3 Ways to Use Information Modeling for Continual Improvement in Your Enterprise


The concept of continual improvement has been a regular feature of modern manufacturing enterprises. Its gaining favor now in different circles, and for good reason. Continually making small incremental improvements to business processes has proven time and again to have a positive impact on production quality, efficiency, and safety. What’s not as well known, however, is how much more effective continual improvement programs can be when used in conjunction with an information model.

An information model can be thought of essentially as a virtual representation of your enterprise, and it provides the organizational and relational structure of your enterprise’s data. Providing context and organization to the raw data is the first step in turning it into actionable information.

Data included in your information model can be drawn from nearly any source. Include data from databases, web services, sensors, PLCs , calculations, real-time user input, or data from other enterprise applications like ERP or MES systems – essentially anything of relevance that can add value and support decision-making.

By modeling your information in this way and providing context to your real-time data, you can visualize your asset management data alongside your process control data, or your maintenance data alongside procurement data. Any data relevant to your business processes is now accessible to your visualization system, and opportunities for optimization become much more apparent when data is presented in context.

For instance, you can visualize how a particular motor’s production throughput is affected by changes in the Overall Equipment Effectiveness (OEE). You can see how the OEE is affected by maintenance operations. The sort of real-time situational awareness enabled by information modeling reveals new opportunities to lower maintenance and operation costs by maximizing asset performance. By defining the relationships in your information model, the data that you visualize becomes much more understandable and actionable.

Another – and perhaps greater – benefit of information modeling is the ability to track the results of incremental changes in real-time across multiple channels.  This allows for faster analysis and greater collaboration. It also becomes much easier to establish new standards, as information entered into your information model is immediately accessible to all who use it. Also, additional media – like videos and manuals – can be included in your model to ensure that all personnel have immediate access to the latest standards and best practices.

There are many ways information modeling can help your continual improvement efforts. Here are three categories of benefits many business owners are already seeing.

1.      Analytics, Reporting, and Condition-Based Task Automation

If managed through the right software system, one of the great benefits of information modeling is that your data is normalized and available in a consistent format, regardless of where the raw data was generated. This presents tremendous opportunities for data analysis, reporting, and task automation. It allows machine-to-machine communication, business-to-machine communication, and business-to business communication. An event in one device or location can automatically trigger an action in another device or location. Automated reports can include data from multiple sources. This is the essence of the Internet of Things (IoT) – the interconnection of all of assets and their associated data.

This also presents opportunities for improvement maintenance operations, as machines can generate their own work requests or alert personnel of potential problems. The possibilities are truly endless when we free ourselves from the data silos many of us struggle to integrate daily.

2.      Data Mining and Activity-Based Intelligence

The US Department of Defense employs a process known as Activity-Based Intelligence (ABI) to find useful details in large sets of data. The process involves creating an automated mechanism to sift through large sets of data in search of anomalies.

Today’s industrial enterprises are finding ways to employ similar techniques. 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 is finding 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 act 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.

3.      Repeatable and Scalable

As you make the changes that will lead to a more efficient, more productive, and safer business, these changes become part of your information model.

Your information model not only helps you identify opportunities for improvement and publicize updated standards and procedures, but also gives you a means for endless repetition and growth. Your information model is progressive; it can always be modified or expanded. As you make successful optimizations, any changes made to your information model can be easily repeated for any other relevant processes. You are also able to expand your model by adding new locations, new assets, new process cells – whatever it is that you have optimized about your model can be repeated or extended indefinitely.

Excerpted from the whitepaper “Continual Improvement with Status”, downloaded at www.scada.com.

4 Ways Mobile Devices Have Transformed Remote Monitoring and Process Control


Mobile devices have changed many things about the way we live and work today. They’ve changed the way we interact with each other, consume new media, purchase goods and services – they have become essential lifestyle accessories in a relatively short period of time. This is true not only for individuals, but entire industries have been impacted in a significant way.

