Where to Start and what is Industrial IOT?


Data-Driven Manufacturing/Industrial IoT is making decisions on manufacturing based on facts, not guesses and opinions. This creates the capability to make decisions based on the combination of three concepts.

Data Driven Manufacturing Equation

What is Data Driven Culture?

A Data Driven culture is a company that provides one version of the truth of its data with everyone, the people are trained and empowered to find problems in the company, analyze the related data, make decisions, and most importantly take valuable action to solve the challenges. Companies with a Data Driven culture typically beat out companies that don’t in their markets.

Having a Data Driven Culture requires two things:

    • A positive, progressive, problem-solving culture within the people: This culture starts with leadership driving the company forward, being open minded about how to improve, and empowering people to take valuable actions.
    • A positive culture around data: The people also need to understand data at a basic level have access to true, accurate, single-version-of-the-truth data, empowered to use it, and interested in using the data for the betterment of the company.

What is IoT?

IoT is where the data comes from…that single version of the truth discussed above.

So, what is IoT (Internet of Things)? In it’s purest form IoT is:

Pulling data from sensors, pushing the data over a backhaul, transforming that data into valuable information, and using the information to enable powerful business outcomes.

To be clearly, IoT is the source of data, or better yet, information. That information becomes the basis on which decisions are made and valuable action is taken.

IIoT (Industrial Internet of Things) is an idea that obviously originates from IoT. It is the application of IoT in manufacturing and heavy industry.


There are two areas where Industrial IoT or Data Driven Manufacturing is typically used in manufacturing and heavy industry.

Smart Connected Operations

In manufacturing plants there are machines or equipment used to form raw materials into sellable products. Many of those machines are critical to that process, and are quite expensive to acquire, operate, and fix. Therefore, manufacturers want to keep the machines up and running as much as possible. The idea with Smart Connected Operations is to make these machines “smart” by connecting the machines using sensors, gateways, networks, software platforms, and other IT tools like servers, the cloud, etc. to implement an Industrial IoT solution.

The best solutions also pull contextual data from other sources like the operator, shift, the parts being run, the schedule, cycle times of the parts processed by the machine, and other characteristics. This data makes the machine data vastly more valuable because it now has “context”.

The combination of these two sets of data turn into a solution which provides the real value…real-time visibility into the operations on the plant floor.

Smart Connected Products

Now imagine those machines in the plant or used somewhere in heavy industry such as an oil or gas field. An OEM (Original Equipment Manufacturer) manufactured that piece of equipment.

Service: The OEM is likely responsible for a warranty and good operations of the machine for a period. Sending a technician to a distant oil field to simply see if it’s running well, let alone is it running at all is very expensive. Why not look at ways to reduce service and maintenance costs, prevent angry customer calls, and create a closer working relationship with the customer.

Innovation and Invention: The OEM likely wants to understand how those machines are used so they can sell more of them. They can do this by understanding how the machines are used in the field and then figure out how to improve the machines such as fix common issues, add new features, or come up with new inventive ideas based on those machines.


There are inefficiencies in operations. Labor is more expensive and harder to find. You don’t have solid data to understand what’s going on at the plant floor.

We can help you get real-time visibility into the factory floor.

Machine cutting tool.

Mid-size OEM of compressors and welding/cutting equipment

Compressor OEM improved levels of service, equipment performance, and operational efficiencies.

Power supply manufacturing.


We need to track changes to the documents, and to check, modify, and close out the document changes.

Cable/Wire machinery.

Small Manufacturer, builds wire and cable solutions

Unplanned downtime has been reduced significantly, increasing asset utilization and revenue from that cell. 


Real-Time Visibility into the Factory Floor, Remotely

Data-Driven Manufacturing solutions provide real-time visibility into the factory floor, remotely. They take all of the data on the plant floor and make it immediately understandable and accessible. Then you know exactly how the plant floor is running.

Implement in 1 Day

One machine, non-invasive sensors, 1-2 data points with additional contextual data, and you can be up and running getting valuable data to drive valuable problem-solving. The solution is then scalable to whole plants and more.

Track Availability and Reduce Downtime

You can determine the What, Why, Who, and When of all your downtime. Data-driven manufacturing solutions give you the power to track availability and all downtime by reason code directly from the PLCs and operators.

Increase Throughput and Performance

Easily measure your actual cycle times and compare them against the standard. Identify bottlenecks and track cycle time improvements. Set up alerts when performance is higher or lower than normal.

Improve Quality and Determine Root Cause

To calculate quality of a part, data-driven manufacturing solutions collect part counts and reason codes directly from the PLCs, other sensors, or operators. Using dashboards, these solutions can help you determine the most common causes of scrap.

Improve On-Time Delivery

With better, real-time data comes accurate cycle times and historical data. Combining that with improvements in production, production process, and quality provides better estimates for producing parts in a job. This all comes together to improve on-time delivery to customers.

Correlate Process Data With Downtime and Scrap

Process data can affect downtime, quality, and throughput. If you correlate that data to the corresponding issues, you will know exactly when an issue occurred.


Bayer Healthcare, medical device manufacturing.

Bayer Healthcare

The software developer doesn’t work here any more.

Wood product manufacturer producing OSB boards with a large press.

Estimated Life Remaining Calculation Reduces Expensive Downtime

Company is a wood products manufacturer creating OSB board with a very large press.

Tier 1 automotive supplier.

Tier 1 Automotive Supplier

Down-time and OTD addressed with asset monitoring for Tier 1 Automotive Manufacturer

Compare Industrial IoT to Other Solutions

Solutions like Industrial IoT / Data-Driven Manufacturing have a unique place in companies and provide a lot of value. That value comes from our solutions’ unique ability to pull data from machines on the plant floor, innately understand that data, add other contextual data to it, and make the data understandable and valuable to all users. These tools are unique to and work with manufacturing processes and machines on the plant floor. We see some manufacturers trying to use other products and they end up missing a lot of the benefits otherwise available.


ERP systems are great for planning for the future by evaluating what happened in the past. ERP systems don’t provide real-time analytics on manufacturing processes and machines on which you can take immediate action. Using an ERP system for manufacturing analytics would be like driving by looking at your rearview mirror. Don’t get us wrong, ERP systems are valuable. Though, their place isn’t in providing that immediate, actionable data on what’s going on now on the factory floor.

Business Intelligence (BI)

Many BI systems provide insights into processes and are very general products used at the enterprise level. However, these products falter because they aren’t built to work with machine data and manufacturing processes. To adjust them to work in that way requires a very significant investment in additional time, people, and money to get the solutions to work optimally.


SCADA systems primary focus is controlling the manufacturing process and what shouldn’t happen in that process. They aren’t able to provide explanations of what’s right and wrong. Additionally, many of the SCADA systems are built on older technology and struggle to make data available to the wide audience that requires the valuable manufacturing analytics data. Manufacturing analytics provides visibility.