Fero Labs has developed software to help certain types of process manufacturing plants improve quality output economically when given a random mix of feedstock. I wrote about the company last August—A Better Way to Control Process Quality.
They sent a new press release, and I must admit that I understood almost nothing in it:
Fero Labs, the only Profitable Sustainability Platform for industrial optimization, announced the release of their ground-breaking feature ‘ExplainIt for Live Predictions’ which expands a factory’s production knowledge in real-time. This advanced feature for cross-functional teams increases trust in AI predictions by disclosing real-time text explanations about abnormal factors influencing their live production.
There were way too many marketing-type phrases in there. Worst of all was the concept of “trust in AI predictions.” So, I asked the very patient publicist. She suggested that I talk with Berk Birand, Fero Labs Co-founder and CEO. And, I did. He was most helpful.
We caught up from my last article about their ability to use the huge data sets manufacturers have accumulated over the past decade using advanced statistical methods and “white box machine learning (ML)” to help engineers optimize their plants. Make them more profitable and reduce waste (sustainability). Therefore the “Profitable Sustainability” company.
Birand took me through an example that I could understand, since I had a customer in the 90s who did this sort of process.
Imagine a plant with piles of scrap steel in a yard. They have an electric arc furnace that melts all that disparate steel that will be poured out eventually to make their final product. Given that the feedstock has high variability as to the composition of the steel, the typical plant overdesigns the process to allow for variations. This, of course, is wasteful on the surface. But if the final chemical analysis shows that the output will not make the desired tensile strength or other spec, then the waste is even higher.
What if you accumulated the data (feedstock, process, finished steel) over time built a modern AI model? Its predictions could be used to drive profits, reduce waste, save time. But, would anyone trust yet another advanced process control system? We all know that models eventually goes out of whack sometimes and sometimes gets the wrong answer.
Here comes the “trust” part of the trust in AI model. They built an explainable model from the beginning. It can predict characteristics, say tensile strength of the mix because of chromium or carbon levels and so forth. Since we know that every model is wrong sometimes, they built in confidence levels in the prediction engine. Their AI looks at the material composition and suggests adding chemicals to the mix, but it gives an explanation and a confidence level. The engineer looks at the confidence report (I am confident in this prediction or I’m not confident in this prediction) and can decide whether to go with the AI or to go with gut feel based on years of experience.
He convinced me. Fero Labs has developed an AI engine that gives the engineer a level of trust in the prediction.
More explanation from the press release:
Expanding on Fero Labs’ white-box ML, which provides full transparency of Fero’s powerful machine learning models, the new ExplainIt feature provides a contextual explanation of anomalous factors involved in each live production optimization.
This type of analysis is typically addressed through linear Root Cause Analysis (RCA) tools. Unlike traditional methods, Fero Labs’ solution is non-linear, much like process operations, and delivers results in seconds rather than the hours or days typically needed. Traditional methods generally require the engineer to preselect a small sample of factors to investigate, which can introduce potentially misleading biases. Fero Labs’ software has the power to evaluate all relevant factors which improves insight and prediction accuracy.
Are you the type of person who is known for getting things done? Is yours the first name that comes to mind when someone in the organization needs a report written or a light bulb replaced? Is “no” a seldom used part of your vocabulary?
In other words, do you always feel busy yet not accomplishing the work that would most boost your career or inner peace?
When you feel the need to focus on the things that really matter needing a way to say “no” more—or better stop being the name everyone thinks of first—then you need to dive into Slow Productivity: The Lost Art of Accomplishment Without Burnout by Cal Newport (author of Deep Work, A World Without Email, Digital Minimalism, So Good They Can’t Ignore You, and more).
We know what productivity is relating to our production and manufacturing plants. But knowledge-worker productivity cannot be readily defined.
Influenced through reading about the Slow Food movement in Italy, Newport thought about how our decades long obsession with productivity has led to what he calls pseudo-productivity—busy-ness just for the sake of appearing to be, well, busy.
He will show you a few calendar tricks to help you say “no” or at least something like “I’d be glad to help if you see where on my calendar I could get to it.”
How do I get to Slow Productivity?
Do Fewer Things.
Work at a Natural Pace.
Obsess over Quality.
If you do what you’re supposed to do and do it well, how can anyone complain?