With that in mind, here’s a look at 4 ways in which mobile devices are changing remote monitoring and process control.

Remote Device Monitoring

Mobile devices can be used as portable HMIs (Human Machine Interfaces) to monitor remote equipment in the same way that standard HMIs are used. Field operators can quickly and easily assess the current conditions of a process or piece of equipment without being tied to a workstation.

This can be particularly useful for checking the system-wide effects of repairs or configurations that are made to field equipment, rather than manually visiting each piece of equipment to take measurements or waiting until someone in the control room lets him/her know about any potential problems or abnormalities.

There may also be situations in which a problem can be diagnosed and corrected without even visiting the site. By giving field operators and technicians the ability to access real-time data from wherever they may be, it may possible to eliminate any travel time or expense, freeing the operator or technician to work on other tasks. This may also eliminate the need for the technician to call back to the control room for updated information. This means the control room operator now has more time as well.


Viewing Documents and Other Media

In addition to monitoring and controlling processes and equipment, mobile devices can also serve as a sort of repository for useful information, providing a handy reference for materials that would ordinarily fill several books and would be nearly impossible to carry around over the course of a work day.

New workers can reference training materials like manuals, pictures and videos. Use tablets and smartphones to access safety guidelines or troubleshooting procedures. View schematics and diagrams.  Review incident reports or outstanding work orders.

If you think of mobile devices as nothing more than a portable library of relevant media, this use alone is enough to justify the investment.


Filling out Forms or Checklists

Operators and technicians frequently have a need to add information to a database regarding certain tasks performed – or simply as part of their day-to-day responsibilities. Whether performing inspections, completing service orders, updating personnel files, or any number of other tasks, mobile devices can save employees a tremendous amount of time by allowing them to perform these tasks from anywhere at any time.


Field technicians can update the control system instantaneously from the field – without having to return to the control room to fill out a form or deliver the results to a control room operator over the phone.  It’s not hard to imagine a scenario where a technician in the field, several miles from any control room, can use a single device to read a procedural document, review a checklist, enter relevant information into a form, then check to confirm that the information was entered completely and accurately – without any unnecessary travel time or phone calls.



One of the most profound applications of mobile devices is as a tool for instant collaboration. By allowing continuous access to live process data, personnel from different departments can collaborate and make decisions with up-to-date and accurate information at their fingertips.

Mobile devices can be used to document best practices by uploading pictures or videos of particular procedures and allowing these items to be reviewed by workers at other locations in other facilities. Smartphones and tablets allow personnel to access rich media at any time as a means of conveying a certain set of information to relevant parties. Use displays of real time and historical data in meetings or presentations. Mobile devices allow off-site personnel to participate in real-time activities with on-site personnel. Many possibilities are introduced by mobile technology.

Excerpted from the whitepaper “The Benefits of Data Mobility”, downloaded at www.scada.com.

The History and Evolution of Data Visualization


Data visualization is a very old idea – ancient in fact. Stretching back to the very beginning of human history, we recognize that actual observed data was used to generate everything from star charts to maps. These ancient visualizations were also very integral to the lives of our ancestors, as they were used to plan essential activities like planting food or hunting.

Figure 1 – This Egyptian star chart was found in the tomb of Ramses VI (reign 1145 BC to 1137 BC). This Egyptian star chart was found in the tomb of Ramses VI (reign 1145 BC to 1137 BC)

Star charts were common and widespread throughout the ancient world, and like all historical data visualizations, used recorded data from the past to make predictions about the future. The same could be said about all of the wonderful, detailed maps that were created and then used to navigate our ancestors through periods of colonization in the past. Observed data was recorded and then used to direct future activity. This same notion carried through all the way to the modern world, when in the late 18th Century new types of historical data visualization were created by Joseph Priestly and William Playfair. Priestly is credited with creating the timeline chart, while Playfair invented numerous types of graphic displays to visually depict social and economic data: introducing in 1786 the line, area, and bar chart, then 15 years later the pie chart and circle graph.

