What is continuous engineering?
Cooking has always been a bit of a challenge for me. Take using recipes for example. Recipes are straightforward lists of required things to combine together in a prescribed manner to create a new thing—the sum of which is greater and more delicious than its parts. Seems simple right?
Yet somehow when I try it, my results always vary—sometimes the result is edible; oftentimes it’s not, but certainly it never seems to turn out like the digital photos in my favorite online cooking magazines. Why are my culinary results not picture-perfect every time? Is it the ingredients, the things that go into creating the final thing? Is it my methods? Did I follow the wrong sequence in the process? Or is it my tools—utensils, mixer, stove or oven? Is my thermometer not reading out the right data? I suspect that the answer is that the whole is only as good as the sum of its parts, the skill of the cook and the tools that are used.
Engineering those "wouldn’t it be cool if" scenarios
A recent tweet about a robotic chef caught my eye. Yes, that’s right, an electronic wonder product that can ingest recipes from the Internet, literally take raw ingredients, and using robotic appendages prepare a meal worthy of a five-star restaurant. The promise is, this robot can consistently achieve all the culinary magic that I cannot muster.
The robotic chef also represents a unique example of the way in which the Internet of Things is poised to literally change the way we live from day to day. Wouldn’t having my culinary creations be picture-perfect—and edible—every time be nice? And wouldn’t just having a network of apps and things creating these culinary masterpieces for me be nicer still?
Here’s an example. My smartphone checks my schedule and predicts when I will leave work. My connected car forecasts my arrival at home by sensing ignition and determining the traffic delay. And an app verifies my family’s schedules to see who will be eating at home. My smart refrigerator transmits data about what ingredients are on hand in the kitchen based on sensors and bar codes. Then with a search of the Internet, a recipe is found and my smart stove begins to heats up. My mixers mix, my robotic chef slices and dices, and voilà! A five-star, picture-perfect gourmet meal is waiting for me when I get home.
But comparable to my own frustrations and challenges in the kitchen, wouldn’t this culinary Internet of Things vision also have problems? What if the milk is bad? Can the robotic chef smell for me? What if my robotic chef gets stuck in an infinite loop of chopping broccoli? What if a label came off and my smart fridge couldn’t account for the right ingredients? What if the stove didn’t get the right data and set itself to broil instead of bake? What if a sensor didn’t turn off the mixer? Or what if my dog jumped up on the counter and grabbed the steak? My dog is very acrobatically talented when food is involved. This vision is equally dependent on all the various things to be correctly and safely connected together to produce meaningful results.
The Internet of Things is often portrayed as some kind of magical web of things that yields all sorts of fantastic experiences: cooking our meals, driving our cars, saving our lives. But the Internet of Things can only deliver real value when the things within it (such as the products, electronics, sensors, machines and data) are well designed, developed, tested and validated. And that value includes communicating the right data at the right time to produce the right results when connected together.
Much like cooking, the Internet of Things is really only as good as the things in it and the skill of the makers of those things. The whole is dependent on the parts. If the things themselves (the mechatronic parts and products) fail, what good is the Internet in the Internet of Things? Bad data, no data, unsafe data, uncommunicative or dead machines, disruptive sequences of events, failing products, connectivity loss, unsafe states and actions, misleading data and so on can all create unintended consequences across an Internet of connected devices. The making of the things themselves—how they are built, tested and interconnected is just as important, if not more so, as the exciting results we can envision from the Internet of Things.
Creating and connecting Internet of Things components
There are many organizations working hard at engineering the things in the Internet of Things to be better, safer and smarter than ever. They are doing this engineering by focusing on continuous engineering as a key enterprise capability that is fundamental for creating the connected products and systems at the heart of the Internet of Things. Several key maker-of-things activities take place in the Internet of Things:
- Unlocking and analyzing engineering data regardless of source to enable enhanced, more timely decision making to build better products
- Preventing rework and achieving high-quality, fast data by modeling physical systems, behaviors and testing through early simulation to find and solve issues earlier than ever
- Designing, planning and building components and leveraging product-line engineering to maximize reuse and deliver the right product to the right market
IBM introduced continuous engineering in 2014 as an enterprise capability to develop sophisticated electronic products that are expected to empower Internet of Things makers. Continuous engineering builds on the more than 25 years of experience IBM has offering solutions for systems engineering and embedded software development to the automotive, aerospace and defense, electronics, energy, medical device, oil and gas, and semiconductor and electronic design industries. These industries and the companies within them are the makers of the things that will form the crucial ingredients of the Internet of Things vision of the future. They are at the heart of creating the things that can enable the Internet of Things to truly meet the hype of “wouldn’t it be cool if” scenarios.
IBM continuous engineering for the Internet of Things is helping to deliver on the goals of working relationships between the Internet of Things and companies such as Jaguar Land Rover, Brockwell Technologies and Diagnostic Grifols:
- Jaguar Land Rover is leveraging continuous engineering from IBM to achieve 90 percent faster software validation for vehicle infotainment systems than was previously possible.
- Brockwell Technologies is achieving 40 percent faster development cycles than ever for defense systems.
- Diagnostic Grifols is accelerating time to market by 20 percent for medical devices.
Continue the conversation about continuous engineering and the Internet of Things. And comment here, follow me on Twitter or connect with me on LinkedIn.