Smart Grids and the Future of Energy

By now, we've all heard about "smart" electric meters and a "smart" power grid. While some might see the concept as nothing more than a new way for Big Brother to stick his nose in our personal business, others see a natural continuation of technological evolution that will ultimately lead to cleaner, more efficient power systems and lower utility bills.One thing about which most will agree is that our power infrastructure is outdated and inefficient. Composed of a patchwork of technology from different eras, there are portions of the power grid that can be dated back as far as 1890! As our power lines and substations have aged, new technologies have emerged. Why, then, should we be concerned about advancing this technology forward?

Most have probably heard about the “smart” meters power utilities are installing across the nation. As could be expected, there have been some concerns about health and privacy associated with this new technology. The health concerns center around the RF radiation generated by the meters’ communication with a central computer system. The radiation generated is similar to that generated by cell phones or Wi-Fi routers, and there are people who believe that this type of radiation can contribute to cancer and other health problems. Verifiable research thus far has been inconclusive, but since the meters are located outside – unlike phones and routers – and are communicating less than 1% of the time, any potential danger is significantly less than that posed by these other technologies (cellular and Wi-Fi) that most people have willingly accepted. There are others who are concerned about privacy issues. Smart meters are designed to both send and receive information, and some citizens are concerned about the meta-information that power utilities will now have access to as a result of smart meters. For instance, metered data can be used to learn about the kinds of devices individuals use in their homes, to map movements of individuals from one room to another, or learn about when people are not home and for how long. Privacy has become a sensitive issue with the advent of “green” technology, and it is not an insignificant concern. In truth, however, with the progress made in satellite imagery, the implementation of public cameras and face-recognition technology, the vast databases of personal phone calls and emails retained by the NSA, and the numerous other intrusions into our personal lives, smart meters may in fact be the very least of our privacy concerns.

How will smart grids work? When we move beyond the perceived dangers, there are a number of very real benefits proposed by smart grid technology. A smart grid can diagnose problems and automate solutions. For example, power outages can be reported automatically as soon as they occur. A work order can then be automatically generated and assigned to the nearest technician. In fact, some problems can be discovered and corrected before an outage even occurs. This could significantly reduce the cost of system maintenance and increase service recovery time in the event of an outage. That mean better customer service and lower cost. Usage data collected by smart meters can also be used to help consumers understand their own usage patterns and find ways to reduce energy consumption and lower their bills. That means lower bills and energy conservation. A smart power grid will be more efficient, more cost-effective, and less wasteful. There are so many benefits to employing smart grid technology that there is really no reason to expect the power grid to simply stop evolving and maintain the status quo.  If you consider the advances already made in the last century, many of which were accompanied by health concerns and concerns over property rights, the burgeoning smart grid is really nothing more than a continuation of the progress we have already made. If you were not concerned about the waste created by power plants or the radiation generated by the high voltage lines running through nearly every town, it doesn’t make much sense to be concerned about today’s advances, particularly in light of the fact that they are likely to lead to a cleaner, safer electrical infrastructure. New advances will happen, and the technology that enables these advances will continue to evolve as well. If a person wants to draw a line in the sand and say “this far and no further”, it could be said that the line should have been drawn long ago. Many will continue to maintain that there is no point in using electricity – or doing anything for that matter – if we are not interested in doing it to the best of our ability.

SCADA in the Cloud

One of today's hottest buzzwords in the world of computing and information technology is 'cloud computing'. With many large and well-known companies adopting cloud-computing concepts, it is becoming clear that this may be something more than a passing fad.

As industrial enterprises seek greater opportunities for data management and integration, cloud-based solutions are one of many on the table. As with any new innovation, there are certainly pros and cons, and when dealing with something like process control, there can be some very real concerns.

What is the Cloud?

First, let's take a moment to define exactly what we are discussing. What exactly is "cloud computing"? In very simple terms, cloud computing involves utilizing a number of different technologies to achieve a system of sharing or restricting access to a particular collection of resources. In application, cloud computing involves networking large groups of remote servers to allow for the centralized storage of and online access to data.

Cloud computing has already proven to be useful enough to justify millions of dollars of capital investment from very successful companies like Microsoft and Google. Smaller companies are already reaping benefits as well. Things get a bit more difficult, however, when considering the notion of remotely monitoring and controlling sensitive devices and proprietary processes in cloud-based systems. After all, a large part of our infrastructure - including oil pipelines, power utilities, water treatment plants and mass transit systems - is controlled by SCADA software.