These types of visualization are still very commonly used today.

dataviz.pngFigure 2 – This trade-balance time-series chart was published by William Playfair in 1786.

Again, diagrams of this sort used historical data to direct actions occurring presently or in the future.

Today – maybe more than ever – we still value charts, graphs and other forms of data visualization that allow us cognitively assess data in a way that appeals to our senses rather than our intellect.
Excerpted from the whitepaper “Real-Time Data Visualization Essentials”, downloaded at www.scada.com.

3 Things to Consider Before Choosing an IoT Platform for your Business


Like many others, you may be considering ways to leverage new IoT technology to advance your business. Whether that means buying new sensors, servers, routers, or other devices – that depends on your goals and expectations. No matter what you envision, though, you are very likely to need some sort of software platform to enable it. Your software is what will transform your operational data into meaningful information, and your software will provide the interfaces your staff will use to interact with the information provided. Ideally, your software platform will provide many other benefits as well, including an ability to archive data, a way to automate certain tasks and enforce rules, and an ability to be customized and/or scaled to meet the needs of your growing business.

How do You Start Your Search?

Before selecting a software platform, it’s good to start with a clear idea of your needs, expectations, and goals. Then, when evaluating different platforms, see how they measure up against your checklist. This won’t necessarily help you choose the right platform, but it can certainly help you identify the wrong ones.

There are countless things to consider if you want to be rigorous to the point of decision paralysis, but if you’re eager to move forward, here are 3 important things to consider:

Think About Security

Every organization has a particular structure that must be maintained. Staff members need to have access to certain information to do their jobs and nothing more. This is not just a matter of security, but simple efficacy. There is no reason to burden someone’s mind with information that has no impact on their personal responsibilities within the organization.

It’s important that your software platform provides a means of managing user access. A maintenance technician logging in should not see the same information as a C-level executive. The technician does not need to see a graph depicting recent trends in discretionary spending any more than the executive needs to see a list of open work orders.

Of course, this should not be a matter of simply directing a certain user to a certain dashboard. The system should include the ability to completely lock down certain sets of information so that they cannot under any circumstances be accessed by another user.

Think About Your Existing Systems

Is this new system going to completely replace all your existing management systems? Or is it being installed as a supplement to what’s already in place? It may be possible to enhance and add value to your existing systems if done correctly. Will the new system communicate with your old systems and devices? Will it be read-only or bi-directional?

Unless you want to do a full replacement of your current systems, there will be many questions to ask about how all of these moving parts will fit together.


Think About the Future

Implementing your new IoT system will require some significant investment – both in resources and time. It’s important that the work done today doesn’t need to undone tomorrow when your work practices or business processes change. Ensure that the system you put in place today can be extended or modified as needed.

Assuming everything goes according to plan, it won’t be long before you’re thinking about expanding. Make sure your IoT software system doesn’t handcuff you.

Excerpted from the whitepaper “Choosing the Right IoT Platform”, downloaded at www.scada.com.

Kaizen and the Philosophy of Continual Improvement


One of the mostly well-known and widely used philosophies of continual improvement originated in Japan. It is known by the name, kaizen, which translates approximately to “good change”. Kaizen has been employed in a wide range of industries – healthcare, banking, psychotherapy, government, and many others. In business, kaizen typically refers to activities that continually improve all business functions and involve all employees.

Kaizen is frequently used to optimize purchasing, logistics, and supply chain processes, and has been employed in lean manufacturing processes to help eliminate waste. Kaizen was first used by Japanese businesses following World War II, and has since spread throughout the world and been implemented in environments outside of business and productivity.

