Machine vision solutions were not build for cloud-native automation

Il semble que tous les blogs et les courriels de ces jours-ci commencent par une déclaration sur le COVID-19 et la crise mondiale qui s'ensuit.

Tout le monde y pense et les conséquences sont terribles, quel que soit le point de vue. Ainsi, plutôt que de s'attarder sur la crise, Tulip concentre sa créativité collective sur les endroits où nous pouvons peut-être aider.

Étant donné que Tulip est une plateforme d'applications de fabrication qui favorise la productivité et que la plupart des opérations de fabrication dans le monde sont à l'arrêt, on pourrait penser que nous n'avons pas grand-chose à faire.

Ce n'est pas vrai quand on regarde les entreprises qui fabriquent des fournitures essentielles pour les soins de santé, des kits de tests viraux, des équipements médicaux et, bien sûr, des thérapies COVID-19. Il s'agit de secteurs réglementés où le délai de mise sur le marché a toujours été un élément essentiel de l'activité.

La plateforme Tulip est axée sur la rapidité, et nous pensons que c'est là que nous pouvons aider.

Trouver la capacité cachée

Pour les fabricants de dispositifs médicaux, y compris les kits de tests viraux et les équipements médicaux tels que les ventilateurs, il s'agit de volumes de production. Les chaînes d'approvisionnement des fabricants sont tendues à l'extrême et ils doivent augmenter les volumes de production de 2 à 3 fois.

Cela met l'accent sur l'OEE, un domaine dans lequel la solution de surveillance des machines de Tulippeut être d'une importance capitale. L'OEE n'est pas un concept nouveau. Les solutions de surveillance de l'OEE ne le sont pas non plus. Ce que la solution Tulip peut apporter, c'est la rapidité de mise en œuvre et, plus important encore, une vision centrée sur l'homme pour comprendre l'impact de l'activité humaine et des opérations sur l'OEE. Nous appelons cela l'efficacité globale du processus, ou OPE.

Augmenter la productivité dans les environnements GMP

Lorsqu'il s'agit de thérapies pour le COVID-19, le principal défi en matière de délai de mise sur le marché est lié au long processus d'approbation réglementaire, puis au transfert de technologie et à la mise à l'échelle de la fabrication.

Ces processus sont lents et impliquent beaucoup d'activité humaine. La productivité peut être augmentée en numérisant la documentation et en facilitant l'activité humaine avec des applicationsfaciles à utiliser. Il s'agit notamment d'instructions de travail et de procédures opérationnelles normalisées (SOP) numériques, de journaux de bord numériques, d'autorisations et de réglages de lignes numériques, et même d'historiques numériques. La plateforme Tulip permet de numériser vos processus papier en quelques heures.

Oui, nous savons qu'il s'agit d'un changement de paradigme. Mais c'est en temps de crise que le changement est le plus facile - nous ne pouvons pas nous permettre d'attendre.

La question est donc de savoir comment Tulip peut faire quelque chose pour avoir un impact significatif sur cette crise ?

Eh bien, pour faire simple, nous aimerions offrir gratuitement nos services et nos logiciels à ces entreprises manufacturières. Nous leur fournirons gratuitement l'accès et l'utilisation de la plateforme Tulip afin de les aider à augmenter les volumes de production et à commercialiser plus rapidement les thérapies. La plateforme Tulip est prête pour les BPF et est validée pour une utilisation dans des environnements réglementaires.

Nous sommes prêts à vous aider à aider le monde avec la pandémie de COVID-19. Le service de fabrication de Tulip, qui possède une expertise unique en matière de fabrication réglementée, soutiendra personnellement toute initiative de ce type.

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A variety of advanced vision solutions are emerging today, many of which employ cloud and machine learning technology. The startups exploring this space are often spun off of research projects or else have roots in academia. Manufacturers, however, rarely have their needs met when the solution focuses on the new technologies and neglects all the other aspects of a real automation solution.

Utilizing everything cloud computing has to offer, a modern machine vision system, such as Elementary, stores all images remotely, enables remote access and configuration, provides event monitoring and alerts, and more. The key to Elementary’s success is that they provide the full stack solution — this means high-resolution cameras, lights, local compute devices, and the cloud architecture that enables the AI workflow. Deployment and onboarding of a full stack system is further simplified with Elementary’s Quality as a Service model, which augments their easy-to-use interface with a team of machine learning applications engineers tasked with supporting their customers.

Scaling AI for Manufacturing

To be robust against environmental and product variations, a traditional machine learning model requires a large number of labeled data. Examples of all variations of “good” products and “bad” products, combined with the variations in lighting and product positioning in the cameras’ field of view must be included and properly labeled. This can easily become cumbersome at best and impossible in many cases when these images must be stored, rapidly accessed, and carefully labeled, before being used to train a model. Further, the labeling and training process must be iterated with new images to maximize the accuracy of the model, making it a daunting task.

