Breaking it Down: Building Blocks of Smart Manufacturing

A Smart Manufacturing company is a manufacturer with fully integrated solutions that empower it to be highly flexible and responsive
to changing conditions, with self-healing systems. Those capabilities enable a company to reduce costs, generate more revenue, and

increase their competitiveness in their market.

So how does it all work, and where do these capabilities come from?

The Nine Blocks that Stack Up to Smart

There are 9 technologies or building blocks that stack up to create Smart Manufacturing.

  1. IoT (Internet of Things): Taking data from sensors on machines, moving it over the internet, and converting it to valuable information to help people make decisions and drive action.
  2. Automation and robots: Using robots and software to enable machines and people to work together more efficiently.
  3. Big data: Storing and using massive amounts of machine data for data analysis to gain insights about operations and machines.
  4. AI (Artificial Intelligence): Using software tools to build models and algorithms which can learn about niche areas of your facility to distinguish between normal and critical conditions.
  5. AR (Augmented Reality): Viewing models or images overlaid onto the real world on a mobile device.
  6. Additive Manufacturing: Creating objects from 3D models by joining materials layer by layer.
  7. Modeling: Portraying or defining aspects of the physical world in digital form for gauging equipment status, simulating operations, or controlling live systems.
  8. Cyber Security: Applying old and new ideas of encryption, protecting attack vectors, and combining digital with physical security tactics to protect data in motion and data at rest.
  9. Cloud: Moving away from local, on-site servers towards 3rd parties like Amazon, Google to store, service, and process data.

Stacking the Blocks

Each of these technologies can deliver value on its own. However, companies can realize exponential value by combining technologies.

Here are a few examples:

     Predictive Maintenance

  • Technologies: IoT + AI
  • Method: AI experts create a machine learning model. IoT pulls data from machines and channels it through the model to assess the probability that a part or whole machine may fail within a certain period of time.
  • Benefits: Clear identification of critical maintenance windows, resulting in up to 50% cost reduction by addressing issues only when needed but before failure.

     Robot-Assisted production

  • Technologies: Robots + Automation + IoT
  • Method: A “human assistant” robot is programmed to work alongside people to handle repetitive and mundane tasks or sets of tasks. The robot is pre-programmed to handle multiple task sets. Input from IoT data (such as production data further up or down the line) directs the robot to change its tasking based on real-time production needs.
  • Benefits: Increased production with existing staff and reduced pressure to hire/replace workers.

     Data-driven quality control

  • Technologies: IoT + Automation + Big Data
  • Method: Set up machines to test products immediately after a certain stage of production. Automatically analyze that data relative to product quality standards. Based on results, either trigger alarms for humans to intervene or have the equipment modify its own behavior appropriately to meet the required standards.
  • Benefits: Earlier notification of equipment problems, earlier identification of product quality issues, reduced waste, and rework. Increased production of a product to standards.

Choosing the Right Blocks

Some of the most exciting benefits of Smart Manufacturing come from the myriad and creative ways that new technologies can be combined and implemented. Finding the right combination requires effort: thoughtful planning, employee input, and focus. But even small and mid-size companies can increase their competitive position, with access to the same building blocks as larger manufacturers.

What Is Smart Manufacturing and Why Should You Care?

Smart Manufacturing is a term with many definitions that all have one theme in common:

using new technologies and capabilities to gain a competitive advantage.

The Ideal and The Reality

At Ectobox, we say that a company is a “Smart Manufacturing” company when they have fully integrated solutions that empower them to be highly flexible and responsive to changing conditions. A Smart Manufacturer produces a quality product, uses finely-tuned processes, monitors their supply chain and coordinates it with production, and overall, maintains systems that work well together. Theoretically, the best Smart Manufacturers can even fix their own problems automatically.

But what do we typically see the most of? Engineers huddled around a problem trying to solve it. Inventory pilling up in various work areas or cells. Inventory “starvation” in other areas. People and machines not working when they should be. These situations are so common that we see them at almost every manufacturing company we visit. The good news is that these issues are all fixable. The bad news is that manufacturers who don’t make the effort to eliminate these issues and increase their efficiencies are the ones who will struggle to stay competitive.

