Scale-able AI and Machine Vision Technology to Improve Manual Manufacturing Steps

We sat down with Ed Goffin, Senior Manager of Marketing Pleora Technologies to discuss their support and involvement with SmartMTX. Pleora is a Bronze level sponsor for the SmartMTX. We needed to know more about his Tech Talk titled: Vodka, Electronics, and Toilet Repair – Make Human Decisions Consistent with AI! Ed’s tech talk session will focus on how AI and machine vision technology can be used to improve manual manufacturing steps. The presentation will specifically focus on how a distillery and electronics manufacturer are deploying new technologies to reduce errors, waste, and costs.  

Q: What’s your main reason for exhibiting at SmartMTX?

A:  We have new solutions that help automate and digitize manufacturing processes and are looking for companies willing to partner with us as we continue to develop these technologies. As a Canadian headquartered company, ideally, we would like to work with other companies based in Canada so we can help develop a competitive manufacturing advantage for our partners.

Q: Who do you want to connect with at the show and why? 

A: Primarily, we are looking to partner with manufacturers, automation solution providers, and system integrators who are seeking easier-to-use machine vision and AI solutions to automate and digitize processes. We have deployed these solutions with several manufacturing partners but would like to get the technologies onto the factory floors of a wider range of industries so we can gather feedback and recommendations. 

Q: What solution(s) are you exhibiting and who are they designed for?

A: We will be exhibiting an app-based solution that uses machine vision and AI expertise to automate and digitize manufacturing processes. The suite of apps help spot, identify and track product errors during manual inspection and assembly processes to make human decisions consistent, subjective, and traceable. This includes apps that bring AI insight into visual inspection tasks and digitize error-prone paper-based processes. For example, the Visual Inspection apps uses machine vision to identify and highlight possible differences on product, with AI insight that provides decision-support for an operator. These apps are best suited for manufacturers who rely on manual inspection and assembly throughout incoming, in process, and outgoing processes. The apps then provide data back to a manufacturer’s resource planning system, so they gain better insight into manual steps for continuous improvement and issue tracking.    

Q: Do you offer any special training for your solutions? 

A: Yes, we have an applications engineering team that provides direct onboarding, training, and customization support. Our overall intent is to provide a technology solution that is easy for a manufacturer or integrator to train and customize on their own, but we are always ready to help our partners.

Q: What customer pain points are you solving and why?

AThe suite of apps bring decision-support and traceability to manual manufacturing processes. Roughly 70 percent of manufacturing steps rely on human decisions or intervention. Most manual inspection steps exhibit errors rates of 20-30 percent, and when humans follow manual assembly instructions error rates can hit as high as 60 percent. Our solution does not intend to replace the human. For many of our manufacturing partners, there is a good reason why they want to keep the human in the decision loop. But our suite of apps do provide technologies to help ensure their decisions are consistent, reliable, and traceable.

By reducing human error, using visual tools to train new employees, and digitizing paper-based steps to streamline processes; we can help manufacturers reduce waste and downtime, increase profits, and ensure consistent product quality. For example, we are working with a distillery to help add operator decision-support during manual labeling processes. Fully automating this process provided to be too expensive for the manufacturer. However, human errors in the processes resulted in brand concerns and costs due to waste and downtime. Often an employee suspected there was an error, production would halt as employees started looking at products to ensure they were correct. With the visual inspection app, they can more easily train new and seasonal employees on brand appearance requirements and quickly check for errors. 

Q: What is the advantage of your solution over the competition?

A: Our suite of apps can be used across incoming, in process, and outgoing manufacturing steps to reduce the number of tools and vendors. Unlike many approaches, our flexible suite of apps let a manufacturer start using technology to solve one process problem, and then they can scale the solution across other steps as they gain comfort in the tools. As an example, we work with an electronics manufacturer who first used our system to aid operator decisions during visual inspection. As they gained comfort in the tool, as well as data insight, they added product tracker capabilities to begin capturing and storing images and operator notes from visual inspection steps for RMA steps and continuous improvement.   

For visual inspection, our solution adds AI-based decision-support to a manual decision. Typically designing and training an AI application requires extensive and often costly development expertise and numerous good and bad images to produce an AI model. Our system uses initial operator decisions for continuous transparent model training. As an inspector accepts or rejects initial product differences, behind-the-scenes they are training an AI model. Within a few inspections, the AI will begin suggesting decisions to an operator. In some applications, and manufacturer can train the model and then redeploy it across multiple inspection stations to ensure operators are all making the same consistent decision.  

Q: Can existing systems integrate with your solution? 

A: Yes the system has a two-way integration between manufacturing and resource planning software tools. It integrates with PLCs for triggered automated steps in the process. The system ships with a camera and edge processing but can work with cameras from most vendors. For example, the solution is in use with one manufacturing partner who uses microscopes in their visual inspection steps.

For more information about how Pleora Technologies is simplifying saleable AI and Machine Vision Technology; visit, follow them on LinkedIn, or contact them directly at info(at)  

Posted: February 8, 2023

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