Kaizen places a strong emphasis on employee feedback, encouraging employees at every level to apply the scientific method in learning how to spot and eliminate waste in business processes. Kaizen can be applied in a very small, personalized way, or it can apply to larger processes that involve groups of employees. In a very general way, the Kaizen methodology can be understood as:

  1. Discovering opportunities for small adjustments based on process data and customer feedback
  2. Implementing these small changes incrementally
  3. Monitoring the results of each individual adjustment for a certain period of time
  4. Using the new data to make adjustments
  5. Defining the results of successful adjustments as standards, and using these standards as baselines for additional improvements
  6. Repeating this cycle indefinitely


The kaizen philosophy aims to improve process efficiency, quality, and safety by making it easier for employees to do their jobs well and with confidence – rather than expecting them to work harder through incentives or fear of replacement.

Improvements made using the kaizen philosophy are typically on a much smaller scale than those found in the “command and control” improvement programs popularized in the mid-twentieth century.

This system of incrementally improving operations is also known the Shewhart Cycle, Deming Cycle, or PDCA (Plan-Do-Check-Act).

Similar ideas are investigated in the realms of Organizational Development (OD) or Business Process Improvement (BPI). The general intent of all of these philosophies is the same: to maximize the value of all available material, personal, and intellectual assets and to improve business processes by making use of resources that are already available.

Like the methods outlined above, other popular methods like Six Sigma, Lean, and Total Quality Management emphasize employee involvement and collaboration, standardizing processes, and reducing variations, defects and cycle times.

Excerpted from the whitepaper “Continual Improvement with Status”, downloaded at www.scada.com.

4 Common Obstacles Between Your Enterprise and the IoT



It should come as no surprise that most companies today have some sort of IoT initiative being discussed, planned, or developed – if not already implemented. And this phenomenon is global and completely horizontal. The early adopters of IoT are already seeing positive returns, and the march of progress is overwhelming if not inevitable.

Why Aren’t We All There Yet?

For those still planning their IoT initiatives and smoothing out the details, there are several barriers that can get in the way. Some of the most commonly cited in surveys include: security concerns, difficulty quantifying ROI to CEOs, concerns about compatibility with existing data systems, and concerns about the technical skills of the staff to implement such strategies.

Obstacle 1 – Increased Exposure of Data/Information Security

As could be expected, security is the almost always biggest concern in most organizations. With the World Wide Web as an example, people today are fully aware of the dangers inherent in transmitting data between nodes on a network. With many of these organizations working with key proprietary operational data that could prove advantageous to a competitor if exposed, the concern is very understandable.

Obstacle 2 – Proving ROI/Making the Business Case

This is a classic example of not knowing what you don’t know. Without an established example of how similar initiatives have impacted your organization in the past – or even how similarly sized and structured organizations have been impacted – it can be very difficult to demonstrate in a tangible way exactly how these efforts will impact the bottom line. Without being able to make the business case, it will be difficult for executives to sign off any new initiatives. This is likely why larger organizations ($5+ billion in annual revenue) are much more likely to have already implemented IoT initiatives, while smaller organizations are still in the planning phase.

Obstacle 3 – Interoperability with Current Infrastructure/Systems

Nobody likes to start over, and many of the executives surveyed are dealing with organizations who have made enormous investments in the technology they are currently using. The notion of a “rip and replace” type of implementation is not very appealing. The cost is not only related to the downtime incurred in these cases, but the wasted cost associated with the expensive equipment and software systems that are being cast aside. In most cases, to gain any traction at all a proposed IoT initiative will have to work with the systems that are already in place – not replace them.

Obstacle 4 – Finding the Right Staff/Skill Sets for IoT Strategy and Implementation

With the IoT still being a fairly young concept, many organizations are concerned that they lack the technical expertise needed to properly plan and implement an IoT initiative. There are many discussions taking place about how much can be handled by internal staff and how much may need to be out-sourced. Without confidence in their internal capabilities, it is also difficult to know whether they even have a valid strategy or understanding of the possibilities. Again, this is a case where larger organizations with larger pools of talent have an advantage.