Why it Pays to Pursue Smart Manufacturing

Besides the appeal of new technology, why does Smart Manufacturing really matter to the average company? It matters because the specific technologies and capabilities under its umbrella can make companies more efficient, enable cost reductions, and potentially, drive new revenue. Some of the capabilities Smart Manufacturing offers are:

  • Better insight into what’s going on at your plant floor
  • New and better products and services to meet your customers’ needs
  • Faster development and launch of new products
  • Reduced costs of production
  • More revenue per employee and per machine
  • New business models (such as selling your products as a service)

Smart Manufacturing is the Future

Manufacturers all over the country are under pressure to be more competitive and overcome new challenges. In reality, factories of the future probably won’t look much different than they do now. The biggest difference is that they will be working much more efficiently. The machines and people and supply chain of the future will be more flexible, better-coordinated, and self-healing. The technology is already here, so companies can start getting “Smart” right away.

In our next blog post, we will talk about the specific technologies within Smart Manufacturing.

IoT Solution Success: Start Small, Work Efficiently

The best way to begin implementing an IoT solution is to start small – but what exactly does that mean, and why is it important?

In this post, you will learn how to plan your first IoT solution by looking for a simple problem that IoT can solve quickly, and why that ensures success.

How to Start Small

When we say to start small, that means don’t try to create a “big bang” solution. It’s natural to want to solve all your problems at once or make a huge impact on the market. But the driving goal in integrating IoT into your business should always be improving how the business runs. Successful businesses tend to grow gradually over time, and implementing solutions to solve business problems the same way allows the process to mature and evolve over time. So, always begin by defining your desired business outcomes and requirements. You can think big as you consider how this will improve your overall productivity and grow over time but then start with something simple as the first step.

Find a Simple Problem to Solve

The best way to figure out where to start is to pick a problem to solve. Perhaps you run a manufacturing plant with pools of cooling water, and your pumps are often down or not functioning properly. This can be the problem you want to solve.

In order to do so, you’ll need to ask yourself some problem-solving questions such as, “Do I know how much uptime/downtime my pumps have?” or, “Can I monitor the motor speeds of my pumps?” You can even ask questions such as, “Can I view my data remotely?” Perhaps you have meters on your pumps to track their performance, but you need an employee on-site at all times to monitor them.

When you focus on one problem, you can define factual questions that will help point to a solution.


A lot of companies get lost at the implementation stage. . While they have identified one problem they wish to solve, they may be unsure of how to begin solving it. Just remember: focus on the simple problem. It’s easy to get confused when, as one problem is related to others, but you will be able to solve those later.

Ensure you have the best people on the job. Find IoT experts to work with and assign employees that have the desire to improve your operations and who are open to change. A great way to ease everyone into this change is to pick an off-the-shelf solution. There’s no need for custom solutions in IoT when you are first starting out. Custom solutions are expensive and can end up evolving into large-scale projects before any basic implementation. PTC’s Thingworx is a great example of an off-the-shelf solution that is designed with manufacturing in mind. It is user-friendly enough that anyone can use it, from the shop floor to the top floor.

By solving that one simple problem, you’ll have achieved your initial success, and created a model for solving future problems.


Implementing an IoT solution may seem like a huge undertaking, but it doesn’t have to be. If you think big but start small, you can avoid many of the common pitfalls. Focus on how IoT can help the business, and find the right people to help you. Reliable employees who want to grow with the company in combination with experienced experts will ensure you can get your first solution out the door. If you have questions or need advice on how to get started with IoT, feel free to give us a call at 412-923-3002 and one of our experts will be happy to help.

Ectobox celebrates 20 years!

The Past

2018 marks 20 years of Ectobox developing solutions outside the box.

Ectobox began as a software consulting firm driven by a simple idea: we don’t like to see companies suffer needlessly doing work manually that can hold a business back when there are opportunities to automate processes. Our President and founder wanted to help. With a servant leader mentality, Ectobox moved forward with helping other companies improve, get better at what they do, and grow with software and data.

The Present

IIoT, Software Expertise and the Manufacturing Sector

Ectobox has recognized the power and value that IoT can bring to manufacturers in becoming better, more efficient organizations. Therefore, Ectobox has transformed into an IoT and software consulting and solutions company. We are able to help manufacturing companies grow with strategic level consulting as well as the tactical details of technical implementations. We have made this transformation by, among other things, being thought leaders and experts in IoT, making strategic moves to expand our consulting and technical capabilities, and using the latest tools and technology including PTC ThingWorx, AWS IoT, and Azure IoT Hub.

