Why Manufacturers are Stoked about IIoT
Michael Alba posted on March 27, 2018 | | 9552 views
In a demonstration of IIoT capabilities, Siemens connected industrial sensors to a miniature model world. (Image courtesy of Siemens).
In a demonstration of IIoT capabilities, Siemens connected industrial sensors to a miniature model world. (Image courtesy of Siemens).
Manufacturing professionals are bullish about the Industrial Internet of Things (IIoT). In a recent survey, they were asked to provide their estimates of the productivity improvements their companies would experience from implementing new processes based on IIoT technology. Not only did they expect to see strong productivity enhancements from superior analytics of machine and process performance, they felt almost as strongly about every other application in the survey.

Specifically, these professionals were asked to rank the expected performance improvements from implementing IIoT across the applications in the chart below, on a scale from 0 (no improvement) to 100 (revolutionary improvement).

Responses to the question: Where do you expect to see the  biggest performance improvements from implementing IIoT in your company?
Responses to the question: Where do you expect to see the biggest performance improvements from implementing IIoT in your company?
We see a consistently high level of response across all applications, averaging in the 60s out of a top possible score of 100.The applications were:
  • Analytics of machine and process performance: An understanding of every machine and process in your production, through IIoT sensor data, can reveal exactly where improvement can be made
  • Execution of orders on the shop floor: IIoT solutions help to ensure a better understanding of production all around, leaving less room for errors and miscommunications
  • Logistics and warehouse operations: IIoT data can give you a better handle on your operations, leading to improved logistics
  • Asset uptime through preventative maintenance: If you can predict equipment failures before they happen, you can save yourself costly downtime
  • Machine-to-machine communication: Connecting assets together allows each to incorporate external data for optimized productivity
  • Asset tracking: With IIoT solutions, you’ll have all the info on all your assets whenever you need it
  • Energy and use optimization: Just as the IIoT can shine a light on production weaknesses, so too can it shine a light on energy and use inefficiencies

No matter the application, be it asset tracking, logistics, energy optimization, production analytics, or otherwise, manufacturers expect the IIoT to improve that application in a significant way.

In engineering.com’s Research Report: Adoption of Industrial Internet of Things (IIoT) in 2018, we delve into all the responses and insights of this survey of 226 manufacturing professionals.

The Most Successful Production Environments are also the Most Optimistic About IIoT

We asked manufacturers to rate themselves in terms of their current production success, to get an idea of the room they felt they had for improvement. They scored themselves from “terrible” to “excellent” across several production measures, such as their ability to minimize production costs, hit ROI targets, manage last-minute changes, and more. The results are in the following chart:

Responses to the question: “How would you rank your production success  in terms of performance for the following outcomes?” (outcomes listed in full report).
Responses to the question: “How would you rank your production success in terms of performance for the following outcomes?” (outcomes listed in full report).
Though the results skew towards the “excellent” end of the spectrum, most of the responses place manufacturers’ production success in the middle of the pack, between “so-so” and “good.” Clearly, there’s plenty of room for IIoT improvement.

When we compare these results with each manufacturer’s level of IIoT deployment, we get a very interesting graph:

Cross-tabulation of results from the following questions: How would you rank your production success in terms of performance? and At what stage is your company in terms of IIoT deployment?
Cross-tabulation of results from the following questions: How would you rank your production success in terms of performance? and At what stage is your company in terms of IIoT deployment?
The line of best fit (red) is suggestive of an interesting correlation: the companies that are furthest along in implementing IIoT solutions are also the companies with the highest level of production success. We are not suggesting that IIoT is the cause of higher reported performance. Instead, these data may suggest that the companies with the highest production success are those companies that are most willing to adopt new approaches like the IIoT.

The Stages of IIoT Deployment

The graphic below tells us what stage of IIoT deployment manufacturers consider themselves to be in, broken across several IIoT activities.

Responses to the question “at what stage is your company in terms of IIoT deployment with regards to the following activities?”
Responses to the question “at what stage is your company in terms of IIoT deployment with regards to the following activities?”
For all activities, around 80 percent of survey respondents reported being engaged in some stage of deployment, whether they’re merely evaluating alternatives, planning and piloting, or in partial or full production. It is interesting to note that these three stages are roughly equal both within and across categories.

To discuss why this might be the case, let’s quickly break down each activity:

  • Gathering and analyzing production data to seek performance optimization: This activity tops the list in terms of overall implementation, and with good reason: if the IIoT is to be useful, it must offer an improvement over current production practices. Clearly, the first step in implementing IIoT solutions is to gather and examine production data such that you can determine areas of improvement. How can you do this? Well…
  • Instrumenting production equipment with sensors: If you really want to understand how your operation works, you need to collect data. And to collect data, you need sensors. Sensors are the backbone of the IIoT, the valves through which all your valuable IIoT data must flow.
  • Identifying predictive maintenance opportunities: Predictive maintenance is one of the biggest promises of the IIoT. Instead of expecting failures and swallowing the downtime they engender, put your IIoT data to work and fix those failures before they happen.
  • Developing dashboards that can be interrogated for equipment performance: Your sensors understand data differently than you do. Dashboards are how you can translate those streams of bits into charts, graphs, and numbers that you can understand at a glance, and probe to obtain a deep understanding of your equipment.
  • Implementing exception reporting for machine performance: Understanding your equipment data allows you to know not just how it should be, but how it shouldn’t be. With IIoT solutions, you can flag every anomaly.
  • Connecting equipment together for M2M communication: Machine to Machine (M2M) communication means each piece of your equipment will not be an information silo. By enabling equipment to share data with other assets, you can optimize the performance of your entire production.

Many of the activities described above are highly interrelated. Connecting equipment and collecting sensor data unlocks almost every IIoT opportunity you could hope for, which explains why the numbers across all activities are so similar: if you’ve got one application underway, the others are within reach.

Konecranes Uses IIoT for Predictive Maintenance

A Konecranes heavy lifting device. (Image courtesy of Konecranes).
A Konecranes heavy lifting device. (Image courtesy of Konecranes).
For a concrete example of the effectiveness of the IIoT, look no further than Konecranes, a provider of heavy lifting equipment. Konecranes has implemented and benefited from IIoT solutions.

Over the last several years, Konecranes has installed sensors in crane components and machine tools and connected those sensors to a network. With this system in place, Konecranes can provide detailed information to help manage these expensive capital assets more economically and over a longer life.

For example, by connecting their assets to Siemens’ MindSphere IoT platform, Konecranes has used its enhanced analytics to determine things like:

  • Optimization techniques: “By training operators on the second shift not to use the emergency brake for operations, they could extend the crane’s life by 30 percent”, or
  • Actionable intel: “Your hoisting brake is nearing the end of its lifetime and needs to be replaced”

Pilot Projects for IIoT Provide a Low-Risk Path to Implementation

Looking at the survey results, it’s hard not to get excited about the potential of the IIoT. Even if you remain skeptical as to how it can benefit your operation, you owe it to yourself to test the waters. Look into possible IIoT solutions, partners, and opportunities, and try to start a pilot project to better understand what’s involved and what you can gain.

To read the full engineering.com research report, click here.

This article and the research it references has been sponsored by Siemens AG. They have had no editorial input to this article. All opinions are mine. – Michael Alba

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