/264055

Industrial IoT -

Digitization of Manufacturing:

from Theory to Practice

on-demand

Greg Kinsey,

Vice President at Hitachi Insight Group

www.brighttalk.com/webcast/12821/269231
Information
Management in the Context of IoT

on-demand

Christian Dornacher

Director, Storage &
Analytics Solutions EMEA, Hitachi Vantara

Jan Konjack

Pre-Sales Consultant,
Hitachi Vantara

www.brighttalk.com/webcast/12821/284095
Digitization of Automotive Manufacturing

November 9th, 2017,

11:00 am CET

Greg Kinsey,

Vice President at Hitachi Insight Group

www.brighttalk.com/webcast/12821/2764477
Data Management in Healthcare & Research

November 23rd, 2017,

11:00 am CET

Christian Dornacher

Director, Storage &
Analytics Solutions EMEA, Hitachi Vantara

Jan Konjack

Pre-Sales Consultant,
Hitachi Vantara

www.brighttalk.com/webcast/12821/290197

Illuminate your data and accelerate your IoT journeyon-premises or in the cloud

By Rob Tiffany – CTO, Lumada

 

If you’ve explored the internet of things (IoT) offerings lately, you know there are hundreds of IoT platforms that promise connectivity between sensor-equipped devices and applications. In fact, a June 2017 Global IoT Platform report identified 450 companies offering solutions for homes, healthcare, the automotive industry and manufacturing organizations.[1] The report also noted that over 30 of the companies on the 2016 list no longer exist. 

 

With hundreds of IoT platforms on the market, how do you find the one that’s right for you? Many of these platforms provide little more than connectivity and require third-party add-ons to ensure security and gain insights from IoT data. If you’re looking for IoT capabilities that drive greater efficiencies, productivity and competitive advantages, you may want to explore an IoT platform that’s intelligent, composable, secure and flexible.

 

Intelligent, Composable, Secure and Flexible IoT Solution Drives Innovation

Lumada’s intelligence comes from asset avatars, digital representations of physical assets that give you a complete view of a single asset or all your assets at once. Its composable architecture is extensible, domain agnostic and hardware agnostic, allowing you to switch architectural components with third-party alternatives as needed. Lumada security is built into every aspect of the platform, from the edge to the core—for data at rest as well as in transit. Finally, the platform is flexible to run on-premises or in the cloud—or both. These capabilities support our three-tiered IoT ecosystem of platform, solution cores and co-creation services.

 

1. Platform Illuminates Your Data to Drive Better Outcomes

Data holds immense potential to reduce costs, increase efficiency, overcome challenges and seize new opportunities. But until the data is illuminated, its power remains untapped. The Lumada IoT platform delivers the most advanced capabilities available today to turn your data into intelligent action.

 

2. Solution Cores Easily Adapt to Meet Your Needs

Lumada includes solution cores, which are Hitachi’s pre-validated IoT building blocks that can be combined and customized to meet the challenges you face today. Solution cores are modular, customizable and pre-validated elements that give you a head start in solving problems, reaching desired outcomes and discovering new opportunities through IoT.

 

3. Co-Creation Drives Innovation

Hitachi IoT specialists work with your organization to jointly develop, test and deploy a unique IoT solution that addresses your specific challenge. Afterward we continue to collaborate in managing and supporting your IoT solutions, and we can iterate the co-creation process to further optimize and transform your business.

 

Transform Your Data Into Insights to Drive Your Business

With hundreds of IoT platforms on the market today, you want to be certain you deploy an IoT solution that delivers the digital transformation you envision. With more than 100 years of experience building operational technologies (OT) across industries and over 50 years developing leading IT systems, Hitachi is uniquely qualified to deliver IoT solutions. We are also one of the few IoT providers that delivers our platform both on-premises and in the cloud—so you have the flexibility to deploy intelligent, secure, customized solutions faster, helping you grow your enterprise.

