4 Steps to Integrate Industrial Robots With Your Digital Stack

Do you use robots on your assembly line or in your warehouse? Industrial robots are a fixture in manufacturing contexts, and have been since the 1970s and 1980s when automation was a new concept and the future of robotics automation was still a blank canvas.

Today we can see a little more of the picture, but there are still huge unknown parts of the canvas yet to emerge. What we do know, however, is that building a successful business model in the manufacturing industry will require strategic integration of robotics with your digital stack.

Recently, the president of the Upstate Alliance, an economic development agency in our home area, cited a stat that tasks performed by robots are expected to increase by 10-25% over the next 10 years.

As robots become more autonomous and technology offers increasing opportunity for innovation, companies have unprecedented opportunities to boost efficiency and productivity. In fact, Deloitte lays out six reasons it makes sense to integrate industrial robots with digital processes and automations:

* Increased efficiency
* Reduced error
* Improved safety
* Collaboration with humans
* Faster delivery rates
* Ability to operate in environments inaccessible to humans

We would add a seventh reason: improved business insights. As you collect data from the sensors on your robots on your plant floor or in the warehouse, you can use that information to make better decisions about cost, production, supply chain, and logistics.

The real question is this: What does a manufacturer with robotics in place need to do to maximize their potential in an IIoT environment?

If you’re ready to integrate your industrial robots with your digital stack, here are the steps we recommend.

1. Digitize Technology

Start by identifying the gaps in your technology and determining where you need to increase your capabilities. For example, you may have outdated equipment or insufficient data storage, making it difficult to add new technologies to your wheelhouse. Your digitization strategy should cover big picture goals for technology and automation, and then narrow down to identify which specific elements you need to invest in. These may include:

Hardware

Retrofitting old machinery with sensors and cameras for automation can be complex and costly, but it also opens doors of opportunity to gather and analyze data you didn’t have access to before. That data forms the basis for any automation or analytics endeavors you want to tackle in the future, and the return on investment is nearly always well worth it.

Protocols

Smart robots hold enormous potential, but they also often require new operational protocols. You may need to develop protocols for various use cases and assess for compatibility.

Connectivity

Data must flow reliably from the robot’s sensor to your software platform, and it you need to be sure you have the power and bandwidth to handle the load.

Data storage

With new streams of data flowing in continuously, you will need a comprehensive storage solution that integrates all the parts of the system while also keeping data accessible and secure.

Of course, you can’t slap a cheap solution on your legacy equipment and expect miracles, but the right tools and platforms will position you for exponential gains. At each step in your manufacturing process you will find opportunities to digitize, and each one of those opportunities represents the potential for greater efficiency, increased productivity, and higher profit.

2. Harvest Data

With your hardware and software in place, the next step is to harvest data from your robots to support and improve the decisions you make. The robots on your shop floor can provide a wealth of information to track, such as:

* Performance data
* Yield/throughput
* Supply chain dynamics
* Profit-per-hour
* Operations data

Sensors and cameras can measure things like temperature, vibration, machine performance, and product flow much more efficiently than human workers could. They can also send and receive data more quickly, making incremental gains possible without increasing the burden of data collection for your human employees. The goal, of course, is to use this data to improve performance and profit over time.

3. Integrate Analytics

With smart robots, you can identify production anomalies, alterations in cycle times, and maintenance needs based on the data collected. Here are just a few examples of insights you can pull from your data to make your plant more efficient (read an in-depth discussion from McKinsey & Company here):

* Track production data to identify hidden bottlenecks in your production lines
* Monitor yield/throughput of assets and optimize parameters to make those assets more efficient
* Manage equipment by monitoring performance and identifying anomalies that indicate a need for maintenance—before the equipment goes down
* Use data modeling to identify performance trends and increase earnings over time

It’s not enough to collect data and create reports. You need to know where and how that data will be most useful in reaching goals like higher profit, fewer errors, increased production, and improved safety measures. McKinsey reports that one company was able to increase earnings by 55% using the data they collected to create usage and performance models that identified areas for improvement.

As you integrate your analytics strategy with your robotics assets, you’ll see an uptick in the data flowing in, as well as in the insights you capture. 

4. Use Data to Optimize Operations

With the first three steps in place, you’ll be in a good position to optimize your robotics performance using newer technologies like AI, IoT, and machine learning. This is where the possibilities really open up, and we will likely see even more impressive capabilities evolving over the next few years. Here are some of the applications available right now:

Commands

Create protocols for robots without labor-intensive hands-on interactions. Send commands digitally to keep robots functioning at full capacity during peak times, adjust speeds based on production cycle needs, or execute pick-and-place operations.

Collaborate with human workers

Collaborative robots accounted for 4% of robots used in industrial contexts in 2015. That may not seem like much, but it’s a number that is growing rapidly as robots are increasingly integrated with AI technology. They are designed for flexibility so they can work with humans, and machine learning platforms allow them to share information so they can “learn” from one another.

Increase output and efficiency

As discussed above, data collection and analysis can identify trends in performance and facilitate incremental increases in both output and efficiency. You can also predict maintenance needs before they cause downtime and the resulting productivity losses.

Adjust processes based on input

IoT sensors make robots more aware of their surroundings and with the right AI platform, they can adjust processes based on that data feedback. For example, a robot could stop or slow when a human worker is in the vicinity, pause production if a component is malfunctioning, or manage production outputs for the most efficient use of energy.

Conclusion

With the advances we’re seeing in both AI and robotics technology, the manufacturing plants of the future may look very different than those we operate today. Robots and humans will work side-by-side to achieve the highest profit and productivity, and robots will become increasingly autonomous as AI and machine learning enable them to adjust processes while also reducing error and maximizing efficiency.

Still wondering whether digitization of your robotics assets is worth the investment? Digitization is becoming the new standard in the manufacturing industry. Ultimately, the companies who embrace the new technology most effectively will be the ones who enjoy the competitive edge that drives them to the top.

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