A variety of local manufacturers attended this event, to ask questions and to interact with the industry experts in breakout sessions. The attendees were from industry areas such as automotive, chemical, electrical maintenance, electronics and one of the nation’s largest food and beverage manufacturers.
At this event, FactoryEye showcased their Industry 4.0 prowess and discussed best practices for manufacturers implementing their own smart manufacturing solutions. The industry panel of experts discussed important topics such as: how sustainability affects your bottom line, tips for obtaining project financing, ways to attract millennials to your workforce, and how to brace for the impact of the silver tsunami of workers leaving manufacturing.
Manufacturers Realize that they Need to Begin Implementing Smart Manufacturing on the Shop Floor
Jim Brown, president and founder of Tech-Clarity kicked off the event as the keynote speaker and shared a recent research study outlining benefits that manufacturers can gain from smart manufacturing solutions.
“One of the things we did in the manufacturing industry, is that we stepped down from this higher-level view of a digital transformation, and we asked a wide variety of manufacturers how important you think the implementation of smart manufacturing or Industry 4.0 is to the long-term success and profitability of your manufacturing business?” Brown said.
“When 19% of those surveyed say it is critical and another 28% think that is it really important, then what we are seeing is that this is not just another trend that is going to come and go. But people are starting to say, if you don’t get this next step in Industry 4.0, you are not going to be ready for what comes beyond that and the continuation of this process.”
Real-time Data Analysis Leads to Improved Machine Maintenance, More Efficient Workflows
One of the key benefits of implementing Industry 4.0 into the manufacturing process is having the ability to track what is actually happening on the shop floor in real-time.
Jake Hall from Feyen Zylstra, (also known as the Manufacturing Millennial) said, “We worked with one manufacturer that had Individual machines that weren't tied together to a central network. So, they had all these machines that were producing their own components and parts, but the manufacturer never knew where their bottleneck was within those processes.
“When were those machines down? How many parts did they actually produce per hour? We were able to implement an inductive automation that allows them to better track every single individual machine and then build a network that allows them to act on that data, to address issues that are doubt," he added.
When asked about the different ways that manufacturers can improve productivity by implementing smart manufacturing, Tim Stuart, president of Visual Decisions said: “When looking at maintenance issues, manufacturers ask, ‘How can you provide autonomous maintenance instructions to the operators on the day that they're supposed to? How can you get a machine that's currently down, up and running faster again? How can you prevent that downtime from happening in the first place?’ ”
Stuart continued: “Whether that's through normal, preventative maintenance activities that are informed and optimized by the data or whether it's through predictive maintenance technologies from an operator perspective of producing parts and so forth, how do you give them the proper work instructions? The goal is to eliminate variation from the process as much as possible that will also help quality as you go through and produce more.”
Another topic discussed was accurate measuring of the scrap in production processes. Nancy Finnegan, vice president of sales, FactoryEye, said, “One common theme we see across manufacturing is how do we measure scrap and rework. We see that as one of the most manual areas of capturing data in the industry throughout the production process.
“It's very interesting,” Finnegan continued. “One company we worked with had recorded their scrap as 3% for almost two decades straight. It was almost folklore. This is what our scrap is. But when we started to pull in those data parameters, we really started to understand that it was nowhere near 3%, but closer to 8%. Having access to real-time data helped them to correlate the data between what they thought they were producing and what they were actually producing and the actual quantity of their waste.”
Finnegan added, “And from there, we really started to analyze, which processes needed to be reworked and how they could bring that scrap back into the bottom line!”
