Internet of Things: Creating Customer Value from Home to Industry

Internet of Things: Creating Customer Value from Home to Industry

This post was written by Prabhu Soundarrajan, global marketing director for Honeywell Analytics

 

The Industrial Internet of Things (IIoT) has been a very popular topic. Several startup companies emerged, and major corporations introduced initiatives throughout the year. Most of us are wondering where IIoT will go within our industry. I want to offer a personal account of how I have been affected by the trend and share my thoughts on how it may impact our industry.

Having spent the past 15 years in the commercialization of innovative technology, I took it upon myself to understand the economic value created by this new technology.

Connected home

My home is now connected. Throughout the year, I piled up a number of “smart home” devices to enable my house for IoT. It started with a smart thermostat, camera, lighting, shower, security system, home theater, TV, and car. By definition everything in my home has connectivity to enable new value in comfort and flexibility. So is IoT for the connected home really new? It is really an evolution of what I am used to, with a slight premium for technology and convenience. I was happy to pay for it and enjoy the benefits of a connected home. I made the transition within a year without really noticing it. Every major retailer has IoT-enabled products and offers incentives to encourage consumers to buy IoT-enabled products.

Applications such as automatic climate control, energy management, and 24/7 security drove my willingness to pay. I paid a few hundred dollars to make my home “connected,” and my wife (boss) already appreciates it. I look like a rock star to her.

Connected industrial safety

Companies are leveraging IoT connectivity so customers can have the same level of connectivity in their workplace as I have in my home (e.g., an IoT-enabled connected safety solution for industrial workers). Industrial work environments are challenging in terms of safety hazards, compliance requirements, and exposure to risks. Unexpected events can lead to a major accident, causing downtime for several days, which in turn affects the productivity of the enterprise. Connected, safety-enabled IIoT has 24/7 real-time monitoring to provide situational awareness for the worker, supervisor, plant manager, and whoever else needs to be in the know. Gas detectors and personal protective equipment are some of the “things” in the safety space that give tremendous value when connected.

Connected workplace

The benefits already proven by connected safety solutions are tremendous. An ethanol plant in the state of Washington could detect a small leak in a storage column when a worker was doing a regular inspection. The worker transmitted information about a gas leak, which the control room operator translated as a product leak after the first few hours of system installation. This helped the plant to change work procedures and process optimization that saved more than $250,000 for the enterprise. The return on investment for a connected safety solution was only a few months.

A major petroleum refiner in Texas embraced connected safety solutions to develop a new emergency management process. It transmitted the hazard data map from gas detectors monitoring the perimeter of the facility, along with a wealth of new data, to the control room three kilometers away. An oil-processing plant in California correlated the personal exposure data for worker health and developed comprehensive work procedures for confined space entry, resulting in greater compliance with environmental regulations. This company shared best practices across its global sites securely over the cloud to enhance a culture of safety. These positive developments were not possible in the past when edge devices were not connected, but with connectivity new value streams were identified for the end user.

The practical applications of IIoT and connected safety solutions are driving three major value propositions for the enterprise:

  • Safety: End users can now transition from reactive to proactive safety procedures and plan and manage the entire safety life cycle of the enterprise.
  • Compliance: Work rules management has transformed from “trust” to “verification” to reduce liabilities across the enterprise.
  • Productivity: Real-time, 24/7 safety data increases operational efficiency by reducing or eliminating labor-intensive procedures.

The IIoT is creating value in both home and industrial environments. The final say for the technology is in the incremental and differentiated value created for customers.

About the Author
Prabhu Soundarrajan is global marketing director for Honeywell Analytics. He has served in a number of capacities as a volunteer leader, including director of ISA’s chemical and petroleum industries division (ChemPID).

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A version of this article originally was published at InTech magazine

Why MQTT Is an Ideal Connectivity Protocol for the Industrial Internet of Things

Why MQTT Is an Ideal Connectivity Protocol for the Industrial Internet of Things

This article was written by Steve Hechtman, president, CEO, and founder of Inductive Automation

 

A number of competing technologies and protocols have been in play for the Industrial Internet of Things (IIoT), each with strengths and weaknesses. There is one protocol, however, that appears to best address the unique demands and challenges of the controls business: MQ Telemetry Transport (MQTT). MQTT is an OASIS standard that is open and royalty free.