While possible, an edge-only system would likely require an engineer to sit in front of the vision system on the factory floor to label images and train the model, or else manually download the dataset, process and label the images offline, and then upload the model to the machine vision system. While manageable as a single project or proof of concept, this workflow quickly becomes unmanageable when a manufacturer needs an AI vision solution for multiple products or lines. Edge-only AI vision solutions need to be underpowered by design, or rather not suitable for real applications, or else the training workflow quickly becomes unscalable.

By utilizing cloud technologies in the right way, ML-based vision solutions become scalable from both a hardware and operational perspective. Elementary utilizes cloud computing to provide a scalable machine learning-based vision solution.

Elementary has integrated its next-generation AI-driven vision solution into Tulip to provide operators with an inspection solution in their existing Tulip workflows. This allows operators to easily perform advanced vision inspections through a single pane of glass, while still getting the benefits of Elementary’s cloud analytics and scalable management.

Tulip Elementary Integration

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Elementary has integrated its next-generation AI-driven vision solution into Tulip to provide operators with an inspection solution in their existing Tulip workflows. This allows operators to easily perform advanced vision inspections through a single pane of glass, while still getting the benefits of Elementary’s cloud analytics and scalable management.

Elementary is a full stack solution provider, which means Elementary provides not only the cloud software to drive the AI, but also all of the hardware required on the factory floor to perform the inspection — including lights, cameras, edge compute, mounting hardware, and even installation.

This makes adding new inspection systems easy since customers don’t need to cobble together parts or suppliers to achieve their ultimate goal of adding quality inspections to their lines. Additionally, the ability of Elementary to natively integrate with devices on the factory floor allows customers to adjust the behaviors of other systems on the factory floor — preventing further defects based on the inspection results. Elementary calls this closed-loop quality.

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Elementary is a full stack solution provider, which means Elementary provides not only the cloud software to drive the AI, but also all of the hardware required on the factory floor to perform the inspection including lights, cameras, edge compute, mounting hardware, and even installation. This makes adding new inspection systems easy since customers don’t need to cobble together parts or suppliers to achieve their ultimate goal of adding quality inspections to their lines. Additionally, the ability of Elementary to natively integrate with devices on the factory floor allows customers to adjust the behaviors of other systems on the factory floor to prevent further defects based on the inspection results. Elementary calls this closed-loop quality.

As shown in the high-level architecture diagram above, Elementary takes advantage of the full stack nature of both Elementary and Tulip to operationalize visual inspections as part of the manufacturing process. On the factory floor, Elementary uses the Tulip connector to connect directly over EthernetIP. This connection drives the inspection process and allows the operator to trigger the inspection through Tulip and receive information about the inspection results. Image data is retrieved from Elementary’s cloud API to be presented to the user, as well as stored in Elementary’s cloud for analysis by quality managers.

The resulting workflow to the operator looks like this:

  1. The operator follows the assembly instructions in the Tulip application as they would with any assembly.

  2. Once they get to a step that requires a visual inspection, they are prompted with an “Inspect” in the Tulip app. Clicking this button triggers the inspection system to perform the inspection required at this step.

  3. The results from the inspection are presented to the operator as a pass or failure if a defect is detected.

  4. If a defect is detected the operator is presented with an image taken by Elementary that highlights the areas that require rework (as shown in the image above)

  5. Once the required rework is done the inspection can be triggered again through the Tulip app until it successfully passes and the operator can move to the next step.

Combining Tulip with Elementary provides a complete solution for manufacturers looking for a robust manufacturing process that includes quality inspections without burdening the operators with additional training or time required to pivot between systems. Also, the full stack nature of both Elementary and Tulip means that everything is provided, from software to hardware, easing the implementation burden on your factory teams. Integrating machine vision into your inspection processes is a must as you try to scale to maintain quality and increase throughout. Tulip and Elementary work together to provide a trusted solution for quality inspection that empowers your operators.

This blog was created in collaboration with Tulip's technology partner, Elementary. For more information about using Elementary with Tulip to support your inspection applications, please visit https://tulip.co/partners/elementary

Conclusion

Combining Tulip with Elementary provides a complete solution for manufacturers looking for a robust manufacturing process that includes quality inspections without burdening the operators with additional training or time required to pivot between systems. Also, the full stack nature of both Elementary and Tulip means that everything is provided, from software to hardware, easing the implementation burden on your factory teams. Integrating machine vision into your inspection processes is a must as you try to scale to maintain quality and increase throughout. Tulip and Elementary work together to provide a trusted solution for quality inspection that empowers your operators.

This blog was created in collaboration with Tulip's technology partner, Elementary. For more information about using Elementary with Tulip to support your inspection applications, please visit https://tulip.co/partners/elementary

Our Partnership with Elementary

Elementary is one of our Technology Partners. For more information about using Elementary with Tulip to support your vision applications, check out our partner page.

Day in the Life Illustration