3 Ways IoT in Manufacturing Boosts Productivity (And a Roadmap to Get There)

By: on February 13, 2019

Time moves forward and Industrial Internet of Things (IIoT) technology gets cheaper and less complex. Sensor-based real-time monitoring of equipment is no longer only for giant manufacturers—even small and midsize businesses (SMBs) should be ready to adopt.

But examples of valuable IIoT benefits—such as boosting production quality, optimizing equipment effectiveness and enabling proactive maintenance—can be found just as often as caveats and warnings in implementing a strategy using connected assets.

So even though the majority of manufacturers understand the value of an IIoT strategy in manufacturing, without a clear roadmap, many hesitate to implement the technology and fall behind more advanced competitors.

Gartner says IIoT implementation success is unpredictable because companies often fail to define important metrics to track and don’t use the technology to continuously improve. (Full content available to Gartner clients.)

Here, we use Gartner guidance and insight from a IIoT expert to offer specific use cases and explain how to confidently create your own path to success.

3 Valuable IoT Use Cases in Manufacturing

Every IoT journey begins with a specific end goal in mind, so the metrics you’ll need to track come directly from the problem you need to solve, and three common use cases for manufacturers aim to optimize some of the most important production KPIs:

Understand and Reduce Cost of Poor Quality (CoPQ) 

Represents the revenue that you would have made if your production equipment was in perfect condition at all times.

Maximize Overall Equipment Effectiveness (OEE)

Factors in availability, performance and quality to quantify how efficient a manufacturer performs compared to its full capacity.

Enable True Predictive Maintenance

With sensors attached to your assets, you can automatically stream condition data to your production and maintenance systems, notifying you when a failure is imminent.

 

Barriers to Success for IoT Manufacturing Projects
Founder and CEO of Crate.io Christian Lutz helps companies—mostly manufacturers—utilize industrial IoT projects to actually leverage the vast amount of machine data they already possess and use it for real improvements to CoPQ and OEE.

Lutz says the complexity of integrating this technology is significantly lower today, as vendors and clients work out proven use cases and integration best practices. Sensors are affordable and detect a wide range of conditions, they’re all IP based, you often don’t need a gateway and you can just place the sensor and connect it to a cloud service,”

“All of the stuff that was complicated only two years ago is now common,” Lutz says. “For these companies, it’s easier than ever and not expensive.”

While costs were the primary concern for 16 percent of a recent Gartner survey, overall, complexity of implementation was the most common reason (34 percent total) manufacturers say they haven’t invested in an IoT strategy.

Hesitate no more! Now is the time to adopt this technology and experience more efficient, reliable and cheaper production. This roadmap will help you get there, step-by-step.

4 Phase IoT Roadmap to Boosting Productivity

Before you start: Avoid adopting too many features. 

Lutz warns companies against adopting more IoT technology than it needs and getting lost in the possibilities. “The right approach is to start with a very concrete business use case you want to achieve, find an objective that is measurable and will have a positive impact on that goal,” he says.

Phase 1: Discovery

This first phase of the IoT roadmap includes defining your project in several ways to make sure everyone involved understands the objective and can approach problems from a comprehensive perspective. Gather your stakeholders and answer the following:

  • What is the specific challenge or problem you need IoT technology to solve?
  • What metrics can you use to track progress on that objective effectively?
  • How many machines do you need to connect to get that data?
  • Will you use wired or wireless connections?
  • What types of sensors do you need to measure the appropriate conditions?

 

Types of Smart SensorsTypes of Smart Sensors

Phase 2: Configuration

This second step is where you create the infrastructure for the network, Lutz says, including the data structure (i.e., how the data will be formatted as it comes in) and the applications you need to fulfill the business case.

For example, you should create a dashboard to view equipment condition information at-a-glance and alerts to notify maintenance techs when sensors detect a problem.

CrateDB Data Management 

 
Users can review notifications over time, like this system utilizing CrateDB data management, to identify common problems you can address for continuous improvement (Source)

 

Phase 3: Continuous Improvement

The key reason you need to visualize this important machine data is to track progress over time and continuously improve metrics that indicate success for this particular project, whether it’s increased quality or reduced downtime.

“You do this for a while and you can see different things: Maybe this process doesn’t make any sense and it’s contributing to bad quality. We need to enrich it somehow,” Lutz says. “Or you may say, ‘Actually we’re missing this component to really tell what’s going on.’ Then you can validate that and improve it.”

PRO TIP: Find your Domain Specialist. 

Collecting data and streaming it to your system in real-time is simple straight out-of-the-box today, Lutz says. But making practical sense of the information requires an actual human.

Identify a Domain Specialist in your organization who has the most knowledge about a particular process or asset. This person is vital to understanding how the IoT project will impact the process and the nuances that help the team make informed decisions.

“No IT company can know those details,” he says.

Phase 4: Evaluation

In the first three phases of the IoT roadmap, we discovered the goal and the requirements to get there, implemented the connections and applications to gather data and established the plan to track improvements.

The last step asks manufacturers to evaluate the results of implementing data-driven solutions to understand its impact and make any changes, all with the key objective in mind.

This process feeds into continuous improvement.

“Things evolve so quickly, so what worked for you last year might have taken five guys coding for three months, costing a lot of money,” Lutz says. “So it’s better to do this on-the-go and continuously improve over time.”

Next Steps to Start Your IIoT Project Confidently

You have no more reasons to hesitate about an Internet of Things strategy in manufacturing. The hardware and software is affordable for smaller companies, the use cases and benefits are clear and with these steps you have the path to success:

  1. Determine your objective and adopt only the software and hardware you need to fulfill that business case
  2. Establish the strategy and ensure all stakeholders understand the goal of the implementation
  3. Work with your site managers and IT team to build the infrastructure and collect data in a usable form to view on dashboards and generate alerts
  4. Analyze data over time and utilize the knowledge of a domain specialist to understand the true causes and solutions for production problems
  5. Review the impact of prior solutions so you can improve over time and allow your production to evolve using data

Before kicking off your new strategy, we can help you prevent any cyber security risks using networked devices or protect your assets from intrusions.

Finally, any IoT approach need a platform to analyze data—You can start your search for the best technology providers with our list of manufacturing systems along with hundreds of user reviews. Or call (844) 680-2046 for free help from our software advisors.

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