The (near) Future

Continuing to Share Manufacturing IoT and Software Knowledge

As Ectobox sees significant company growth in size and market presence, we hope to continue to build strong partnerships with all of you that last into the next 20 years, and beyond.

We have many exciting trade shows, speaking events, and webinars coming up at the end of this year and into 2019 including:

How to Profit from IoT Webinar – October 3rd
Business Transformation with IoT – October 17th
Manufacturing Day – October 4, 2018
Industrial IoT World Atlanta – October 29-30
Digital Bridge Industry 4.0 Conference – November 1st
Westmoreland Chamber IoT Roundtable Panel talk – November 2nd (registration info TBA)
NWIRC IoT/Industry 4.0 Webinar – November 7th (registration info TBA)
NWIRC IoT/Industry 4.0 Webinar December 11th (registration info TBA)

The Value of Condition-Based Monitoring. Part II: Technology

Last time, we discussed how to prepare to implement an effective condition-based monitoring system for your operations.

In this month’s post, we’ll show you how to choose the right technology.

Choosing the Right Tool

With the operating parameters and failure modes defined, you can now add effective monitoring to your operations. Many companies currently employ humans to monitor the conditions manually. Maintenance rounds are a common part of maintenance staff duties. The employee will walk around with a clipboard, take measurements from the equipment, and then log the data into some log format. Ideally, they compare those data points to required operating conditions, and if they see some operating value out of bounds, identify impending issues.

Technology can help a lot here. A system such as an IoT software platform, can easily pull data from multiple pieces of equipment and automatically deliver warnings of potential issues.

There are two major components of success when implementing a technology-driven solution.

The Right Platform

The first key to success in a technology-driven monitoring solution is choosing an IoT software platform that is flexible enough to handle nearly any piece of equipment for configuring how the equipment operates, as well as the multiple ways the equipment could fail, and what automated notifications to send. Additionally, the software should be able to read the data from nearly any piece of equipment. Some software tools are proprietary to a specific hardware product and won’t work for all equipment, so you will want to avoid those.

A tool like ThingWorx from PTC has the flexibility to handle any piece of equipment and read data from nearly any data source. It can also be set up to provide warnings of any type, and it can integrate with a company’s CMMS. And it’s scalable. When installed, the reliability team can start small, tackling one component of a single piece of equipment for testing purposes. If that works, then they can easily add other components and equipment. The tools for setup and configuration allow for fast setup and long-term solutions.

Choosing the Right Factors to Monitor

The second key to a successful monitoring solution is understanding what the most impactful components, operating conditions, and failure modes of the component are. That information can be configured into your IoT software platform. Once an abnormal condition or failure mode is noticed by the automated system, it can throw an alarm, send a text message, or put in an automatic request for service from the maintenance team, etc.


Let’s put all of this info into a short example. For a high-pressure air compressor, one of the components is a pump. The pump’s purpose is to pump oil to the compressor lubrication system at a target pressure of 25 psi. The machine can continue operating without affecting the larger equipment even if the pressure is maintained above 20 psi. So if the pressure drops below the optimal 25 psi but hasn’t gone lower than 20 psi ThingWorx could throw a “yellow flag”. Then, if a maintenance person has the time they can look at it while it is still operating effectively. However, when the pressure drops below 20 psi, the system delivers a red flag that warrants immediate action.


Condition-based monitoring is important because 50% of manufacturers become aware of a problem only after a breakdown has occurred, which results in downtime, lost revenue, and high repair bills When an issue is caught and fixed before it breaks down, a company can expect a significant decrease in maintenance and repair costs as the equipment is protected from a more significant or catastrophic failure.

The Value of Condition-Based Monitoring. Part I: Preparation


Diligent monitoring of the condition of equipment at manufacturing plants (condition-based monitoring) can have a big impact on the company. This is an increasingly urgent issue in a market where approximately $65 billion worth of automation systems are at or near the end of their useful life. The oldest equipment still in use dates back to 1938.

Condition-based monitoring can greatly reduce the cost of repairs and keep the company assets up and running for longer periods. At the same time, it allows the company to reduce costs and generate more revenue.