There are some valid concerns, and not all of them lend themselves to simple solutions. In truth, many of the solutions will vary from one organization to the next. However, in many cases the solutions could be as simple as just choosing the right software platform. Finding a platform that eases your concerns about interoperability can also help ease your concerns about whether your staff can handle the change, as there will be no need to replace equipment. Likewise, a platform that can be integrated seamlessly into your current operations to help improve efficiency and implement optimization strategies will also make it much easier to demonstrate ROI.

Excerpted from the whitepaper “Choosing the Right IoT Platform”, downloaded at www.scada.com.

Is the Internet of Things Really Happening?

Over the last few years there has been much speculation about the inevitable growth of the Internet of Things (or Internet of Everything). Forecasts have suggested anywhere from 30 to 50 billion devices will be connected by 2020. Cisco has estimated that the global IoT ecosystem will have a value of $14.4 trillion by 2022, and IDC has projected yearly IoT market revenue to increase to $1.7 trillion by 2020.

Here we are now in 2016, a few years into the future they were talking about back then, and it may be a good time to take a look the current state of the IoT and see how it measures up to all of these lofty expectations. Are people really embracing IoT technology at this rate? Is this money really being invested?


Connected Devices

First, let’s take a look at the number of connected devices. If we flash back to 2013, we find that Gartner released a report entitled “Forecast: The Internet of Things, Worldwide, 2013”. In this report, they predicted that the IoT will include 26 billion connected devices by 2020. Two years later, Gartner reported a total of 4.9 billion connected devices at the end of 2015, up from 3.8 billion in 2014. Gartner also revised their 2020 estimate, anticipating 20.7 billion connected devices by 2020, a decrease of 5.3 billion (20.4%) from their 2013 estimate. (It should be noted here that Cisco continues to anticipate as many as 50 billion by 2020).

So, according to Gartner, IoT adoption has not proceeded at the rate they had anticipated at the end of 2013.

One reason for the slower-than-expected growth is the difficulty faced when trying to implement IoT technology. In fact, Gartner anticipates that through 2018, 75% of IoT projects will take up to twice as long as planned.

Value of the IoT

Now, let’s consider the monetary value of the IoT and how that number has progressed. Cisco initially projected a value of $14.4 trillion by 2022. Within two years Cisco had increased this number to $19 trillion.


This highlights an interesting fact. Even though fewer connected devices are expected by this date, the total value of these devices and the underlying network is expected to be greater than it was when more devices were expected. Based on this, I think it’s safe to suggest that implementing IoT technology is turning out to be more expensive than originally thought.

This may be due in part to the fact that some enterprises are rushing headlong into IoT projects without the proper foresight and planning. Often it is a reaction to competitive pressure, based on a perception that a competitor is already moving forward with their IoT strategy, or simply in an effort to be the first and gain a competitive edge.

“I think it’s safe to suggest that implementing IoT technology is turning out to be more expensive than originally thought.”

Another answer may come from Gartner’s 2015 report: “Predicts 2015: The Internet of Things”, in which Gartner predicts that through 2018, there will be “no dominant IoT ecosystem platform”. They cite a lack of IoT standards and anticipate that IT leaders will be forced to compose solutions from multiple providers.


Read our White Paper on Choosing the Right IoT Software Platform

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Even when faced with these realities, however, enterprises are still moving forward with their IoT projects. The extra expense – though unanticipated – is not nearly enough to outweigh the potential benefits. The IoT is most certainly transforming the way businesses operate, and no one wants to be the last one to this dance.

IoT Investment

This is an important category as it will largely determine how quickly the industry moves to develop standards, and how motivated IoT solution providers will be to develop more powerful and more cost-effective solutions.
Recall IDC’s projection of annual market revenue reaching $1.7 trillion by 2020. It would stand to reason that if we are learning that IoT projects are coming in over budget and late, there is probably some distaste in the marketplace, and maybe IDC’s projection was a bit ambitious.