MQTT is a publish/subscribe protocol whereby edge-of-network devices publish to an MQTT server that can be on or off the premises. The data can then be discovered by, and delivered to, any number of subscribing clients. Clients can be supervisory control and data acquisition (SCADA) systems or other enterprise applications. This one-to-many capability decouples edge-of-network devices and data-consuming client applications for more efficient information distribution and increased scalability.

 

Traditional polling systems usually require clients to know everything about edge-of-network devices in advance. In brokered publish/subscribe systems, such as MQTT, data can be discovered and tags can be automatically generated by the simple act of subscribing from a client—which can save an immense amount of development time.

Several features of the protocol make it particularly suitable for remote sensing and control. It reports by exception and has extremely lightweight overhead (2-byte header). Unlike the usual poll/response model that generally saturates data connections with unchanging data, MQTT maximizes available bandwidth. In fact, it was originally developed for the often low-bandwidth, high-latency, and unreliable data links used in the oil and gas industry. Update rates in the 100-millisecond range are possible even with external cloud-based brokers.

MQTT also maintains stateful session awareness and is bidirectional. When an edge-of-network device loses network connectivity, all subscribed clients will be notified with the “last will and testament” feature of the MQTT server (which is important in the SCADA world). The last known and time-stamped value will still be available using the “retain” message feature of the transport. The bidirectional capability of MQTT means that any authorized client in the system can publish a new value to the edge-of-network device, so bidirectional connectivity is maintained, as you would expect of any SCADA system. The changed value is then read and published back to the broker from the edge-of-network device, thus confirming to all subscribed clients that the value has changed.

Being a lightweight and efficient protocol facilitates a higher throughput rate, which in turn significantly increases the amount of data that can be monitored or controlled. Therefore, organizations can publish stranded intelligence from field devices, such as flowmeters, to the MQTT server, and maintenance folks can subscribe to it (whereas operational clients would subscribe to operational data). Previously, this metadata had to be manually retrieved from the location, because it was often so voluminous that bandwidth limitations made transporting it out of the field hard to justify.

Security is permission based in that the credentials used to log into an MQTT server determine the resources available to that user. Because MQTT was designed on top of TCP/IP, authentication and encryption are typically transport layer security. They are implemented outside of the specification to keep it simple, lightweight, and future proofed as TCP/IP security models change. Security can be further enhanced with on premise brokers or a hybrid model.

The MQTT specification is data agnostic; it does not define a data representation for the message payload. This can present a problem of compatibility between different MQTT systems, because each can have different data representations. The controls industry has a limited number of well-known data types, so the formation of compatible edge-of-network devices, brokers, and subscription clients is within reach. In fact, a number of companies are already working together on it.

There are quite a few open-source projects for MQTT clients (e.g., the Eclipse Paho project) and brokers (e.g., Mosquito and RabbitMQ). Although MQTT was borne from oil field requirements, it is now used as far afield as Facebook Messenger. Amazon Web Services announced that Amazon IIoT is based on MQTT as well.

Most likely, polling schemes and existing protocols will remain the standard on local area networks, but wide area data acquisition and control systems will transition toward one of the industrial IIoT paradigms. MQTT appears to be a protocol with a good track record, good adoption, and unique suitability for the control systems used by industry.

About the Author
Steve Hechtman is the president, CEO, and founder of Inductive Automation. Before starting the company in 2003, Hechtman had 25 years of experience as a control system integrator. He co-founded Calmetrics Company, a control systems integration company, in 1988 and became president and CEO in 2000. He formed Inductive Automation to bring up-to-date technologies to the controls business with Web-based, database-centric products and sensible licensing models.
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A version of this article originally was published at InTech magazine

How IIoT Will Revolutionize Real-Time Plant Maintenance and Analytics

How IIoT Will Revolutionize Real-Time Plant Maintenance and Analytics

This article was written by Mary Bunzel, general manager of the Manufacturing Industry Solutions Group at Intel Corporation.