You’ll find below the way to begin condition-based monitoring in your operation. Keep in mind that the work outlined below should be performed within the context of a business case to ensure the work is has a good ROI, is based on an incremental process of Proof of Concept through Production, and that it is performed in a culture that drives and welcomes change for the betterment of the company and all who work there.


To monitor equipment, there are three prerequisites you need to ensure that you can prevent major issues and realize the resulting cost saving and additional revenue. They are:

  • Know the equipment
  • Know the Issues
  • Have a tool

Know the Equipment

Before you start hooking up sensors and software to equipment you need to know your equipment:  how it needs to operate for optimal outcomes, its suggested limits, and how it can fail. The team working to set up condition-based monitoring must understand the technology and the operations of the equipment so they know what is normal and what is abnormal. They can then translate this information to the monitoring system.

You’ll want to record this information for both the primary function of the equipment (its main purpose) such as a high-pressure air compressor that supplies compressed air) and also the functions of its components (e.g., electric motors, pumps, valves, etc.). If possible, this information should be organized into a hierarchical diagram, with primary functions at the top and lower level support functions further down the diagram.  It is important to document the individual component functions because those functions and breakdowns ( loss of function) can negatively impact the whole piece of equipment and ultimately, the performance of the plant.

Next, you must define and agree upon the operating context of the equipment. The operating context means the desired operating parameters of the equipment. For example, what are the capabilities of the equipment and its components, what are the optimal minimum and maximum operating parameters for the equipment (e.g., power, flow, pressure), and suggested shutdowns and maintenance work. You can usually find all this information in operating and maintenance manuals.

Know the Issues

Once you have defined normal operating conditions, you are ready to define the failures or potential failures What are the different ways that a component could fail? What is the potential impact on the equipment and other components if the component in question fails? How can that failure be identified in terms of operating parameters (e.g., pressure rises above 100 psi) or other data (e.g., the temperature of the motor casing rises above 200 degrees). These definitions are referred to as failure modes. Along with defining the failure modes, the team should define proactive tasks that can be performed to mitigate or eliminate the issues.

Next time, we’ll discuss the keys to successfully implementing a condition-based monitoring system.

One-Two Punch: Use the Industrial Internet of Things (IIoT) and the P-F Curve to Save Money and Asset Utilization


IIoT can improve a manufacturing company’s asset utilization ratios and the production line’s up-time to produce significant savings in maintenance costs. This is illustrated through the P-F curve method of condition-based maintenance.

Causes of Failure Vary:

Let’s start with the basics. Failure of an asset or piece of equipment is a process, not an event. The common leading causes of failure in equipment include wear, stretch, deterioration, misalignment, and contamination. Each of these failure causes can develop over time. Additionally, the time from the start of a cause of failure to the actual point of failure (i.e., the functional failure) can vary. Therefore, these causes don’t lead to failure immediately, nor all at once. However, failure can and does eventually occur from one or more of these causes. Therefore, the failure of an asset is a process that occurs over time based on how the machine is utilized and treated.

The good news is that failure takes time to happen. This provides an opportunity for maintenance staff to identify potential failures and apply fixes, to prevent or reduce the consequences of the failure.

Fixing equipment after it fails is called Reactive Maintenance.  Unfortunately, it is an all-too-common method of identifying and fixing issues with equipment and has expensive consequences. Failure of equipment leads to lost production time, costly fixes, or asset replacement.

The preferred approach for the maintenance of equipment is to avoid failure altogether. We can maintain the physical assets in such a way as to avoid the consequence of failure, whatever the cause.

Consequences of Failure Are Expensive:

The causes of failure can vary from small to significant. If the causes are negligible, maintenance staff may choose to do nothing.

However, the costs or consequences of failure can significant, such as loss of production of the asset, loss of the asset such that it has to be completely replaced, or shutdown of a whole production line. In these cases, it makes sense to put forth the effort to detect the failure “process” as early as possible before failure. At that point, maintenance staff can take corrective action required to avoid the failure or at least reduce the consequences.

The performance of the equipment will degrade over time, from the point the potential failure starts through to the functional failure. The cost of fixing a potential failure often will be lower if the cause of failure is identified and fixed earlier.

P-F curve:

Use the p-f curve chart to assess your asset utilization

The P-F curve (illustrated here) illustrates the progression of behaviors of an asset over time and the increasing costs of addressing those behaviors.