During the heyday of Getting Things Done productivity, I used an app called Nozbe for personal productivity. Perhaps less productivity as in a place to collect things and then generate lists which are the essence of tackling tasks. Over time I noticed that all the productivity apps generated to team collaboration for getting things done.
This new app seems to be a bit oversold (marketing fluff at the beginning) but it does fit a couple of trends of people working together and getting new employees up to speed quickly. Like many of the things I’ve written about for the past lot of years, I wish I could try it out to see how real it is. But the concept is solid.
BILT, the operational enablement tool, announced today a new feature tailored to professional technicians and tradespeople tasked with upskilling a new generation of workers. The latest app update introduces project sharing, a collaboration feature designed to enhance on-the-job enablement. Some educators expect trainees may be able to successfully install products in the field without ever having touched the equipment in the classroom if they have familiarized themselves with the 3D instructions.
“BILT is a game-changer in a training environment,” says Lab Instructor Christie Peterson of the San Francisco Joint Apprenticeship & Training Committee for Local 6. She says “BILT is absolutely the next step in the evolution of training and ideal for apprentices.”
With the new project sharing function, technicians and tradespeople can:
Streamline teamwork: Now, users can easily invite colleagues to work together on complex projects, ensuring tasks are completed with precision and speed.
Collaborate in real-time: Teams can synchronize efforts on the job, eliminating communication gaps to promote a smooth workflow.
Follow 3D interactive guidance: Images and animations on the 3D app can be manipulated to suit an individual user’s perspective to enable a comprehensive understanding of each task’s intricacy.
Contribute feedback: BILT garners ratings, reviews, and user feedback and provides managers with analytics and insights to identify pain points and potential delays.
“Project sharing fosters a dynamic, collaborative environment that boosts productivity,” says BILT Chairman & CEO Nate Henderson. He says the tool is uniquely attuned to helping professional technicians facilitate teamwork, reduce errors, and improve training.
Would you be comfortable wearing a headset that includes a sort-of goggles and speakers for periods of time? They would be a combination of virtual reality where you are immersed in a projected simulation and can be switched to augmented reality where you can see the physical area around you with an overlay of digital information.
The Apple Vision Pro unveiled at the June 2023 Worldwide Developer Conference (reviewed here) revealed Apple’s solutions to the many engineering and design challenges. Rampant speculation about using it and applications followed.
After listening to this conversation between Flexibits co-founder Michael Simmons and John Gruber of Daring Fireball and The Talk Show has broadened my mind. “Michael Simmons returns to the show to talk about his experience at Apple’s developer lab for Vision Pro, and his enthusiasm for the future of spatial computing.”
You need to listen to the conversation. But Simmons discusses his hands on time with the product in a developer lab and his current thinking about developing applications. I’ve now changed my mind about its applicability for general computing. It provides ability to see multiple screens while the user continues to use keyboard and mouse or whatever. He said he did not tire using the headset for an extended period. Nor did he suffer effects such as dizziness.
Certainly you can watch movies and sports and play games. Watch developer activity over the next four or five months. I would not be surprised to see an Emerson or Honeywell adaptation. Perhaps also Rockwell via PTC Vuforia team.
Let’s say you go to a nice restaurant. They show you to a table. You and your guest are seated. They hand you an elegantly printed menu. You look over all the options presented and choose. Perhaps you choose an appetizer to start dinner. Then you choose a salad, an entré, and a dessert. Perhaps a bottle of wine to complement the meal.
Now, let’s change the venue. You are at your desk. You need to decide what to do next. You look at your to do list. You know, that list that never stops growing thanks to email and Slack and other computerized incoming enemies.
Do you just take the top item? Do it? Check it off? Then look at the next thing?
Do you look at the list and panic at its size?
How about your email? You read about “inbox zero” but know that it is an unachievable vision of heaven.
Burkeman suggests looking at these things like a menu. Ah, I’m presented with a fine list of options. Which shall I work on now? I will select this one first as an appetizer. Later I’ll select the entré.
Thank you, Oliver. Somehow I feel a little better about the whole productivity thing.
Do digital tools have the effect of adding more things to our plate rather than helping us get things done? Gary looks at how software helped him get productive and then seemed to bog down and still accomplish a lot, but it seems slower over all. Even more, what is more important—getting more done or doing what is impactful?