 

To learn more about Lumada, see Understand the Lumada IoT Platform

 


[1] IoT Analytics. IoT Platforms Company List 2017 Update. June 27, 2017.

From simple games to self-learning systems – AI has come a long way

By Ravi Chalaka, Vice President, Global IoT and Lumada Marketing, Hitachi Vantara

 

Today, talk of artificial intelligence (AI) is everywhere – from Apple’s Siri to how Uber dispatches drivers, to the way Facebook arranges its Newsfeed. However, it wasn’t long ago that AI was regarded by many as purely science fiction – the plotline of Hollywood blockbusters, such as 2001: A Space Odyssey. The term “artificial intelligence” was coined in 1956 with the hope of creating machines that could emulate human intelligence, such as reasoning and judgement.

 

Those early days drew scientists from academia to enterprise, to ignite a revolution of innovation that we’ve been riding ever since. Here are three significant waves of AI that have brought us to where we are today – while the first two generated hype and no real commercial adoption, the third time was the charm, which has already produced many real world use cases, taking us closer to the fulfillment of that early vision.

 

First Wave: Age of Search and Deductive Reasoning
The first wave of AI generated a lot of interesting ideas in the 1950s. Engineers devised deductive reasoning programs with logical rules, a method in which a conclusion is based on multiple premises that are assumed to be true. This approach led to simple games such as the first computer program capable of playing the game of Draughts. Although these first-wave AI systems could perform straightforward reasoning tasks, they were unable to learn anything on their own. While they couldn’t be applied to business at the time, some of today’s applications in smartphone maps can be traced back to this first-wave of AI technologies. But in general, this wave did not have any material impact on business or people’s lives.

 

Second Wave: Age of Knowledge Acquisition

The second wave of AI began in the 1980s with big AI projects when researchers turned their focus to helping machines acquire knowledge. Instead of just programming precise rules for machines to follow, they tried to teach machines the knowledge of experts, and developed statistical models which machines could use to adapt this knowledge to different situations. While second-wave AI machines had some breakthroughs – Deep Blue became the first computer system to defeat a reigning world champion Gary Kasparov in 1997 in chess – many of these second-wave expert systems struggled with accuracy due to complexity issues, rendering them impractical for most business applications. Commercialization of AI was still elusive.

 

Third Wave: Age of Machine Learning

Since the turn of century, we’ve been riding the third wave of AI, where computers use machine learning  and deep learning techniques to automatically learn from vast amounts of data and improve from experience without being explicitly programmed with knowledge. Immense processing power enabled development of artificial neural networks, better natural language processing, and enhanced image processing. Third-wave AI is  now able to consume data from statistical models, identify patterns in the data, create common sense rules, and incorporate information from multiple sources to reach a conclusion on their own. For example, AI – along with internet of things (IoT) connectivity – is extracting data from wearable devices and public sources to create personal health updates in real time. We’re seeing third-wave AI driving numerous commercial applications in personal assistants, such as Amazon’s Alexa and operating self-driving vehicles used in industry. This wave is expected to last for a long time while dramatically changing the way we live.

 

While the journey from the simple games of the 50s to the self-learning machines of today has been quite a ride – we have just scratched the surface of the full potential of AI. One thing is for certain: AI is more than Hollywood storytelling. It has become essential for suggesting alternate driving routes in rush hour traffic, making online shopping recommendations – even helping airport security officials use AI with video cameras to perform live face matching to recognize criminals within a crowd at busy terminals.

 

But the big game changer is applying machine learning in industrial environments, such as manufacturing, transportation, mining, agriculture, and energy to predict failures, recommend options and even augment human activity to build safer cars, sustain the planet, achieve mass customization, and reduce waste. Hitachi is making significant investments in AI’s machine learning and deep learning research and development to deliver solutions for the industrial world with its AI-enabled Lumada IoT Platform.  