In the P-F curve, the X-axis represents time, and the Y-axis represents the condition of the asset. On the curve, a potential point of failure–one of the various causes referenced in the previous section– will occur early on the timeline. That is the point at which a failure cause first manifests and may potentially be detectable. Over time, across the X-axis you can see the decrease in the condition of the asset. That degradation of condition will exhibit itself in various forms, each of which should be detectable.

The P-F curve illustrates the interval between the point of potential failure (earliest point of a detectable behavior which indicates eventual failure) and the functional failure, and the behaviors that are exhibited over that period of time are important.

This progression of behaviors and deterioration of the condition of the asset over time means it is best to identify the failure cause, i.e., potential failure, as early as possible before the failure of the asset, and fix it. Additionally, the P-F curve illustrates how the cause of potential failure will be less costly to prevent earlier in the timeline. Exercising proper asset utilization and collecting important data will assist you in avoiding machine failure.

Here is an example of the change in behaviors over time and the costs for failure prevention on a P-F curve: The potential failure could be detected early in the process in lubricant oil through analysis. One cause might simply be that the oil is old and needs to be changed. That can be a relatively inexpensive fix. If not addressed, however, it could then deteriorate to a vibration. Data about the vibration would need to be obtained and analyzed. Eventually, the use of IR thermography may detect heat where a human may not easily detect the heat caused by friction. At these points, the issue could possibly be addressed with inexpensive fixes such as additional lubrication or replacing a part. The issues could eventually progress to audible noise, heat detectable by a human, and smoke. These conditions could cause other problems with the equipment which would increase the time and costs for fixing the equipment. If not addressed, the equipment will eventually reach the point of functional failure. That is the point at which the costs for fixing the issue are highest.

A CBM Program Can Help

Companies can put a Condition-Based Maintenance (CBM) program in place to systematically identify and address potential failures earlier than otherwise possible and save significant costs and time.

Detection of potential failures with condition-based maintenance historically is done by regularly scheduled inspections. Maintenance staff will visit and review the condition of the asset on a fixed schedule. That schedule could be defined in a number of ways, including usage of the asset (number of hours of usage), productivity (number of parts processed), or the calendar (every 2 weeks or every 6 weeks). Some common condition monitoring techniques are vibration measurement and analysis, infrared (IR) thermography, process parameter trending (e.g., temperatures, pressures, rates, flows, etc.), visual inspection, corrosion monitoring, and others.

With this method,  the inspection intervals must be shorter than the interval from potential failure to functional failure.

The problem is those manufacturing companies are challenged with reducing expenses and staff, while at the same time maintaining and increasing asset utilization. To be clear the asset utilization formula is a measure of how much the asset is available for producing products versus how much it’s scheduled to be available. Any maintenance staff team member might struggle to visit and inspect every machine on the required schedules. This is especially true for manufacturers that have a large number of assets or where many of those assets are in remote locations relative to the maintenance staff.

IIoT to the Rescue:

IIoT can be integrated into a company’s CBM program to automate monitoring and analysis of equipment behaviors. In an IIoT solution, data can be pulled from sensors on equipment, analyzed, and eventually converted into valuable information. The IIoT solution can constantly monitor every asset — 24 hours a day, 7 days a week, x365 days a year. The maintenance staff can then see the status of all of their equipment from any location, can assess the causes and severity of the potential failures earlier in the P-F curve, and then optimize their personnel and financial resources to address potential failures.

This allows the maintenance staff to then be more proactive, focusing on issues earlier. It also translates to reduced costs of maintenance and prevents the costs of lost production time. As a result, the manufacturer will see a higher asset utilization ratios for the assets, and thereby attain greater production uptime, which can be expressed in improved OEE (Overall Equipment Effectiveness).

IIoT Delivers More Money with Better Asset Utilization Ratios

Incorporate Industrial IoT systems on these pieces of equipment to decrease downtime and gather important data. Also use these IIoT systems to reach optimal Asset Utilization Ratios.Manufacturers can improve their operations and thereby generate better revenue and profit with IIoT.

They can do this by unlocking data from their equipment, calculating the OEE (Overall Equipment Effectiveness) for the equipment, and use the resulting data to find the issues, and even fix them right then and there.


Let’s start with a bit of perspective. Manufacturers have historically struggled to determine whether or not the equipment was performing at its peak performance. It has often required a labor-intensive effort manually collecting data from machines, either by operators or maintenance staff. Often that data was collected and filed, and never compiled and analyzed.