With all the hype in the press about the “new” Internet of Things (IoT) and what it offers industry, it is challenging to decide which pieces are best for an organization and how to get started. The fact is, what is best for your organization is probably at least a bit different from what is best for another organization.

Systems and processes no longer exist in and of themselves. With connectivity and visibility throughout the enterprise, the interrelationship between all parts of an organization is becoming obvious. This provides new opportunities for improvement and for leveraging technology to achieve more efficient operations.

 

Production processes, maintenance protocols, safety initiatives, training content (or lack of it), staffing, and schedules affect each other in ways we could never have foreseen even 10 years ago. Yes, we understood that interconnected components were potentially valuable, but now we have technology in place to better define, measure, and act on these interrelationships.

After the business challenges of the 2008 global financial crisis, most of us have harvested the low-hanging fruit that keeps the doors open and allows us to continue improving. The next step is to take advantage of the tools of IoT. IoT has been part of our lives for quite a while, whether we know it or not. Our cars, assets, and even our Amazon accounts use huge numbers of data streams to protect us, improve performance, and drive our buying habits. Perhaps IoT should be called “things we can communicate with,” but TWCCW does not quite roll off the tongue.

What is the difference between now and 10 years ago? Analytic methods and software have been refined. They are easier to use and available on demand with cloud services. In the past, we could see most of the obvious correlations. Those that were less obvious were only identified by really smart subject-matter experts using spreadsheets, really geeky math, and big mainframe computers such as the IBM 360.

Analytic engines give us the capability to work many of these concepts much more quickly. Just as the PC distributed processing from the mainframe to the desktop, analytic engines drive the processing the same direction. We can process thousands of data streams, and discover—or let the machine discover—hidden relationships and correlations. Then, we can use these relationships to validate changes to systems or processes.

For example, weather conditions, such as temperature, humidity, and pending storms, affect how assets perform. Understanding what is “normal” is predicated on the kind of process running, the quality of the raw materials, and the quality of the energy delivered by the provider. Seeking correlations between these influencers is not optional anymore; this capability is considered a base requirement for operations and maintenance.

How do you get started? Pick one area, one piece of equipment, or a high-tech process to focus on. Cloud computing offers easy access to business analytic models (see IBM.com/IoT for more information) that you can experiment with. Connecting a data stream is as easy as deploying an app. Let existing models show you correlations you did not know about—explore and expand on these as signposts to early successes.

Recognizing that effective use of data is dependent on an understanding of what you already have, determine where decision-support data lives and bring it all into a single framework. Only then can you move toward more forward-looking possibilities.

Where do you start? Unless you are living under a wet rock, it really does not matter what your role in the enterprise is; we can all see an opportunity. Grab a small piece, and get started.

Reactive to predictive

Technology development is expanding the tools available to increase the effectiveness of maintenance to dramatically improved uptime and equipment availability. Reactive maintenance, which waits for machines and other equipment to break down and then fixes them, is a costly method, affecting production efficiency and manufacturing quality. This practice also has a big impact on increased life-cycle costs, often shortening the useful life of equipment.

Preventive maintenance based on calendar time improves equipment effectiveness. However, lacking a link between equipment use and wear, this method has not proven to be reliable, and it requires a significant commitment of labor resources. Much of the work and materials are overkill. Condition-based maintenance using real-time monitoring to constantly assess the condition of assets can dramatically improve availability and limit downtime. The big next step in maintenance is enabled by IoT technology and cloud computing. Companies identify and correlate patterns in variables that, taken as a whole, affect equipment performance to determine actions that can prevent failures. The application of predictive methods can significantly improve maintenance strategy and the ability to anticipate performance issues and mitigate them before they impact operations and cause unscheduled downtime.