At the same time, though, if people are spending more on IoT initiatives than they had originally planned, perhaps IDC’s projection was a bit conservative. Let’s examine how things are taking shape.

In 2015, IDC reported that worldwide IoT spending reached $655.8 billion in 2014 and calculated a 16.9% CAGR (Compound Annual Growth Rate).

Well, 2015 is now in the books and we can see how IDC’s projections seem to be holding up. Their latest report indicates that spending in 2015 reached $698.6 billion, a CAGR over 2014 of only 6.53%. Had IDC’s anticipated CAGR proven accurate, 2015 revenue should have been closer to $766 billion.

Notwithstanding this fact, however, IDC continues to project a CAGR of 17% and an increase in spending to $1.3 billion by 2019, which would equal approximately $1.5 billion in 2020. It looks like IDC sees the IoT market cooling off a bit, though not much.

So, while the earlier projection has proven to be overly optimistic, it is clear that investments in IoT initiatives are continuing to increase with no end in sight.

If there is any kind of meaningful takeaway from all of this, I think it’s safe to surmise that IoT projects may be coming in late and over budget, but that doesn’t seem to have had much of an impact on continued investments. It is clear that business owners and executives see the value and have no interest in letting their competitor’s gain an edge.
So, was the IoT hyped a bit excessively over the last couple of years? Maybe a bit. But, it is also very real and happening right now.

Choosing the Right Maintenance Strategy

How do you choose the right maintenance strategy for your organization? Someone from the outside looking in might think the notion of choosing a maintenance strategy is as simple as choosing between ‘repair it’ or ‘replace it’, and that’s not entirely inaccurate. Beyond the surface, though, there are a number of different considerations that can have a long-term impact on a company’s bottom line and ultimate viability. Particularly when working with numerous or expensive essential assets that are subject to the continual wear-and-tear and eventual breakdown that plagues all machines, maintenance costs can take enormous bites out of revenue.

Fortunately, numerous maintenance strategies have evolved over the years, and technology allows us to apply new techniques using new models that were previously unheard of. Let’s review some of the more popular maintenance strategies:

Reactive Maintenance
This is the simplest strategy, sometimes referred to as ‘breakdown maintenance’. The premise is simple: Use something until it can no longer be used. Then, do what needs to be to repair it and get it back in action. If it can’t be repaired, replace it. There are some benefits when compared to other strategies, such as lower initial costs and reduced staff, as well as eliminating the need to plan. Of course, these benefits are usually negated in the long term by unplanned downtime, shortened life expectancy of assets, and a complete inability to predict breakdowns and maintenance needs. The only real viable reason for employing this strategy is an inability to afford the initial costs of any other strategy.

Preventative Maintenance
Preventative maintenance is performed while an asset is still operational in order to decrease the likelihood of failure. In this strategy, maintenance is performed according to a particular time or usage schedule. For instance, regular maintenance will be performed when this particular machine reaches 5,000 hours of uptime since the last maintenance. Predictive maintenance will typically keep equipment operating with greater efficiency and extend the lifetime of the asset compared to reactive maintenance, while also preventing unnecessary downtime. It does, however, require greater planning and man-power. Preventative maintenance is not a good choice for assets like circuit boards that can fail randomly regardless of maintenance. It is also not ideal for assets that do not serve a critical function and will not cause downtime in the event of a failure.


Predictive Maintenance
The purpose of predictive maintenance is to predict an imminent failure and perform maintenance before it occurs. This strategy requires some specific condition monitoring and will typically have a higher upfront cost due to the need to add sensors or other hardware, and will also require skilled personnel capable of anticipating failures based on the data points being monitored. Benefits include: the ability to prevent unnecessary downtime, and minimal time spent performing maintenance as it is only done when failure is imminent. Predictive maintenance is usually not a good option for assets that do not serve a critical function, or assets that do not have a predictable failure mode.