Think about how much money and resources it really requires to keep up to date on all of the information on every machine in your lineup. Historically, you would have to pay someone to do all of this work. That is a lot of money on a regular basis for someone to get this done. However, that isn’t even the worst part, the worst part is the substantial amount of downtime. Downtime accumulates fast in these situations where a machine or a lineup of machines will have to be down to gather this information for preventative maintenance. Fortunately, there is a better solution today.

Large companies with large budgets have had the resources to purchase or build systems to automate the collection and analysis of that data.

However, technology has changed to allow smaller companies to purchase, setup, and then get immediate access to valuable information on their equipment. These changes include not only IIoT software platforms for collecting, analyzing, and visualizing the data for human consumption, but also changes in other areas such as PLCs with automatic fault codes, and low-cost devices to get data from older machines. This completely changes the manufacturing landscape. With this revolutionary technology now readily available to small-medium sized companies, the standards in all levels of the manufacturing industry are changing. Automation for better asset utilization is the direction everything is moving towards.

Research Says

Now more companies are using IIoT and OEE to improve asset utilization. Some studies suggest nearly 80% of manufacturers adopting IIoT do it for machine health and asset utilization (World Economic Forum’s Industrial Internet Survey). Respondents said the top reason they are adopting IIoT is for optimizing asset utilization ratios. Some even said near-term adoption was “extremely important” or “very important”.

How To

To get the benefits of improving asset utilization ratios for equipment, manufacturers must use IIoT and a KPI such as OEE. The company should start by using the IIoT solution to calculate OEE (How to Calculate OEE Guide). OEE a decades-old method of measuring how available your equipment is to be productive and generate revenue. It looks at uptime versus downtime, and all of the types of downtime. The IIoT solution can pull data from equipment previously not available and then calculate OEE. Staff and management can then use the machine fault codes and related equipment data from the IIoT system to the valuable, easier, and less expensive issues to fix. The fixes can lead to early wins of more equipment uptime. A data-driven culture and a continuous focus on OEE can yield a better asset utilization ratio and better revenue and profit.

End results

PwC research suggests industrial companies can achieve more than a 30% increase in revenue if they make efforts to digitally transform their operations, including using IIoT for improving asset utilization and the related asset utilization ratios. Some companies report they can find and fix issues within even a few weeks. This enables a fast and significant ROI from the investment in focusing on OEE using an IIoT solution.

Why should your manufacturing company look at the Internet of Things?

Your manufacturing company likely has business goals which include growing revenue, margins, and profits, as well as beating out the competition.

In today’s market, those goals are increasingly difficult to achieve.  Companies must continue to become more efficient, increase output, work for more demanding customers, work under increasing regulations, all the while continuing to earn current or better margins, and profits.

In the past, installing ERP systems or using Lean and Six Sigma frameworks was enough to improve the business. Many businesses can still benefit from those kinds of efforts. However, more and more those efforts aren’t enough to get the required efficiencies, production, and competitive differentiation.

The Internet of Things, which is a set of technologies put together into a system to convert data into useful information, is the next solution for enabling a business to accomplish its goals.  Here are a few ways IoT becomes the next solution:

  1. Digging Deeper: ERP and MES (Manufacturing Execution System) systems are set up to provide data down to a certain level of detail for manufacturing processes. That used to be enough for companies to make major improvements in production efficiencies. However, IoT can provide data that is another level or two deeper. It can, among other tasks, provide data about conditions inside the equipment. That data can be used to understand how close the machine is to its effective operational limits, in addition to providing production output and related data.
  2. More Uptime: The internal data can also be used to provide information on the condition of machines and even predict if and when they might break down. This allows maintenance and service technicians to fix the machines before major issues occur and keep them up and running longer, thereby increasing OEE (Optimal Equipment Effectiveness).
  3. Sharing Data: The information that comes from an IoT system about production and equipment conditions can be shared beyond the manufacturing plant floor. Equipment often has an HMI (Human Machine Interface), or a screen from which users can view status information. However, that data is often not available outside of the shop floor. Utilizing the “Internet” portion of the Internet of Things allows maintenance technicians, management, and business leaders to see important data as needed.

