Manufacturers Often Miss the Benefits of Data Analysis

Robotics Business Review

It’s no secret that the world of manufacturing is on the edge of a large transformation, thanks to advances in artificial intelligence, robotics and the so-called Industrial Internet of Things. But getting a more valuable return on their investment and getting good data analysis from equipment still takes a lot of work.

“A lot of the customers we go into definitely have automation, but right now, those customers are doing ‘islands of automation,’” said Sam Hoff, president of Patti Engineering. Getting those companies to move from an Industrial 3.0 to a 4.0 world requires more data analysis, as well as connecting to the cloud and higher-level systems, he said.

Sam Hoff Patti Engineering, will speak about data analysis at LiveWorx

Sam Hoff, Patti Engineering

Creating strategies around ROI and better ways to measure a large automation investment is one of the topics that Hoff and three other panelists will be discussing at the upcoming Robotics & AI Summit @ LiveWorx, being held June 18-19, 2018, in Boston.

Hoff, a member of the Control System Integrators Association, will join Asuman Suenbuel (director of robotics & IoT for SAP), Alex Shikany (vice president, AIA) and Doug Olson (president and CEO, Harmonic Drive) on the June 18 discussion around implementing automation and measuring ROI.

Creating a business case around a new automation project has to make sense, Hoff said.

“If you’re going to spend $10 million to put in a system and you’re only going to get $500,000 of gain, there’s no reason to do it – that’s just over-automating and not being smart about it,” he said.

Beyond the initial calculations on how much money a system will cost, companies often miss out on ways that the equipment can be improved, which requires cloud connectivity and better data analysis.

Cleanup needed for data analysis

“One of the problems with manufacturing data right now is that it’s not clean,” Hoff said. “Manufacturing data is dirty – somebody has to clean up the data and really present the data in a usable way.”

Currently, a lot of these systems are designed to control the automation and robots. However, they aren’t designed to give that data to a higher-level system to be analyzed. Hoff said that an expert on the machine at the operational level – someone who knows it and can clean up the data – needs to do this before it moves to the other systems or even a data analyst sees it.

Hoff said the supplier of the equipment is often the best option for providing this data analysis and/or cleanup.

“I don’t care how much training you give to the end user – they’re not going to know the equipment as well as the supplier,” he said. “This supplier may sell 100 machines, and he sells it to your company – that’s one of 100 machines. You have no way of comparing the performance of your machine to the other 99 machines [the supplier has] previously sold. If [the supplier] is getting data and analysis back from the field, and you’re allowing them to do that, now they can compare your performance to the other 99 machines, and help you improve.”

Utilizing the data from other systems connected to a cloud environment can improve efficiency and performance, as well as provide predictions about maintenance, Hoff said.

He gave an example of an automotive manufacturer that was sending their data to the supplier via the cloud, and the data analysis returned with a prediction that a drive on a robot was about to break. Unfortunately, the automotive manufacturer didn’t trust the prediction, until the drive broke down a week and a half later, Hoff said.

“Suddenly, they had instant credibility and they’re listening to everything they had to say,” he said.

Manufacturers also continue to have fears over cyber-security when it comes to connecting their data to a cloud-based system, Hoff said. Many IT departments within the manufacturing space have a fortress mentality when it comes to protecting their data, which never works, he added.

In the end, however, the benefits of data analysis, performance and predictive maintenance should outweigh those concerns

“Industry 4.0 is coming – I think you have to educate yourself on how you’re going to put data up to the cloud and analyze it,” Hoff said. “If you don’t you’re going to be behind.”

Hoff will speak at 2:30 p.m. on Monday, June 18, on the panel titled “ROI Strategies: Implementing Automation and Measuring ROI.” Register here to attend the Robotics & AI Summit.

The post Manufacturers Often Miss the Benefits of Data Analysis appeared first on Robotics Business Review.


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