The 20/20 on Machine Vision
We look at machine vision: what it is, how it functions in the future-facing industrial environment, and whether it’s right for your business.
Find out how automation can reduce your scrap rate, and raise your profit margin and company profile, by fine-tuning your efficiency and quality control.
In the first two articles in our series about organizational readiness, we looked at the roadmap to AI maturity, and saw how smart, data-driven automation can yield insights that deliver continuous improvements to productivity. We now conclude this series by looking at two vital and closely related factors in realizing your operation’s potential: efficiency and quality control.
From volatile global supply chains, labor shortages, and soaring energy costs to the implications of climate change, there are rising pressures on businesses to make continuous improvements or they will lose out to the competition. On top of that, there is a growing need for regulatory compliance within many industries. In some sectors, it’s essential for error margins to be minimized—there are no second chances for less-than-top quality.
This points to two independent yet connected goals: operational efficiency and customer satisfaction. You want to improve your financial bottom line by reducing your overheads and wastage, while customers are also rating you on quality and, increasingly, on the sustainability of your operation (touching on wastage again, and energy use) and your commitment to the circular economy (including product provenance and traceability). Efficiency and quality control are partners in tightening up your processes and promoting your company’s profile.
Retaining your competitive edge and boosting productivity need not mean scaling up massively. Measurable gains can be made by implementing smart manufacturing.
Efficiency is about using less in terms of inputs, wasting less through the process, and retaining high-quality outcomes. It is about putting ten units through your operation and getting at least nine, rather than just seven, to market. The crux is finding out what makes that two-unit difference in your scrap rate—and data is the key.
By shifting over to smart manufacturing, you are setting up a digital platform to capture and analyze data from all aspects of your operation, enabling efficiencies across the board. For instance, sensors in your cooling/heating/air filtration systems could alert you to a clogged filter or duct, or a faulty extraction unit, which could be causing the system to run inefficiently (and thus adding energy costs). Or it may be a machine vision system that detects a tool that is trending out of specification, alerting your maintenance team to step in.
Taking it further, by creating a digital twin (a.k.a. digital shadow) of your physical processes, you can monitor operations in real time. You can model ways to optimize processes; for example, reordering a manufacturing sequence to capitalize on periods of lower-cost electricity or cooler ambient temperatures, or by reconfiguring the storage of materials to align with ideal logistical flows.
Quality control (QC) is often one of the last elements of an operation to be brought into the smart factory. Many companies still rely on staff performing manual checks on product samples; this is usually cumbersome and can raise the error margin through incorrect checking or faulty recording of data.
Automation offers multiple ways to boost your QC performance, such as:
Vehicle maker BMW has been known to comment that in quality control, 99% isn’t enough—after all, even with this pass rate, there would still be around 40 problematic parts on a factory-new motorbike. The company uses a high degree of AI throughout its European and U.S. manufacturing plants—from self-learning machine vision to the laser codes engraved into each body blank (ensuring every part can be followed through the build process), and to the sensors on every welding tip that regularly measure friction levels and so predict the need for scheduled maintenance work.
You do not need to implement a full, lights-out future factory to see the benefit of automated quality control. The well-known “80/20 law” states that around 80% of impact stems from 20% of the faults; that’s a good place to start.
We can work with you to map out your best route to greater efficiency and higher quality. By collecting machine data, we can begin by fine-tuning your overall equipment efficiency. Being able to baseline your environment and identify any existing big gaps is a giant first step.
Speak with one of our consultants to find out how your business can benefit from smart manufacturing no matter where you’re at in your AI journey. Contact Facteon via our contact page.