“How do we know how well the AI model performs and how many mistakes it makes?” is a question we often hear from manufacturers interested in our AI-based solution for manufacturing applications such as quality control and predictive maintenance. Model performance is a justified concern, artificial intelligence is still a young discipline and people need […]
Confusion Matrix: Addressing Confusion About AI’s Performance Read More »
A while ago we wrote a blog about how classic AI e.g. machine Learning (ML) is ready for prime time on the shopfloor while generative AI will need a little while longer to be mature enough to be deployed in manufacturing itself. However, if you work in and with AI everyday, there is no way
Generative AI Helps Promote Classic AI Read More »
We live in the age of big data. Whether it is social media platforms, retail and e-commerce, telecommunications, healthcare or manufacturing an estimated 2.5 exabytes – or 2.5 quintillion bytes – of data is generated each and every day. The ability to crunch and make sense of these data was long the limiting factor. However,
How AI is disrupting our industry and what can we do about it? – this was the question Authority Magazin asked AI professionals and of course we were only too happy to talk about the changes, challenges and opportunities we see for AI in manufacturing. The article is in form of an interview and you
Interview – How AI Is Disrupting Our Industry? Read More »
Our analytics show that “mature AI” is an important keyword that brings people to our webpage. Let’s ignore the possibility that the intent behind the search term “mature AI” can be described as “show me AI-generated pictures of mature women” (although Google does not rule that interpretation out) and focus on what we believe the
Mature AI – Ready for Prime Time on the Shopfloor Read More »
In our short series of challenges facing the forward-looking manufacturing professional ready to adopt AI, we have so far talked about data and change management challenges. Now it’s time to talk about technology challenges our customers have encountered and how to address them. Here are the four most relevant ones: Technology Challenge 1: Integration with
4 Technology Challenges You Need to Address when Implementing AI in Manufacturing Read More »
When we started our first AI project with a large consumer goods manufacturer the welcome on the shopfloor wasn’t exactly warm. The staff feared that within a few weeks or months, a lot of them would lose their job. We realized quickly that the algorithms or data wouldn’t be the main challenge, AI change management
4 AI Change Management Challenges to Be Aware of Read More »
Artificial intelligence (AI) is the future of manufacturing. Many of the issues that continue to plague the industry – too expensive, too much scrap, unplanned downtimes, lack of personnel for both specialized and routine tasks – can be addressed with this new powerful technology. AI has come a long way over the last few years
AI Implementation: Don’t Let These 4 Data Challenges Slow You Down Read More »
We recently gave a presentation about AI in Manufacturing to an audience at Cyberlago, a German organization in the Lake Constance region that promotes digitization, digital transformation, and IT. Here is the link to our presentation titled KI in der Fertigung (in German) and an annotated pdf version. KI in der Fertigung CyberLago final annotated
Video: KI in der Fertigung (AI in Manufacturing) Read More »
If you are looking for a perfect application to start deploying AI in manufacturing, look no further than visual inspection. AI significantly outperforms conventional methods by bringing automation, speed and accuracy to visual inspection processes. In this blog, we’ll talk about why AI is superior to both manual and machine vision-based quality inspection and then
The Role of AI Models in Visual Inspection Read More »
Admittedly, we stole that headline (hence the quotation marks), or rather borrowed it, from a recent article published on the MIT Sloan website. It was done in the spirit of imitation being the sincerest form of flattery. The original article introduces a framework to help readers decide when to swap out human labor in favor
4 Questions to Ask Before Swapping out Human Labor For AI Read More »
One of the main problems we encounter when speaking with manufacturers about the use of AI in manufacturing for quality control, predictive maintenance, predictive analytics or human-machine interface simplification is not a technical one: it’s trust. “How do we know that the algorithms give us the correct answer?” “Doesn’t the model just tell you what
Accella AI develops tools that enable the rapid implementation and easy management of artificial intelligence models for manufacturing applications. Our mission is to make AI-empowered solutions in quality control and predictive maintenance economical for manufacturers.