 

In a future blog, I will discuss the future waves of AI, when AI becomes ASI (Artificial Super Intelligence) which means it first catches up and subsequently surpasses human intelligence. Don’t worry we are many, many decades away from that wave.

Industrial revolution 4.0 technologies drive manufacturing to new heights

The industrial internet of things (IIoT) is the application of IoT technologies in manufacturing. Like the first industrial revolution in the 18th century, IIoT is transforming today’s manufacturing industry. This fourth industrial revolution is built on advancements in artificial intelligence (AI), IoT, 3D printing and robotics, and they’re the foundation for the factories of the future.

 

Let’s see how this 250-year evolution from mechanism to machine learning and smart factories was built on disruptive technologies that stretched across four revolutionary phases.

 

Industry 1.0: Mechanization Using Steam Power

Before Edmund Cartwright introduced the first mechanical loom in 1784, textiles were produced in people’s homes. Cartwright used water and steam to power his mechanical looms, which led to giant leaps in productivity and helped launch the first industrial revolution. The original design was continually refined, and by 1850 there were 250,000 power looms operating in England—and mechanized versions of other equipment like paper machines and threshing machines soon followed.

 

Industry 2.0: Mass Production Using Electrical Energy

 

The first assembly lines appeared in the meatpacking industry in 1870 and drastically reduced the time to slaughter and dress a single steer from eight hours to 35 minutes.[1] By 1913, Henry Ford developed a moving assembly line for large-scale manufacturing, producing affordable cars faster than ever before. When cars became available to the masses, thereby creating a more mobile society, many other industries quickly followed suit by adapting the assembly line.

 

Industry 3.0: Automated Production Using IT

 

In 1969, Richard Morley developed the first programmable logic controller (PLC) for General Motors. Originally designed to replace hard-wired relay systems, PLC’s hardened embedded processor, running a real-time proprietary operating system, became a mainstay of the industrial automation world.[2] Today, PLCs control a vast array of equipment and can be found in everything from factories to vending machines.

 

Industry 4.0: Cyber-Physical Systems

 

The fourth industrial revolution is the IIoT era, in which companies are leveraging intelligent, connected cyber and physical systems to monitor, analyze and automate manufacturing. The result is predictive maintenance, improved safety and other operational efficiencies. We’ve already seen approximately 50 percent replacement of legacy machines that cannot be connected. According to a June 2017 forecast, the number of connected devices is expected to grow to more than 45 billion by 2023, which represents an annual growth rate of 20%.[3]

 

 

What’s Next for Industry 4.0?

 

IIoT technologies enable smart factories to deliver greater operational efficiency, on-demand products, support access to information from any source at any time and implement environmentally sustainable practices. But that’s not all. With advances in AI and machine-learning, and more connected devices on the horizon, expect IIoT to make an even greater impact on how customers use and experience the final product.

 

Hitachi’s Lumada IoT platform connects industrial assets with intelligent software to deliver powerful capabilities for smart manufacturing, including end-to-end operational visibility, predictive quality and optimal production efficiency.

 

 

Ready to learn more about Hitachi and Lumada? Watch the video.


 


[1] Bramley, Anne. “How Chicago’s Slaughterhouse Spectacles Paved the Way for Big Meat.” December 3, 2015.

[2] Payne, Jeff. “Future of the PLC.” Control Engineering. August 26, 2014.

[3] Frost & Sullivan. “IoT Security Market Watch—Key Market Needs and Solution Providers in the IoT Landscape.” June, 2017.

 

 

Enterprises around the world are looking at internet of things (IoT) technologies as a transformative opportunity to improve operational efficiency and drive innovation. Yet, with all the promise IoT offers, companies struggle with complex challenges that prevent them from making the leap. With hundreds of competing IoT platforms on the market today, manufacturers, transportation companies and energy producers need guidance and an experienced partner to implement the best IoT solution that deliver valuable outcomes. With more than a century of experience building operational technologies (OT) and five decades in informational technologies (IT), Hitachi is uniquely prepared to help.

