Non-CAE simulation? Kineo explains

My first car was a used Chevy Chevette. Go ahead and giggle –you’re right– and when you’re ready, let’s talk maintainability. I thought the car had it all: AM/FM radio and tape deck, air conditioning, a hatch to carry all of my stuff … My little American dream machine. Then, since I was a newly graduated engineer, I decided I needed to learn how to do all of my own maintenance. After all, how hard could it be to change the oil, rotate the tires and … stuff? I’m a city kid; car maintenance wasn’t something that came naturally (and MIT certainly didn’t cover this) so I figured that a Chilton Auto Repair Manual could tell me all I needed to know. I scoped out spark plug gap tools at the local NAPA auto parts store, scoured Sears for tool sets and tried to follow the instructions in the book. I skinned my knuckles taking out the spark plugs. Couldn’t reach the oil filter. Had to move things out of the way just to check the oil. It was probably amusing to watch, but I wasn’t happy — maintainability was clearly not at the top of the list of considerations for the Chevette. Manufacturers today look at things differently. Can the driver’s seat and dashboard be installed, given the size of the door and windshield openings? Can we mount the windshield wiper motor in the space available — and can a repair tech reach it for repairs or replacement? How should a welding robot be programmed to maximize efficiency while staying collision-free? Automotive, aerospace and other industries use path planning algorithms, a type of simulation that has nothing to do with loads and deformations, to maximize efficiency and minimize collisions. I hadn’t realized how complicated this was, even with my Chevette drama, until a call several weeks ago with the Siemens Kineo team. You may remember that Siemens acquired Kineo in late 2012 after partnering for a several years. Kineo makes software (as end-user apps or components embedded in other software apps) that optimize paths to  make both human and machine work more efficient. Kineo’s Margarita Pariente told me that Kineo’s path planning tools are used in all sorts of applications: planning paths to program robots; studying the ergonomics of a particular process; checking for collisions during assembly or disassembly; and programming coordinate measuring machines. Kineo is embedded in Siemens PLM’s NX, Tecnomatix, and Teamcenter products and in similar products sold by other software vendors; adding together Siemens, standalone and other ISVs, Ms. Pariente estimates that more than 200 companies use Kineo’s path planning algorithms. I’m used to the kind of simulation that uses meshes to determine deformations; checking for collisions is just as complex and compute intensive. I didn’t quite understand why form and fit simulation was necessary since CAD packages all can do interference detection, so I reached out to a couple of contacts in industry to get their take on it. One told me that they use Kineo CAM in assembly planning: yes, they start with interference detection in their CAD modeling process, but that’s not sufficient. They need to make sure that a product can be assembled in ways that reduce physical effort and avoid repetitive motion injuries. Using Kineo’s Human Path Planner, a production planner selects the part in a CAD model, specifies the task and any human kinematic constraints (say the height or reach of the average worker) to optimize the task. If there are collisions, the Human Path Planner suggests alternatives. Robotic processes can be just as complex — more so, if you factor in the speed at which robots operate. In this case, Kineo’s path planning algorithms let planners assess whether a design is manufacturable and perform mounting and dismounting simulations. Ms. Pariente adds that Kineo is used to automatically compute robotic tasks, for off-line and onboard programming, reducing and optimizing robot cycle times. I was especially interested in the AEC and shipbuilding applications for path planning. Ms. Pariente had an example of a nuclear power plant, with very tight spaces. Downtime means lost revenue so maintenance is carefully planned, as is every imaginable emergency scenario. Workers must quickly gain access, do their jobs and get out. Kineo’s solutions find the quickest, safest paths for workers and equipment. Ms. Pariente is right: this can translate into time, money and resource savings. Kineo used to say that it can do in 2 minutes what otherwise would take 2 days. Speed matters, no doubt, but maybe this is they key: one of my contacts told me that “we’ve moved from reacting to predicting”. When you predict, you can mitigate; all you can do when you react is … react. Image courtesy of Siemens PLM.