Manufacturers use SensrTrx Manufacturing Analytics to easily collect actionable data from the shop floor and display it in dashboards that anyone can use.
SensrTrx automatically collects data from machines, contextualizes it, and delivers it in actionable dashboards.
Improve OEE, downtime, quality, scrap & more by using simple centralized dashboards that only take hours to set up.
SensrTrx provides data from machines on customer shops floors. Everything from software to hardware – in less than 7 days.
See how Versatech used SensrTrx to increase OEE by 30% and significantly cut their overtime costs in this case study.
SensrTrx is an affordable manufacturing analytics platform designed to collect and display actionable data from the shop floor. Our solution helps manufacturers easily deliver more efficient processes, improve quality, and assert greater control of operations. Using this data, manufacturing businesses can increase machine availability, productivity and quality to directly increase profitability without complex software or the help of IT.
Reduce scrap rates and improve operations
Automatically calculate and review OEE
Quickly identify bottlenecks & other issues that affect performance as they happen
Track & identify costly downtime and change over
As crazy as it sounds, manufacturers that move towards more and more automation often start noticing a strange problem. They begin missing the benefits of non-automated processes and realize that they may have actually relied on manual human efforts more than they may have realized on the surface. For those that often read our blog, it may come as a surprise to hear us touting the benefits of anything manual vs. manufacturing automation. However, the truth is that simply automating manufacturing processes, cells, or machines does not inherently makes things better or more cost-effective.
Manufacturing automation requires good data to work properly, and in most cases, more data than you had before. This is because — whether you knew it or not — humans were actually collected data all along. They just weren’t sharing it with anyone or storing it anywhere…
One of the hottest buzzwords in any industry right now is artificial intelligence. In fact, trillions of dollars will be made by businesses over the course of the next decade who leverage this world-changing technology to disrupt their respective spaces. It offers the core solution to intimidatingly large data and complex ecosystems with revolving variables. It is being viewed by many as a silver bullet to existing industry problems. Unfortunately, these solutions mostly aren’t here yet – for any industry – and smart businesses are forced to proceed forward with caution.
The manufacturing space is no exception to this phenomenon. Artificial intelligence and machine learning in manufacturing are talked about at every industrial conference; yet implemented on of very few actual shop floors.
This ground swell would have you believe that this industry is on the verge of having every major manufacturer equipped with a fully-functioning smart shop floor; complete with Watson writing songs with Bob Dylan in the corner. Dare I say that this isn’t the case?
The Worst Way To Collect Machine Data I have the benefit of having seen how thousands of manufacturers collect machine data. Everything from the most efficient manufacturers to the least. As you can imagine, I have seen a lot of strange stuff, and a lot of really “interesting ideas” along the way. As a whole,[…]
Illinois manufacturer, Versatech, recently underwent a project to reduce their reliance on overtime work. A major component of the excess overtime labor that they identified was related — directly and indirectly — to a reliance on paper tracking and manual processes. Getting off tracking and paper, and a reliance on spreadsheets would allow them to[…]
Recently Versatech underwent a project in order refine their ability to impact and improve manufacturing quality, efficiency, and performance. Versatech was able to use SensrTrx to look at downtime time and quickly solve issues as well as recognize negative trends inside the project. Versatech hoped that this new project would help them capture the data[…]
Versatech recently implemented a company-wide initiative aimed at using data to improve manufacturing performance and reduce reliance on overtime work. Their continuous improvement department was a part of this initiative and was able to successfully leverage their new centralized data to get off of paper and streamline processes. One of the biggest benefits for us[…]
Versatech recently sought to improve their ability to impact and enhance manufacturing quality, efficiency, and performance. Versatech CEO, Chad Hill, knew that further centralizing their manufacturing and machine data would allow the organization to improve operations and reduce their reliance on overtime work. Verstech understood that their paper tracking system and reliance on manual tracking left[…]
Recently, we finished a comprehensive case study with Versatech – a full service engineering, manufacturing, and consulting company – who recently launched a company-wide initiative to leverage data more effectively to reduce overtime and improve manufacturing production and efficiency. In this article, we’ll highlight their manufacturing engineering efforts, approaches, and results inside of the overall initiative. Manufacturing[…]
One of the biggest issues that manufacturers face is inefficiencies in their manufacturing lines. This looks like manufacturing cells with bottlenecks, unscheduled downtime, and inconsistent throughput. This is one of the first places that experiences lean manufacturing leaders look to cut costs and increase important metrics like OEE. The secret to reducing costs and improving[…]
The world of big data, AI, machine learning, and the Industrial IoT has become extremely convoluted. These innovative new technologies are now marketing buzzwords. What’s more, manufacturers are often being misled, confused, or intentionally tricked about what these technologies can and can’t do for them… now and in the future. GE and IBM do a[…]