 

Hitachi offers Disruptive Innovation for IIoT Platform Market With Lumada

Today, Hitachi Vantara a dnewly formed company for IoT, announced Lumada IoT Platform 2.0 to help enterprise customers, partners and Hitachi companies to simplify and accelerate their journey to Industrial IoT (IIoT) and Commercial IoT. A standalone software offering for IoT developers and architects, Lumada is the most composable, flexible, intelligent and secure end-to-end IoT platform. These capabilities are essential for you to create the kind of innovative solutions that will drive your business transformation.

 

It’s composable because the architecture extends to fit your unique needs and is domain and hardware agnostic. It’s flexible because it can run on premise or in the cloud or both, and supports IoT deployments at the edge and in the core. It’s intelligent because of its advanced analytics, artificial intelligence (AI), machine learning (ML) and digital twins – called Asset Avatars – which deliver rapid insights on your assets. And security is built into every aspect of the platform, and for data at rest or in transit.

  

Gain Powerful Insights With Lumada’s End-to-End IoT Platform

Lumada IoT platform software delivers these capabilities through five major layers that blend machine, human and business data from across the enterprise and combines it with AI and analytics to accelerate your time-to-value:

  • Lumada edge: Supports asset integration, data caching and filtering at the edge and near the assets
  • Lumada core: Provides asset registry, identity and access management and creates Asset Avatars to enable users to manage asset performance effectively.
  • Lumada analytics: Blends machine, human and business data and uncovers patterns and insights with powerful analytics, ML/AI.
  • Lumada studio: Provides pre-defined widgets to simplify the creation of dashboard applications; issues alerts and notifications or and 3rd party application enablement.
  • Lumada foundry:as well as security and micro-services,

Internet of Things@

The new Lumada IoT platform helps you improve operations with descriptive, predictive and prescriptive analytics, informational dashboards and new automation capabilities.

 

Adapt to Meet Your Needs and Drive Innovation

Getting the most value out of the IoT means more than just bringing together sensor data from assets. Your organization must apply context to sensor data and use this data to improve reliability and performance. In fact, analysts report that as much as 80% of a company’s data is considered “dark data” or unusable information.

 

The name Lumada was derived from the words illuminate and data. Lumada delivers data driven outcomes that increase operational efficiency, greater product quality and innovative business opportunities. To do that, Lumada is a three-tiered IoT approach that includes the IoT platform, solution cores and co-creation services.

 

  • Lumada IoT platform
  • Solution cores
  • Co-creation

 

With this three-tiered approach, Lumada accelerates the creation of IoT-based solutions to solve problems and deliver the outcomes you’re looking for.

 

Illuminate Your Data With an Intelligent IoT Platform

The IIoT is leading digital transformation, combining sensor data with human data to improve operational efficiency for manufacturing, energy utilities and transportation companies. Lumada puts your organization at the intersection of physical and digital worlds, so you can quickly and easily use your data to gain insights that provide a foundation for business transformation.  

 

Maximize the value of your data with Lumada, Hitachi’s intelligent IoT Platform, and turn your challenges into opportunities.

 

Read the Lumada News Release

To the list of greatest inventions of the world such as the wheel, compass, steam engine, concrete, automobile, railways, airplane add 21st century’s offering the Internet of Things or IoT. Gartner estimates the total economic value-add from IoT will reach US$1.9 trillion worldwide in 2020. Other reports claim close to half the companies in sectors like oil, gas and manufacturing industries are already using Instrumented devices capable of providing valuable data.

 

The major benefit of IoT is the ability to measure, monitor and manage any asset in any location from anywhere at any time. However, companies implementing IoT face some real challenges. At its heart IoT involves dealing with data streams from a wide variety of sensors. For example a regular automotive car has roughly 30k parts and the new generation autonomous cars may likely have even higher number of smarter parts. These parts either by themselves or through connected instrumentation generates about a GB of data per second in operation, we are talking about 3600GB of data per hour. All this data must be taken through an intelligent lifecycle from capture to archive and used all along to support the data driven decision process.