Exploiting asset data

More and more intelligence is built into sensors on equipment every day. Automation systems linked to these intelligent sensors deliver insights into real-time performance data. With the application of Internet of Things technology, these terabytes of data turn into actionable information. The opportunity is for a much clearer fact-based understanding of asset performance and efficiencies to lower maintenance costs, improve production uptime (lower downtime), improve product quality, improve production yield, reduce unplanned downtime, and optimize maintenance labor resources. This data can also be used to justify replacement of existing equipment and verify performance of new production processes and recently installed equipment.

Newer and easier-to-use analytic modeling software is becoming available due to the demands of customers whose appetites are whetted by compelling results and who drive the need for more and more insight into their business operations. Analytic models are bringing high-hanging fruit in reach; maintenance and operational improvement directly affects the bottom line, and that is why large enterprises are so interested in leveraging these technologies.

Exploring potential worth

Data from automation and monitoring systems, leveraged with analytics, monitoring, and reporting, creates the basis for a real-time maintenance program. The potential impact of employing predictive maintenance is significant, as illustrated by a Nucleus Research analysis of potential improvements:

  • Reduction of annual unplanned downtime: 60–90 percent
  • Reduction of excess capacity required to compensate for unplanned downtime: up to 90 percent
  • Scrap or rework reduction: up to 50 percent
  • Asset life extension improving lifetime return on assets: 5–15 percent

Identify and prioritize needs

A valuable analysis is to identify and prioritize your situation considering three factors relative to analytic use cases.

  • Operational and organizational readiness: Are you ready, or do people need more information and training?
  • Business and strategy alignment: Is this in line with your company’s goals and objectives?
  • Risk and return value: For your operations, what is the economic potential?
How real-time maintenance and analytics affect an operation depends on the organizational characteristics
Areas of improvement         Organizational characteristics with highest value return
Asset quality yield improvement from predictive analytics impacting production and manufacturing processes Complex discrete and process manufacturing
Asset quality yield improvement for higher levels of quality of finished goods and services Complex discrete and process manufacturing
Process-driven root-cause detection and diagnosis and prognosis for quick resolution of complex problems High-risk industry, multisite operations
Process-driven predictive tool calibration for improved throughput, uptime, and accuracy to maintain tolerance accuracy Precision manufacturing
Reducing recalls and warranty exposure based on predictive, early alert, field-asset problem determination Competitive markets, costly product development cycles
Asset track and trace to detect and predict asset movement and location (supply-chain management) Collaborative partners for subcomponents, expensive assets, outsourced maintenance
Reducing scrap due to improvements in production process analytics and root-cause analysis High cost of raw materials, fixed cost for processed goods
Early warning and predictive parameter modeling for early and precise problem determination Precision manufacturing
Product service improvements as a result of defect detection and prevention results in customer loyalty Competitive markets, expensive recalls, risk to company reputation
Asset monitoring and analytics for regulatory compliance warranty or recall Highly regulated industry, high cost of noncompliance
About the Author
Mary Bunzel is the general manager of the Manufacturing Industry Solutions Group at Intel Corporation. Previouysly she was with IBM and brings more than 30 years of experience in best practices for manufacturing industries, with a special focus on the automotive, industrial products, and food and pharmaceutical industries. Before joining IBM, Bunzel spent 10 years working for MRO Software (PSDI), where her role was Maximo’s strategic accounts manager for General Mills, J&J, Cargill, ADM, Ford, and General Motors. Bunzel serves as IBM’s voice to the market, to customers, and to analyst groups on the state of the manufacturing market as it relates to Maximo asset management offerings.
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A version of this article originally was published at InTech magazine

What Are the Benefits of Connected Manufacturing?

What Are the Benefits of Connected Manufacturing?

This article was written by David Parrish, global senior director of industrial machinery and components marketing for SAP. | @parrish_denver

More and more customers today are looking for highly customized products. At the same time, manufacturers are under pressure to produce efficiently at mass-production costs. One way organizations can meet this challenge is by integrating business and manufacturing systems with automation technology. Traditionally, these systems have run independently of each other, but the factories of the future will have a fully integrated system from sales orders to manufacturing orders to delivery confirmations. Known as connected manufacturing or Industry 4.0, this integrated approach can help manufacturers operate more efficiently using a variety of data sources from both operations and enterprise systems. More specifically, companies are able to turn massive amounts of data into action by using advanced analytics to identify bottlenecks, troubleshoot issues, understand asset interdependencies, and reduce costs.

