Mike Marra holds a PhD in electrical engineering and works as a system engineer at Funai.
When Funai bought Lexmark’s inkjet-related technology and assets in 2013, Mike joined an internal group to help facilitate the transition, educating Funai engineers with various inkjet printer project details.
Historically, Mike has been a MATLAB user. MATLAB is a mathematical tool package that allows you to generate arrays of data, and then to plot and analyze them. MATLAB runs off a scripting language, so for Mike to use MATLAB he had to write specific programs to read his log data.
One advantage of Initial State, Mike explained, was that he didn’t have to write separate programs to read his log data files. He simply uploads the files and can immediately start looking for data anomalies.
As an example, the stats function in Waves provides Mike signal stats when he looks at inkjet printer paper feed data. Mike can look at the wave graph to understand how accurate the hundreds of tiny movements he makes are over time. In the below screenshot, Mike can see the time ranges in which most errors occur.
While Mike will often start in the Waves tool to find areas of interest, he’ll switch over to Lines to better understand the profiles of velocity the paper went through, accelerating and decelerating over time.
I asked Mike what additional features he’d like to see.
For one, he’d like to see a split-screen or multiple tab view option. In two days, Mike had uploaded dozens of data sets and subsequently had dozens of windows open. He’d like to more easily sync up time scales and view his velocity profiles alongside each other.
Secondly, Mike wants to share the data with his colleagues. Many of his Japanese coworkers use other tools, and he thinks that if he were able to easily share his visualized data that other engineers within Funai would adopt Initial State, streamlining log data debugging efforts across the company. [Note from Jamie – this feature will be released very soon!]
Finally, Mike would like to annotate or somehow add comments to the visualized data, so that when he shares it with his coworkers he can more clearly position the data.
Mike, thanks for chatting with us! You’re a valuable Beta user and we look forward to working with you down the road.