Condition-Based Maintenance
Condition-based maintenance is similar to predictive maintenance in that it involves continually monitoring specific conditions to determine when maintenance should be performed. Typically, however, condition-based maintenance is not just performed to prevent failure, but also to ensure optimum efficiency, which can not only improve productivity but extend the life of the asset as well. Because condition monitoring equipment and expertise can be expensive, initial costs can be quite high – prohibitive in some cases. In the long term, however, condition-based maintenance may be the most cost-effective strategy for ensuring optimal productivity and extended asset lifecycles. Condition-based maintenance is usually not a good choice for non-critical assets or older assets that may be difficult to retrofit with sensors.

When choosing a maintenance strategy, think about your goals: both long-term and short-term. Determine which of your assets are critical and which are not. Calculate the cost of downtime (per minute, per hour, etc.). Take into account whatever data may already be available for you to monitor. Determine the cost and viability of adding sensors to monitor things like temperature, vibration, electric currents, subsurface defects (ultrasonic sensing), or vacuum leaks (acoustic sensing). Estimate the costs of maintenance personnel in different scenarios. Estimate the difference in costs between each of the different strategies.

You may determine that a condition-based maintenance program would provide the greatest value, but you lack the resources to implement it right away. Can you deploy a simple predictive maintenance program in the meantime, while positioning yourself to make the leap to CBM in the future?

There is not going to be any one-size-fits-all “best” strategy, and not much drains a bank account faster than over-maintaining your equipment (yes, there is such a thing). Consider your circumstances and your goals, and choose wisely. It’s one of the most important business decisions you will make.

*B-Scada software provides data analysis, task automation, and real-time visualization for enterprises looking to implement a CBM program. Learn more at www.scada.com.

3 Reasons Modern Farmers Are Adopting IoT Technology at an Astounding Rate

It seems like everything today is touched in some way by the Internet of Things. It is changing the way goods are produced, the way they are marketed, and the way they are consumed. A great deal of the IoT conversation has revolved around transformation in industries like manufacturing, petrochemical, and medicine, but one industry that has already seen widespread adoption of IoT technology is often overlooked: agriculture.

Of course, many of us are very familiar with some of the efforts that have been made to optimize food production. As populations continue to grow, there has been a serious and sustained drive to increase the crop yield from our available arable land. Some of these efforts have not been particularly popular with consumers (i.e. pesticides, GMOs).

With the advent of new technology and the Internet of Things, farmers are finding new ways to improve their yields. Fortunately for us, these new ways are decidedly less disturbing than toxic chemicals and genetic manipulation. Using sensors and networked communication, farmers are discovering ways to optimize already-known best practices to increase yield and reduce resource consumption.

If it’s surprising that the agricultural industry would be technological innovators, it’s worth considering how agriculture is in many ways an ideal testbed for new technology.

There are a few good reasons for this:

1. Ease of Deployment

Unlike in other industries, deploying sensors and other connected devices on a farm can be relatively easy and inexpensive. In a heavy industrial environment like a factory or refinery, new technology must replace old technology that is thoroughly embedded in the production infrastructure. There are concerns about downtime and lost revenue, as well as concerns about finding the right products or group of products to integrate into their existing technological ecosystem. On a typical farm, there is no need for downtime, and usually no concern for any existing technology that may be incompatible. Inexpensive sensors placed in various parts of a cultivated field can quickly yield very useful actionable data without disrupting a single process.

2. Instant Value

Another reason that agriculture has provided such a fertile testbed for IoT technology is the speed with value and ROI can be realized. Pre-existing metrics of precision agriculture can be applied more easily, maximizing the already-known benefits of established practices (knowing what types of crops to plant when, knowing when and how much to water, etc.). Farmers have also had success safely and naturally controlling pests through the intelligent release of pheremones. Of course, there is the obvious and very tangible benefit of decreased resource consumption and increased yield. A modest investment can yield measurable results within a single season.

