Defect Detection Product Manufacturing Support
Highlights
Our client, a recently founded company, is working to establish itself as a top developer of machine vision products for production quality control. Enlisting the assistance of PSA, the company has developed a cutting-edge defect detection system leveraging neural networks for use in printing houses. Suffering a lack of relevant expertise, they asked PSA for additional support through the product manufacturing phase.
Challenge
Client Challenge
Finalize product prototype to prepare it for certification and further mass production.
Project Objective
Establish the end-to-end manufacturing process for 10 samples of the defect detection device to be used for trial operation.
Solution
Having moved past the development stage of the Defect Detection Product, PSA prepared the foundational framework for all samples to be seamlessly manufactured. Our technical & management support included the following activities:
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Components procurement based on the initial BOM, including processor modules and long lead components
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Logistics management. Transferring the components to the manufacturing site
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Documentation updates for production, defining errors and missing components
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PCB assembly support, providing components’ replacement when missing
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Final samples bring-up. Addition and adjustment of the light sources for the client’s needs
As an output, our client received 10 prototypes of the defect detection device to be used within the machine vision system at printing facilities. It allowed the client to launch their trial operation to maximize product potential, identify flaws, and create a strategy for further development
Development Included
- Components Selection & Procurement
- Documentation Updates
- Assembly Support
- Improvements implementation
Results
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Production and delivery of prototypes
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Final BOM validated
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Time and money saved on updates
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Commencement of trial operation
Technology Breakdown
- 5 Software Engineers
- 16 months
Further Cooperation
Alongside our client, PSA is continuing work on further product development, evaluating the neural network's performance deployed in the device itself.