Ciena Corporation

Niakam Kazemi

Andrei Csipkes

Muhammad Raza

A manufacturing quality information database structure is useful for tracking quality information relating to a manufacturing process. Accurate tracking of symptoms, defects, and actions (repairs) is achieved through data associations between symptom data entities, defect data entities, and action data entities. Further associations between symptom and symptom category data entities; defect and defect category data entities; and action and action category data entities may be used to increase the data tracking capabilities of the database. Moreover, manufacturing processes and process steps may be tracked by process and process step data entities that may also be associated with the symptom, defect and action data entities. Still further, a variety of different modules and module types may be tracked by including an item data entity that identifies each module.

Defect management database for managing manufacturing quality information

A defect management system and method includes a centralized database operatively connected to operator, troubleshooter, reworker and inspector workstations via a network. A defect information management application program is installed on the workstations and generates graphical user interfaces that permits the operator, troubleshooter, reworker, and inspectors to log and coordinate defect information. Modules being manufactured may exhibit symptoms of a defect. The symptom and symptom category are logged into the database by the operator. A troubleshooter reviews the logged symptom information to aid in the diagnosis and entry of defect category and defect information. The symptom and defect information are associated with various processes and process steps to accurately track defect module information. A reworker reviews the logged symptom and defect information to determine appropriate repairs. Repair action categories and repair actions are then logged by the reworker. An inspector reviews the logged symptom, defect and repair action information to provide feedback on whether the repair was successful.

Defect management system and method

A method of improving the quality of manufactured modules includes logging manufacturing information to a database and utilizing a knowledge base to determine defects of a manufactured module. A quality ticket is issued for defective modules that is used to log and store defect symptom information in the database. Defects may be determined based on the quality ticket and by utilizing the knowledge base. Repair suggestions may be made and logged to the quality ticket based on the defect determination. Repairs are performed and repair actions logged to the quality ticket. Tests are then performed on the repaired modules. Based on the test results, the knowledge base is updated. In other words, the knowledge base learns over time as more modules, symptoms, defects and actions are tracked. The knowledge base aids during troubleshooting by providing a list of repair actions and frequency of such repair actions that successfully repaired the defect identified in the quality ticket. Alternatively, the knowledge base may provide a list of defects and defect frequency for the symptom identified in the quality ticket. Using these techniques, the quality of a manufactured item may be improved.

Method of improving quality of manufactured modules

A system and method analyze raw data derived from a manufacturing control facility, the manufacturing control facility for manufacturing at least one device by execution of a sequence of assembly operations. A preprocessor is used to receive the raw data from the manufacturing control facility and to configure the raw data into a predetermined database format. The raw data after being configured by the preprocessor is stored into a database. A server transmits queries and results between the database and at least one user terminal. The results transmitted by the server are displayed on at least one graphical user interface at the user terminal, the results being indicative of at least one performance parameter of the assembly operations.

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Dayton, MD, United States of America

Niakam Kazemi