How do you make sense of this? Where do you begin? How do you create an environment that learns by itself to use or discard the insights generated by using these data? Is it about accuracy or precision or both? What impact does it have on real time operations and decision making?

The primary challenge is handling the massive amounts of data. This includes security of the data and the network as well as the analytics required to derive usable business intelligence from it. IoT technologies have to support this entire process from sensing, transforming, network, analysis and action. If it were to be a homogenous environment where, we are dealing with assets of one class or type, it would still be a scalability challenge. With number of asset types and assets of each class multiplying in the process, the complexity is getting multiplied across the layers from edge to action. There is no interoperability among these asset types and the whole technology landscape has gotten crowded with several siloed solutions and products.

 

Apart from this an IoT implementation faces issues like:

  • Ubiquitous connectivity: Yes, it is 2017 but network outages do occur even in the most advanced nations leaving the very concept of in stream data analytics at risk.
  • Interoperability: The numbers of different systems connected through IoT continue to create interoperability challenges.
  • Competing standards: Different IoT vendors are pushing their standards creating a veritable Tower of Babel. This will take time to sort out.

 

A successful IoT implementation needs to address three issues:

  • Complexity: IoT is not a one-size fits all kind of solution. The key is to find a scalable platform that integrates all aspects of the business to ensure seamless information flow across the enterprise.
  • Data Usage: Sensors will throw up a huge amount of data. There needs to be sanity across all layers of implementation. The overall platform architecture needs to have a robust data management and distributed analytics framework to create actionable insights where it matters.
  • Security: Hackers and sensitive data loss created a big risk and interrupt operations. It is therefore a business imperative to have a solution that identifies each and every asset which is locked-down at every tier using authentication and authorization while enabling logging, blacklisting and encryption of data at rest or in transit.

 

The benefits that accrue from a smart enterprise far outweigh the risk and the complexities involved in its implementation. Customers have the real need of dealing with new product innovation, eliminate wastage in their process, improve product quality, reduce operational costs and create new consumption led business models.

 

So the bottom line really is not if you need to make your business smarter, but how soon you can do so. For delaying the process is simply handing your competition an unassailable advantage.

On July 13, 2016, Hitachi and Daicel announced their collaborative efforts in development of an Image Daicel_company_logo.pngAnalysis system to detect signs of facility failures and deviations in front-line worker activities.


Daicel, a chemical company based in Japan, creates high performance chemicals and engineering plastics such as automotive airbag inflators. In recent years, mega-recalls in various industries (specifically in the automotive industry regarding part failures) have brought a renewed interest in accumulating and managing manufacturing performance data. Manufacturing performance data is essentially a gold mine - it can be used to identify the causes of product defects and implement countermeasures. Prior to Hitachi's involvement, Daicel was unable to identify when or where production issues occurred within their manufacturing plants.


3013789-poster-1920-faq-about-self-building-self-tooling-people-free-manufacturing-plants.jpgTogether, Hitachi and Daicel developed an Image Analysis System that uses in depth cameras to extract 3D forms to measure worker activities. Hitachi stressed the importance of gathering a wide range of work related performance data including manufacturing performance and inspection data and the results of visual checks by workers. The new image analysis system uses depth cameras to detect operational failures in production in facilities and deviations in worker activities on the front lines of manufacturing. Additionally, new manufacturing execution systems (MES) that incorporate Hitachi's IoT technologies including advanced analytics were crucial for Daicel to implement, especially in regards to automotive airbag inflator production processes.

 

What Are The Expected Results?