Are we comfortable putting these processes in something as ubiquitous as the cloud? As the introduction of this article suggests, there are many perceived benefits and risks to putting SCADA systems in the cloud.

Many of the perceived risks revolve around the sensitive data that could be available to malicious parties. Additionally, there are concerns that the actual operation of these essential systems could be vulnerable to attack, which could be devastating. Many of these concerns are more closely related to what information should be included in the cloud rather than whether or not the cloud itself is secure.

While security concerns are certainly valid - as they have always been - there are some undeniable befits to cloud-based SCADA, including:

• More cost-effective subscription-based pricing for smaller companies that may not otherwise be able to afford a SCADA system
• Enhanced scalability for large or growing organizations
• Lower cost of implementation and maintenance
• Greater accessibility
• Greater ability to collaborate
• Easy and affordable upgrades or add-ons

Many other risks and benefits can be listed, but the question is not really about whether or not cloud-based SCADA is a good idea – it is about whether cloud-based SCADA is a good idea for you and your organization. The major questions now revolve around how much control should be distributed through the cloud. Many engineers will insist that control be limited to local PLCs, and cloud-based information should be read-only. Others may suggest that control should be distributed as well.

There are no right or wrong answers at this point. It is fairly clear that the perceived benefits of cloud-based SCADA will outweigh the perceived risks - and probably rightly so. There is no reason that SCADA systems should not evolve to take advantage of the latest technology as they always had.

As smart devices and sensors evolve and become more affordable, more businesses are going to want to automate their processes. The subscription-based pricing of hosted SCADA software will make it accessible to organizations that otherwise may have been unable to afford it. This will allow smaller companies to begin to compete in the marketplace in ways that were impossible before. The industrial workplace is changing worldwide, and cloud-based SCADA is one way that change is being realized.

Information Modeling as a Tool for Collaboration

In the spirit of the upcoming holiday season, let’s take a moment to examine one of the greatest and most appreciable qualities of a healthy organization: collaboration. In a world so full of information, where we are all so busy and so pressed for time, it seems collaboration has become something done more out of necessity than out of a desire for quality and efficiency.

Some of this reality may be due to the fact that there simply are no good tools for collaboration in the modern workplace. Sure, we have email and teleconferencing, web meetings and text messages – but for all of our technology, our endless need to compartmentalize and segment our business processes has left us no closer to a model of organic collaboration than we were in the past.

With relevant information stored in separate silos, decision-makers are still forced to rely on reports and statistics compiled from historical data and interpreted to support a specific agenda. There has really been no truly organic means analyzing real-time data alongside the historical data. Likewise, the available tools for integrating data from separate systems are limited in terms of their ability to create a real-time context and to display the appropriate data to decision-makers at the speed with which decisions must often be made.

While these tools may be useful for looking back and analyzing what has happened, it is another matter altogether when trying to look forward to make plans or predict outcomes.

Information Modeling

One of the ways this challenge can be overcome is by using an information model to organize and structure your organization’s data in a way that provides context and clarity in real time. Information modeling allows assets to be associated with all relevant information – regardless of where that information may reside.

For instance, a motor on your plant floor can have live data related to its RPM, temperature, throughput, or other process data – as well as a commission date, a maintenance schedule, troubleshooting documents and training videos. Properties of this motor can also include OEE (Overall Equipment Efficiency), Net Asset Value, or other performance and resource planning metrics. Some of this data may be coming from PLCs, some from databases like SQL Server, some from user input, and other data is coming from programmed calculations. In this situation, it is not important how this data is generated or where it is stored. What is important is that this data can be visualized at any time in whatever way suits your collaborative needs.

There are a number of different tools that can be used to create an information model for your organization. A few things to consider when choosing an information modeling tool:

• Does the modeling software take into account both real-time AND historical data?
• Does the modeling software allow you to include ALL relevant information from every source?
• Is your modeled data logged in a relational database like SQL Server so it can be queried if additional information is needed?
• Does your modeling software provide the tools you need to visualize your data in a useful way that supports decision-making?

Before you jump into a new software product and a new data management system, do some homework. As with everything there are pros and cons to the different products available.

Learn more about information modeling in modern software systems, visit: http://scada.com

How is the Automotive Industry Handling the New Industrial Revolution?

