Elemental Machines uses the cloud, Internet of Things and machine learning technology to model and understand how complex chemical and biological processes in a laboratory or factory work and help obtain consistent, repeatable results, saving companies time and money. It pulls data out of machines that are currently not connected to anything, collatees it with data from equipment that is already being monitored,. analyzes what is happening in real time and displays it on dashboards. The Boston-based startup, which has so far raised $11.5 million in angel and venture funding, has 100 customers ranging from small startups to big pharmaceutical, petrochemical and food manufacturers.
« We are building the hardware and software tools that allow companies to model and understand how complex processes works and very rapidly zero in on what went wrong or right, » says CEO Sridhar Iyengar, a serial entrepreneur. Chemical and biological R&D and manufacturing is extremely complex, as there are myriad variables that can impact the success of a production run. « If things are done correctly there is no waste and high yield and it helps prevent drugs and other products from being recalled. »
Think of it as a Fitbit for machines and factories that can look at external variables and prevent unwanted butterfly effects. Take the case of a synthetic biology company, one of Elemental Machine’s customers. When it grows cells it heats warms them to 37 degrees celcius and the flasks are gently shaken to both blend and aerate the cell mixture. The company was consistently getting bad results and couldn’t figure out why, says Iyengar. Finally, it discovered that a tiny screw was loose in one of the machines charged with shaking the mixtures. The shaking vibrations and the rate of aeration was a little bit different so the cells grew at a different rate, expressed themselves differently, impacting the purity rate « It took them months to figure this out, » says Iyengar. « Now they are using our technology to measure all the variables that may affect their yields and outcomes. »
Earlier this month Elemental Machines announced that it is partnering with Perkin Elmer to allow scientists, as well as lab and facilities managers, to access information at any time from a computer or mobile device and be notified of potential problems when conditions in a lab change.
Elemental Machines started by focusing on helping R&D laboratories control variables but has since branched out into manufacturing. One of its manufacturing customers, a materials science manufacturer, was not measuring temperature, humidity or light in the areas where it was mixing chemicals. « Turns out the micro climate made a huge difference, » says Iyengar. Now the manufacturer is using the startup’s technology to measure those elements and analyze the data.
Iyengar sees many more applications for the technoloyg.. « Now that we have a way to collect and analyze all of this data it allows us to generate a numerical representation of quality and use that to train our models on the way the process is actually run ,» he says.
While it is still early days Iyengar says he believes it will be possible to develop a system for R &D trials and manufacturing that would work in much the same way as Waze, a GPS navigation software that works on smartphones and tablets that provides drivers with turn-by-turn navigation information.
Elemental Machines’ «Waze for factories» could prove crucial not just to traditional R&D labs and manufactuers but to a variety of emerging fields where precise and repeatable results are crucial such as personalized medicine and next generation materials such as lab-grown leather or meat, he says.
