FEATURE Machine Vision
AI and MV for improved quality T
he pairing of Artifi cial Intelligence (AI) with Machine Vision (MV) is providing manufacturers with a new
approach for maintaining quality in high- volume manufacturing environments. The arrival of competent and cost-eff ective AI has enabled the possibility for a camera feed to be reviewed in real time, and have faulty widgets identifi ed and tagged either physically or virtually. Potentially, it has become possible to inspect every part coming off the line – something that was neither economic nor practical with human operators. This solution is particularly valuable in the manufacture of automotive components, which are complex, price- sensitive, high-volume and frequently safety critical.
Mission critical
In this context, the announcement by Bosch VHIT (Vacuum & Oil Pump Products Italy – a manufacturing subsidiary of Bosch) of a partnership with mission-critical edge specialists Lynx Software Technologies to test a new proof of concept camera-based quality program for use with real-time decision making in industrial settings is extremely interesting. The move is part of Bosch VHIT’s digital transformation of its processes and product development.
“Partnerships such as this one with
Lynx are critical to shaping our future and continuing on our path of innovation to best serve our customers,” said Corrado La Forgia, Managing Director, Bosch VHIT. Pavan Singh, Vice President, Product Management, Lynx Software Technologies added: “Many manufacturers, including Bosch Italia, are exploring better ways to proactively and continually improve quality. Our experience has indicated there are some false positives, but this is much better than failing parts making their way to end customers. As the algorithms improve, the incidence level of those occurrences will reduce. The combination of AI and MV is signifi cantly more eff ective than batch testing, which is used to manually and retrospectively trace faults back to the manufacturing environment and workers, to understand root causes and make changes to processes.” The program captures data from
30 September 2021 | Automation
cameras on manufacturing plant fl oors and logistics warehouses, and harnesses machine learning algorithms to identify quality issues and feed information into the MES system, in order to generate an optimal decision in real time. When securely connected to the cloud, the system benefi ts from continued access to advanced artifi cial intelligence algorithms and data analytics packages. By partnering with Lynx, Bosch VHIT is able to close the digital feedback loop that is reliant on capturing quality images and analysing the data to provide a safe real-time action. The LYNX MOSA.ic for Industrial product enables the program to run multiple functions on a single SoC without compromising performance, security and safety.
“As we continue advancing cutting- edge technology applications for factory automation, we are excited to partner with Lynx to accelerate a new, secure IIoT- based quality system for the market,” said Riccardo Sesini, Digital Transformation Manager, Bosch VHIT. “In increasingly- connected manufacturing environments, manufacturers require safe, versatile and resource-conserving solutions. Lynx has a long history of robust, safety-critical, high- availability systems and was the obvious choice to help us realise this latest program in a safe and scaleable way.”
Quality systems
For new manufacturing quality systems, Lynx’s framework is focused on ensuring security and mitigating any period of equipment downtime that could impact business output. It provided the software platform that can run the inference engine and control functionality on the same platform, ensuring that these applications
are appropriately isolated, and allocated the right hardware permissions (and nothing more) to perform their tasks. A camera might highlight an issue, then a soft PLC can connect to the line and make appropriate process improvements. This infrastructure is “mission-critical edge”. Since these systems are critical to the manufacturing process, they need to be protected against hacking and the malfunction of another program running on the same hardware is critical. LYNX MOSA.ic for Industrial consolidates mixed criticality workloads running on the same multicore processor – the resources and performance provided by the hardware platform, and the capability of the software components. At the same time, the framework completely isolates critical applications from non-critical workloads, to provide high levels of immunity to the former from cyber attacks. Additionally, this greatly reduces the architectural complexity, cost and number of points of failure – a critical factor in ensuring business resiliency.
“Bosch VHIT’s goal to accelerate the
realisation of connectivity solutions for a smarter industrial future aligns with our eff orts in the space,” said Singh. “Providing robust edge solutions for the connected camera-based quality system will enable real-time responses to be delivered to events while ensuring critical applications run reliably and safely alongside other functions operating on the server/gateway hardware.”
CONTACT:
Bosch VHIT
www.bosch.com Lynx Software Technologies
www.lynx.com
automationmagazine.co.uk
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