To understand the true potential of integrating business and manufacturing systems from the top floor to the shop floor, it is helpful to review the situation many companies operate in today. Typically, traditional shop management processes are manual and time intensive. Getting manufacturing performance data to the top executives is a slow process, subject to human error and interpretation. Often it begins with plant managers creating spreadsheets from system-generated reports. Executives review these spreadsheets at the end of each week and use the data to create visual dashboards for higher-level management. Unfortunately, complicated graphs and spreadsheets do not give enough actionable items to help until after the fact. Another example is shop-floor supervisors physically dispatching job packets. Operators receive a hand-delivered stack of papers with their jobs for the day and verbally report back completion to their supervisors.

It is fairly obvious to most manufacturers that paperless systems improve efficiency by reducing manual work. But imagine what could be accomplished if a company could use technology to create real-time connections among the automated manufacturing floor and all other business systems, both internal and external. Not only that, but what if the data was instantly converted into visuals, so all employees could easily analyze and understand the information?

With information at their fingertips, managers can identify and resolve issues up and down the supply chain to increase efficiencies, improve profitability, and raise customer satisfaction. In fact, the seamless integration of plant information with business systems presents so many opportunities, companies are just scratching the surface of what is possible. Below are a few examples of existing processes being transformed by connected technology:

  • Plant production planning: Smart planning, forecasting, and clear visibility into operations and finances are essential to maximizing plant resources, especially when adding assets from an often dizzying array of mergers or acquisitions. Using an integrated system allows managers to easily assign which plant manufactures which products for a given order and strengthens on-time delivery performance.
  • Employee performance: People on the plant floor get real-time feedback on how their actual work compares to planned output. They can immediately see the value they are contributing to the whole business and the impact their work has on customers.
  • Product traceability: Connected manufacturing systems enable transparency and collaboration across the entire supply network, starting within the four walls of a manufacturing plant and extending across global supply chains.
  • Production warehouse: Connecting the shop floor to other business systems allows decision makers to optimize material movements between warehousing and production. By integrating real-time material availability with real-time manufacturing capacity, days-in-inventory reductions of 15 percent or more are common.
  • Manufacturing accountability: Workers at each production station are now guided by visual displays of standard work instructions, elapsed assembly times, and customer-specific requirements for various features and options. As a result, manufacturing efficiency increases, and production cycle times are compressed significantly.
  • Sourcing: By making strategic sourcing a key component of an overall strategy to cut costs and maintain a competitive edge, companies with connected systems have increased productivity by finding and qualifying new suppliers faster. Additionally, they are able to gather feedback on suppliers from all departments, so they can evaluate a wide range of performance metrics, such as price, quality, and on-time delivery performance.

Real-time, connected manufacturers enjoy many benefits not available to companies still working within a more traditional environment, which typically has misaligned departmental silos, manual processes, and disconnected systems. Putting the right data in the hands of decision makers when they need it allows companies to take immediate action in response to changing market conditions. Companies report more effective communication and consistent oversight when the factory floor and the front and back offices share a single powerful database. Also, sharing information helps encourage the development of ideas or better solutions from all parts of the organization. Finally, integration between the shop floor and the top floor can reduce manufacturing costs by increasing overall equipment effectiveness and minimizing unplanned downtime.

Although there are many practical applications of an integrated technology solution, one of the biggest advantages is that it allows everyone from the machine operator to the CEO to have a voice. Placing the power of information in the hands of all employees and supply-chain partners can create a collaborative environment in which everyone plays an important role in solving problems. In this way, companies can thrive, enjoying a continuous stream of innovative ideas that can quickly become reality.

Cybersecurity risks need to be assessed and mitigated as industrial plants find value in communicating more data internally and externally to improve performance and maintenance. The ISA99 standards on industrial automation and control systems (IACS) security provide a framework for analysis and protection.