  1. The Image Analysis Technology is expected to improve quality and productivity
  2. The solution is expected to dramatically improve the time to discovery of machine and material defects which will reduce the overall number of product recallsDaicel2.jpg
  3. By using obtained image data, the role of on-site management supervisors will shift their focus on monitoring of trends and preventative measures to prevent outages and failures before they occur
  4. Hitachi and Daicel will begin operations of this solution at the Harima Plant in FY2016 and plan to promote the rollout to six of Daicel's main overseas plants in the coming fiscal year

 

Learn more about how Hitachi Insight Group can help you lead your industry by optimizing your enterprise.

It’s been about 4 months since I transitioned from Business Applications solutions marketing to IoT marketing within the newly formed Hitachi Insight Group. In this role, I am now focused on energy, specifically microgrids, which is a new and exciting field for me. As I’ve learned in these last few months, microgrids are key to achieving energy resilience as written by Jeremy Deaton in this article, Here's why the lights stayed on at NYU while the rest of Lower Manhattan went dark during Hurricane Sandy. Jeremy Deaton (@deaton_jeremy) explained how microgrids provide cleaner power. He also stated that microgrids can lower energy costs, and I’d like to dive deeper into that topic with this blog post.

 

Historically, microgrids often cost more than traditional power. As such, they were more attractive to niche applications with special needs, such as hospitals and remote military bases. Today, microgrid costs, particularly solar photovoltaic (PV) systems are coming down, which is helping microgrids enter the mainstream of U.S. power supply.

 

Hitachi, for its part, is focused on three things that enable energy resilience as well as lower costs:

  • Energy-first design
  • Microgrid controls that use IoT technology
  • One-stop shop product and services, including finance

MG.jpgOur energy-first design approach has enabled us to deliver microgrids, sized between 1.5MW and 40MW, at a cost equal to and sometimes lower than current energy prices. This is important in parts of the United States where electricity costs are high such as in the East and West coasts as well as Hawaii. This design approach takes into account what customers’ energy needs are first and foremost. Hitachi Microgrids are designed to use the strength of the entire portfolio. And since we aren’t pushing any particular product or system, we are able to use best-of-breed components that are best suited to our customers’ requirements.  For example, we’ll take a combined heat and power unit or turbine and we combine that with the variable load shape of a solar PV array that actually matches a load curve in a building or community very well and we tie that together with energy storage.  All these are actively managed by intelligent microgrid controls.

 

The microgrid controls are monitoring the equipment and incorporating sensor, weather and other types of data enabling us to take advantage of the Internet of Things (IoT) and advanced analytics to fine tune energy supply every moment of the day.  We can also monitor operations 24/7 and if the data shows a particular trend that can affect one of the energy resources, we can get our maintenance team to go an explore the issue before it causes a major disruption.   In the end we optimize resources  and increase cost savings over time.

 


Hitachi, which recently announced its North America Energy Solutions Division, has been in the energy business for decades thus has a thorough understanding of the market. The North America team takes a unique approach to the overall economics of a microgrid project. Since microgrids use a number of energy resources (check out this video to see how microgrids work), designing, building, operating and managing them could be a very costly proposition. Many vendors offer a piece of the value chain, whether it be the microgrid components or the construction, operations and maintenance. Very few can deliver on the full microgrid lifecycle, Hitachi on the other hand can deliver microgrids from “soup to nuts” from feasibility studies and solution design all the way to construction, operations and maintenance often times surprising many of our customers who are accustomed to dealing with multiple vendors. And through Hitachi Capital as well as partnerships with other banks, Hitachi can offer financing, eliminating a common roadblock for projects. Hitachi uses a power purchase agreement (PPA) model which means that customers don’t have to pay any upfront costs. Hitachi and its financing partner create a special purpose entity for ownership and operation of the microgrid. Hitachi gets paid back over a 10 to 20 year period.

 

As the number of power outages in the US continue to rise due to weather-related incidents, microgrids are a solution to “keeping the lights on.”  Not only can it provide resiliency, but cleaner power at a price that doesn’t cost "an arm and a leg".

 

Are you considering microgrids for your community?  I’d love to get your comments.