Smart Quality Inspection
| dc.contributor.author | Omar Dere | |
| dc.date.accessioned | 2023-05-16T10:12:38Z | |
| dc.date.available | 2023-05-16T10:12:38Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | Defect detection was executed manually by human inspectors, naturally prone to fatigue, inattentiveness and biases. Later, manual inspection was augmented by rule-based machine vision technologies. Over the past decade defect detection has become increasingly technology-driven, building on advancements in artificial intelligence and image processing and big data. The use of smart cameras and related image processing-enabled systems is already helping manufacturers deliver high quality inspection in shorter cycles, reducing latency and costs, and setting new standards that are far beyond the capabilities of even the most experienced human inspectors. In this project we design and implement software for process management on a production line to improve quality of the production process and detection if an error occurs. The software includes Customer page and Admin page, On the customer page, we market the products, allow the customer to purchase them, and display general information about the product line to the customer, in the admin page we divide it to three roles: Manager, Head and Employee each of them has specific powers to management production line and dealing with image processing. Because this out of our scope we be working with students from industrial engineering department. Our project is built with ReactJS library for web that based on JavaScript programming language and Flutter for mobile that’s based on Dart language. Furthermore, it includes application programming interface (API) made with Java spring boot to support the main application features and manage the database. It uses 2 types of databases, a SQL database (PostgreSQL) is used for storing the main data of the application while real-time features like the chat messages is implemented using firebase messaging service. | |
| dc.identifier.uri | https://hdl.handle.net/20.500.11888/18253 | |
| dc.supervisor | Dr.Anas Toma | |
| dc.title | Smart Quality Inspection |
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