Once the IoT system is in place, people across the organization can use the deeper, more useful data from equipment, manufacturing processes, and other areas of the business to drive decisions and actions. This is where the data becomes valuable information, and thereby becomes the differentiator in moving the business to the next level of growth in revenue, margins, profit, and also in competitive advantage.

These Industrial IoT systems give you access to data that has never been available before. We now have the ability to pull a large amount of new data from machines instantly. This all happens in real-time and is a game-changer for the manufacturing industry. Instead of tending to a machine that went down, diagnosing the problem, and trying to determine what you need to fix it; You can let your manufacturing IoT system pull the data you need to prevent this problem before it happens, or if something does break, you now have all of the information to determine the cause a lot faster. This also helps you understand your machines better, if you can see the data and watch everything that is going on inside your equipment, you will be able to run an efficient plant while making confident data-driven decisions.

If you have any questions at all, feel free to Contact us for more information. If you enjoyed or found some insightful information in this article, check out our blog, we have many more IIoT based articles to help you take your business to the next level.

Consider off-the-shelf IoT software platforms

We have seen some companies attempt to create a custom IoT software platform for their own use.

Generally, we recommend against this for several good reasons.

First, some background information. [Or, if you are already familiar with IoT, skip ahead to the Why Not to Build section below].

What is the Internet of Things?

The Internet of Things (IoT) is the process of pulling data from sensors on equipment or other devices, moving it over the internet, adding other data from external systems, and then transforming that data into valuable information.

IoT converts physical action and data into digital data. A sensor detects a certain type of activity on a piece of equipment. That “activity” is transformed into a digital signal, and then sent over the wire to a collection point, and then pushed on into the IoT software platform. The platform is where the data is transformed into valuable information through processing, adding other data from external systems, often run through machine learning algorithms, and then displayed to end-users.

Some uses of IoT:

  • IoT solutions allows companies to monitor and manage activities in various areas of the business, such as the condition of machines
  • IoT allows physicians to monitor the heartbeats and respiration of babies in-home and allows parents to maintain a warm home environment to allow babies to develop.
  • IoT can tell you what food is in your refrigerator and then automatically order missing items from your grocery store for delivery.

What is an IoT software platform?

An IoT software platform is the place where the data transforms into valuable information. There are a number of components in the platform, as follows.

  • Software: The software contains the data and cyber model and orchestrates various parts of the software platform. It also provides the visualization, and often the capability for end-users (not only software developers) to configure the system or make changes to the system.
  • Data processing and storage: When data comes into the platform, data must be processed and then stored.
  • Analytics: A lot of the transformation of the data into valuable information happens in the analysis of the data. This analysis can include basic descriptive statistics all the way up to machine learning algorithms for predictive analytics.
  • Interface to External Systems: Any good software platform must be open such that it can interface with other systems. Part of the value of IoT comes from data other than the data from equipment and other devices.
  • Security: Security is increasingly important to protect the company’s intellectual property. The IoT software platform should provide strong protection for data at rest (in storage) as well as in motion (moving over the network and into the platform).

Why Not to Build an IoT platform

Now, imagine creating a tool from scratch that does everything described above? The project would be immense, long, expensive, and likely experience the unfortunate issues and delays too many software projects experience unless you have the right team and leadership running the software project.

It’s analogous to building your own ERP (Enterprise Resource Planning) system. We talk with a lot of manufacturing companies, and out of the hundreds I can think of only 3 companies that have a custom ERP system, all of which are now being replaced; two because they are old and inflexible, and one because the company truly is unique and no other system did what they needed.

There are a lot of ERP systems to select from and many of them provide virtually the same features and benefits because the needs of manufacturers are often very similar.

This same principle applies to IoT software platforms. IoT is about pulling data from sensors on equipment, moving that data over the internet, adding other valuable data to it, and converting it to valuable information. This means the needs of different companies are often very similar. Additionally, at a high level, the components of systems are frequently the same.

When needs are the same, and there are a lot of similar systems that can provide the required features and benefits, it’s likely that there is an IoT software platform out there that will provide what a company needs.

Which System to Use?

We are believers in choosing the platform that best fits your needs. We provide IoT solutions using either or both the Microsoft Azure IoT platform and the PTC ThingWorx suite of IoT products.

If you have questions or are looking at either Azure or ThingWorx, please call us at 412-923-3002. We’d be happy to provide a  free consultative meeting with recommendations.