About the Author
David Parrish, global senior director of industrial machinery and components marketing for SAP, previously held various product and industry marketing positions with J.D. Edwards, PeopleSoft, and QAD. Parrish has a BS in advertising from the University of Illinois-Urbana, an MBA in transportation management from the University of Colorado-Boulder, and a CPIM from the American Production and Inventory Control Society (APICS).
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A version of this article originally was published at InTech magazine

IoT Is Ready for the Process Industry

IoT Is Ready for the Process Industry

This post was written by Tom Moser, president and CEO of Phillips and Temro Industries.

In today’s competitive business climate, process plants are looking for ways to quickly reduce costs, improve operations, and comply with regulatory requirements. Addressing these challenges with yesterday’s technologies, while practical, often has unsatisfactory results and does not yield the desired competitive advantage. But there is a technology ready for deployment right now that can address many operational challenges, and it is proven in use with more than 5 billion operating hours. This innovation consists of adding wireless sensors to process plants, and then connecting these sensors to internal intranets or to the Internet to create an industrial Internet of Things (IoT) infrastructure. The data from these sensors can then be interpreted and analyzed to help users save energy, improve reliability, and increase throughput. This is not some futuristic vision of the IoT, but is a current reality at many process plants around the globe.

The first step is to identify plant processes or equipment where substantial savings can occur with real-time, continuous information and interpretation. Plant personnel typically have a long wish list of such areas, and suppliers can assist with a study to uncover more. In most cases, countless areas for improvement have been neglected or forgotten because of the high cost, long installation time, and required downtime for wired sensor installations. Now that these negating factors have been eliminated, rapid improvements to plant operations can be made at costs often low enough to be funded by operating budgets.

Installing wireless sensing technologies is quick and low cost, because battery-powered wireless sensors can be brought online in a fraction of the time of a traditional sensor. No wiring is required either for power or for delivery of actionable information to plant personnel. An increasing number of today’s sensors are nonintrusive, further easing installation.

Once this sensing network is established, a combination of smart software and personnel with domain expertise can interpret sensor data. This can be done on site if a plant has the right people, or off site by either corporate engineering or supplier personnel.

For both on-site and off-site analysis, the industrial IoT delivers data to the right personnel without requiring connection to the plant’s real-time control system. This is important, because control system connections require careful vetting and strict procedures, lest plant operation be compromised.

Wireless sensors can be connected directly to plant maintenance management systems or historian databases, and from there to the cloud via secure one-way Ethernet or Internet connections. These clouds can be public, private, or hybrid—in each case providing the required level of data security.

Once the data is received, actionable information can be ascertained and securely delivered to the right people. With this information, plant personnel are empowered to make decisions to immediately improve plant operations.

In some instances, the most pressing need for a process plant is not the bottom line, but rather compliance with health, safety, and environmental regulations. In these instances, the cost of noncompliance can be extremely high, ranging from daily fines to plant shutdowns. As an example, a refinery needed to prevent vapor cloud releases associated with pump failures. It installed wireless, nonintrusive vibration sensors to tell operators which pumps needed service. They now monitor more than 100 pumps at less than the cost of manually checking just a few pumps, and the wireless system has given early warning of three impending pump failures in its first year of operation.

The industrial IoT is here today, being used by hundreds of process plants in thousands of unique applications globally. Wireless sensors have opened up countless new opportunities, and are now able to quickly deliver bottom-line benefits. The question to be asked is this, “What if there was a way to . . . ?”

About the Author
Tom Moser is president and CEO of Phillips and Temro Industries. Previously, Tom worked for 26 years with Emerson Process Management, and he has held several positions, including president of Rosemount, president of Micro Motion, VP of Rosemount Asia Pacific, and VP of Rosemount Europe, Middle East, and Africa. He holds bachelor’s and master’s degrees in mechanical engineering from the University of Minnesota, and an MBA from Duke University.

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A version of this article originally was published at InTech magazine.

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