Bill Gates is alleged to have once quipped that “If GM had kept up with technology like the computer industry has, we would all be driving $25 cars that got 1,000 MPG.” Even though the authenticity of this quote is questionable, it has been circulated throughout the internet for years because there is something about the sentiment that rings true to us. It certainly does not seem that the automotive industry has kept up with advancing technology the way that the computer industry has.

This may be due in part to the manufacturing infrastructure that has evolved over the years. Making sweeping upgrades to equipment and/or processes seems a very expensive and risky proposition. When you couple this with the fact that many automobile manufacturers today struggle to find enough demand for their current supply, it is easy to understand why keeping up with the latest technology isn’t always a top priority.

The problem with this reluctance, though, is that automobiles are not inexpensive consumables that people buy casually. Customers expect vehicles to come with the highest standards of safety and efficiency. Customers expect the latest technology possible. How can manufacturers keep up with this demand for innovation without changing their processes?

It seems that some manufacturers are beginning to embrace the ways of the modern industrial world, and are finding ways to align their business models with the current wave of interconnectivity and streamlined automation.

Honda Manufacturing of Alabama

Honda’s largest light truck production facility in the world – a 3.7 million square foot plant – was faced with a problem all too common to large manufacturing facilities. Over the years, a number of different automation systems were introduced to help streamline production. With operations including blanking, stamping, welding, painting, injection molding, and many other processes involved in producing up to 360,000 vehicles and engines per year, it is not surprising that they found themselves struggling to integrate PLCs from multiple manufacturers, multiple MES systems, analytic systems, and database software from different vendors.

Of course, on top of these legacy systems, Honda continued to layer an array of smart devices on the plant floor and embed IT devices in plant equipment. The complexity introduced by this array of automation systems turned out to be slowing down the operations they were intended to streamline.

After reorganizing their business structure to merge IT and plant floor operations into a single department, Honda proceeded to deploy a new automation software platform that enabled them to bring together PLC data with the data coming from MES and ERP systems into a common interface that allowed the entire enterprise to be managed through a single system. This also allowed Honda to manage and analyze much larger data sets that revealed new opportunities for further optimization. While this reorganization required a significant investment of resources, they were able realize benefits immediately, and ultimately positioned themselves to maintain a competitive edge through the next decade or more.

Ford Motor Co.

Ford Motor Company operates a global network of manufacturing operations, and have had difficulty when trying to promote collaboration and share best practices between their various plants. They found a solution using technology based on the Google Earth infrastructure.

Ford was able to develop a cloud-based application that stores 2D and 3D representations of Ford’s global manufacturing facilities, and allows users to navigate through these virtual environments, place pins, and upload video, images and documents to these pins that are shared throughout Ford’s global operations. Engineers and operators can share information about current plant conditions and procedures, which can be accessed in real time from anywhere in the world. The accumulated data can be used for training or to update standard procedures. By creating a global collaborative tool, Ford has created a means of ensuring that each and every one of their employees has the latest, most accurate information on how to best perform a particular task or how to avoid a problem that was encountered elsewhere.

We will have to see in coming years whether or not these innovations will lead to improved market performance for either of these manufacturers, but in the meantime it is probably safe to expect other companies to follow suit. With the advances in manufacturing technologies and machine-to-machine communication, it is becoming very difficult to remain competitive without playing by the same rules as everyone else. Industrial technology has advanced to the point that we are experiencing what people refer to as a new industrial era – or Industry 4.0. Reluctance is no longer a viable option.

To learn more about innovations in manufacturing software technology, visit: http://scada.com

Finding Big Data Opportunities in Industrial Automation

Here we are in the world of Big Data and all of its possibilities. Just look at all the data we have available to us: production, maintenance, distribution, personnel, finances – real-time, historical and predictive. There is more data being collected more quickly and from more sources than ever before. We are swimming in it.

So, now what? Now that we’ve gathered all of this data, what does it mean to us? Personally, having reams of integers, floats, strings and timestamps in my hands doesn’t make me feel any smarter. As the old adage goes: Data is not information. Data without context offers no insight. Data without structure reveals no opportunities. How do we get from data to information? How do we get from information to knowledge? And how do we get from knowledge to action?

Finding the Anomalies

The US Department of Defense employs a process known as Activity-Based Intelligence (ABI) to find useful details in large sets of data. For example, in 2013, when two bombs exploded near the finish line of the Boston Marathon, investigators immediately had at their disposal hundreds of hours of surveillance footage, cell phone photos, and time-stamped video from dozens of angles. To manually review all of this media would require thousands of man-hours – time that is obviously not available in a situation like this.