3. Continual value

In agricultural IoT deployments, the same practices that provide instant value will continue to provide value for as long as they are employed. Conservation of water and waste reduction provide repeated value, as well as the increased yield brought on by precision farming. There are also opportunities to improve the equipment that farmers use every day. A connected combine or tractor can record useful information about its operation and maintenance. It can also allow for certain processes to be optimized and automated.

There are some real concerns about our ability to feed our ever-growing population in the future. While controversial technologies like genetically-modified-organisms have helped to increase food production, these techniques are not exactly popular with the general public, several of whom have voiced concerns about the long-term impact of a genetically-modified diet.

The good news is that similar increases in food production are possible without the need to modify the food; we simply have to modify the processes used to produce it. And it’s not just about food production. Plants are also used for biofuels and as raw materials in manufacturing. By increasing yield and reducing resource consumption, growers are also having a positive impact on numerous other industries.

For instance, a Colorado-based company called Algae Lab Systems is helping algae farmers improve their output by introducing sensors to measure environmental factors like temperature, pH, and dissolved oxygen in their photobioreactors and algae ponds. Algae growers are now able to continuously monitor their crops from any location, also allowing for larger and geographically dispersed operations.

A case study detailing Algae Lab Systems provides some insight into how they are transforming the algae farming industry, and aquaculture in general.

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To Each His Own: Creating Custom Dashboards for Operators and Analysts


It’s always very annoying when I try to perform what seems like it would be fairly routine maintenance on a home appliance or worse – my car – only to find out that this seemingly simple thing I would like to do is actually quite difficult with the tools at my disposal. A little bit of research usually reveals that it actually is quite simple; I just have to buy this proprietary tool from the manufacturer for what seems like a ridiculous price, and then I can proceed.

Of course, it’s easy to understand why the manufacturer doesn’t want to make it easy for end users to service their product. They want you to buy a new one, or at the very least buy this overpriced tool from them so they can scrape every morsel of profit afforded by their built-in obsolescence.

It really makes me appreciate the simplicity and widespread application of some of our more traditional tools. Take a hammer, for instance. If you need to drive a nail into wood, it doesn’t matter if it’s a big nail, a little nail, a long nail, or a short nail. It doesn’t matter who manufactured it or when. All that matters is that it’s a nail. Just get a hammer; you’ll be fine.

This got me thinking. What if we had a hammer for every type of nail available? What if each hammer was perfectly sized, shaped, weighted and balanced for each particular nail? And what if that perfect hammer was always available to you every time you needed it. This isn’t realistic, obviously, but it reminds me of some of the things I hear from our customers.

One of the great benefits cited by our end users is the ability to create custom dashboards for the different work responsibilities in their organizations. The same system is used to create maintenance dashboards for technicians, control panels for operators, system overviews for managers, reports for analysts, and even special dashboards for contractors and vendors. By providing every member of the team with a real-time view of exactly the information they need to do their jobs and nothing more, each person is empowered to do their jobs with the utmost efficiency – improving the speed and accuracy of decision-making as well as increasing the capacity for planning.

In the past, so much of our data visualization was tied to the device from which the data was drawn. If you wanted to know something about a particular machine, you had to look at the same picture as everyone else, regardless of what you needed to see.

Some modern software platforms like B-Scada’s Status products eliminate this need to tie visualizations to the device from which the data is drawn. It is now possible to visualize data from multiple devices at multiple locations through the same interface. This allows for a new concept in user interface design: rather than displaying all available information about this particular thing, you can now display all information relevant to a particular task or set of tasks.

It’s not quite “a hammer for every nail”; it’s more like a complete tool set tailored to every job, containing exactly the tools you need and nothing more. It’s really been a transformative development for many organizations.

B-Scada recently released a case study detailing how one prominent North American electric utility used Status to create a system of customized views for their operators, managers, and analysts, providing specific insights into the real-time status of their generation resources:

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