To make use of this constellation of data, investigators were forced to find a way of automating the investigation. They decided to establish a specific set of details they wanted to locate in all of these photos and videos. Namely, they were looking for any individuals at the scene of the bombing who were not running away or looked unafraid. The behavior recognition technology existed, so it was a simple matter to enter a set of variables into a program and to let the software review the footage in an effort to find the activity that matched these variables. Soon, two suspects were revealed.

While it would have been nearly impossible for human analysts to review all of this footage in a timely fashion, investigators discovered that Big Data could in fact be very useful if combined with a mechanism to compare and contrast the thousands of data points being reviewed.

A similar technique is now being employed in cancer research. A so-called “Big Mechanism” has been created to review the vast and complex medical records of cancer patients that have been established over the years to find overlapping patterns or consistencies that can lead to a new understanding of root causes or precipitating circumstances. By automating the research, we are now able to analyze data sets of much greater size and complexity than would be possible using only human analysts.

Can Similar Techniques be Employed in Industrial Automation?

Today’s industrial enterprises find themselves in a situation similar to those described above. Huge amounts of data are being recorded and opportunities for improvement are known to exist, but how do we know what to look for and how do we find it? The same sort of ABI employed by the DoD may well have a place in the commercial world.

If we can review our historical process data to define the circumstances surrounding certain conditions (unplanned downtime, spikes in energy consumption, etc.), we may be able to recognize repeated patterns or anomalous activity related to these specific circumstances, thereby enabling us to take action to correct the situation before it happens again. By finding the data that stands out from the rest, detailing the characteristics of that data, and looking for those characteristics elsewhere, we may be able to pinpoint causal relationships that were previously obscure or misleading.

On the flipside, the same techniques can be employed to define the circumstances surrounding periods of extended productivity or energy efficiency. The same techniques used to discern the cause of deficiencies can be used to optimize asset performance and improve the quality and efficiency of our processes.

By creating analytic mechanisms aligned with the principles of ABI, we are able to create a safer, more efficient, more productive work environment. Of course, some of this runs counter to the way most of us are programmed to think. We tend to put more stock in consistent, reliable information, while discounting the anomalies. ABI encourages us to find the anomalies and focus on them.

The key to navigating the world of Big Data may not lie in the massive set of data, but in the tiny subset of data that teaches us about the abnormalities or anomalies we find. Look for the data points that stand out from the rest and ask yourself why. Consider the circumstances surrounding the collection of that data; can we map certain plant floor conditions to specific results?

Thus far, the Big Data movement has been a combination of hype and optimism, with very little practical value in daily operations. Some companies are finding ways to take advantage of the opportunities, while others have fallen behind.

Can you find the opportunities?

A Case for Mobile Devices in Automation

One of the fastest-growing and most widespread trends in the HMI and SCADA software realms is that of mobility. Namely, how can we – or should we – take advantage of mobile devices in automated work environments?

There are those who have concerns about security. Are mobile devices secure enough to allow them to access sensitive process-related data? And if so, how much access should they have? Read/Write access? Read only? Should they be limited to a certain subset of data? And, if so, how can our control user access to ensure that users only access what they are authorized to see? Will these devices open holes in the network that allow malicious applications access to sensitive controls?

While some of the security concerns are certainly valid, the benefits of mobile devices are impossible to overlook, and the truth is that many of the security concerns are not inherent in the devices themselves, but in the way that the HMI/SCADA system and network infrastructure are configured.

Consider some of the pains that mobile devices can help eliminate:

• A field operator must call the control room to ask for the reading on certain piece of equipment (i.e. valve, switch) he/she is looking at or manipulating.
   
• A field operator must call the control room to confirm whether a certain piece equipment has truly been shut down for maintenance work because it sounds like it is still running.
   
• A field technician dangerously works on a live line because the control room has shut down the wrong line!
   
• A field operator must call the control room to describe equipment schematics because he/she has no access to an HMI or drawings on the floor at that moment.
   
• A field operator must call the control room to pull out the manual for a piece of equipment because the panel on the one he/she is looking at is different from the others he/she is used to.
   
• A field operator must describe over the radio what he/she is seeing - lights on a panel, leaks, etc.
   
• An operator must take a check-list out to the field, return to the control room and enter the results into a form or spreadsheet, or into the control HMI.
   
• Constant calling back and forth between field and control room when testing or calibrating a measurement or control element.

A mobile device can be used to remotely monitor processes and equipment, view drawings or manuals, review an online checklist, enter information into a form, even adding value as a tool for remote collaboration.

When properly configured and combined with role-based user access control, a wide array of new possibilities are revealed. The time saved in the field can now be used to perform other tasks or implement programs for optimization. A safer, more productive workforce is a very real benefit, and that's not something that business owners or managers will take lightly.

Are mobile devices a part of your business model? If not, it may be time to review your processes and make room for the future.  

The Integrated Enterprise - Are We Ready?

There are many barriers to change in a commercial enterprise, and most of them start with a dollar sign. You are comfortable with what you’re doing. Your staff is comfortable. Sure, there may be some missed opportunities, but perfection is unrealistic. To implement enterprise-wide changes to something like your data management strategy would require cooperation across multiple departments, absorb numerous man-hours in implementation, and who can say how long it will take for all parties to get used to the new strategy and work with a level of comfort they already feel today? Is it worth it? How long will it take to recover the investment?

There are many legitimate questions to ask when considering whether or not to move toward an integrated data management strategy. How do we calculate the true cost of making such a change? A question that is very rarely asked is: What is the true cost of not making such a change?

First, let’s consider some of the reasons in favor of data integration.

Inconsistent data

One of the problems addressed by data integration is inconsistency between data on the plant floor and the business data further upstairs. Depending on the type of business, different departments typically have different goals and criteria for success. The plant floor supervisor wants to know where his products are; the executive upstairs wants to know how much his products are worth. Here is a case where we have different people querying for different bits of information about the same asset. Over time, the different goals and process definitions have led to departments using the same terms to describe different things, and different terms to describe the same things. This barrier to departmental collaboration in the manufacturing industry, for example, has led to the development of standards like ISA 95 to help facilitate the integration of manufacturing systems with business systems.


Redundant data

Another common condition is the tendency for different departments or divisions to have different ways of recording information about the same things. It is not at all unusual for large organizations to have multiple records of the same asset. For instance, if we imagine a particular production unit from the perspective of the plant floor operator, he will need to have information about where it is in the production process, its quality, the personnel involved in its production and testing, and when it will be shipping. At the same time, a manager will want to have information about how much it cost to produce this unit, how many units will be produced today, and how much we will get for it. We now have a situation where we are capturing and recording separate sets of data about the same thing.


Fewer Human Resources

This one seems obvious, but it a significant difference-maker when you analyze your bottom line. Making it easier to find needed data will allow personnel to spend more time focusing on other aspects of their jobs. It will allow for faster decisions and more immediate response to abnormal conditions. Your plant floor supervisor won’t have to make that call upstairs to find out why today’s production schedule has changed, or log in to a separate system to find out when a piece of equipment was last inspected. And the manager upstairs won’t have to call downstairs to find out why we are behind schedule today, or what happened to that shipment that was supposed to go out. Having the ability to quickly assess a situation leads to better-informed decisions made more quickly and with more immediate results.


Reduced Risk

While we are on the topic of making informed decisions more quickly, this is a good time to consider the way that decisions are currently made in many enterprises. When a decision needs to be made quickly, and the data that could support that decision is not available as quickly as the decision is needed, owners and executives are left to make decisions based on intuition. Studies have suggested that about 80% of decisions are made this way. It may work and it may not. Having the right information when and where it is needed can significantly reduce the risk involved in the decision-making process.

There are many additional benefits that can be attributed to data integration. New business opportunities can be revealed. New calculations can be used to improve efficiency and coordinate processes. Improve inventory management, energy consumption, supply chain scheduling, etc. Whether you choose to use a system of data virtualization to integrate key data from different divisions, a system of data federation to consolidate all enterprise data, or opt for a complete data integration solution that re-engineers your entire data system, the benefits are very real and yes, so is the cost. The cost, however, is a short-term loss for a long-term gain; a temporary pain for permanent growth.

So, to revisit the topic of this article: Are we ready for the integrated enterprise? The answer is irrelevant. Those who are ready will continue to prosper. Those who are not will lose the ability to compete, and will ultimately have to get ready or get out of the way.

For more information on how you can integrate and visualize your business's data, visit: www.scada.com