A Technical Training and Data Collection Program for Structural Welders and Fitters
Project Participants: Northrop Grumman Shipbuilding
Project Start: November 2004
With an aging work force and the perception that manufacturing jobs are less desirable, highly skilled structural welders become more difficult to find and retain. This causes the information associated with quality standards and dimensional tolerances to pass to craft management and internal inspection agencies. The result is an over-reliance on inspection to insure proper quality, often at the cost of multiple repair cycles.
A second issue relating to productivity involves daily planning accomplished by frontline supervision. Experienced foremen do a reasonable job of juggling the many variables involved in this planning process. However, the work sequence and job assignments are often sub-optimum due to the complexity of the task and the pressures of time. In addition, few information aids are available to assist in detailed daily tasking. This task then becomes highly subjective. Pilot studies suggest that as much as a third of productivity is lost due to these two concurrent issues.
This project will develop a comprehensive system that will allow quality performance training, quality performance tracking, daily tasking and daily status assessing for individual welders.
In addition, detailed design data will be made available to production management in a paperless environment, which will facilitate quantitative incremental tasking for production personnel. Ultimately the system will provide quality and performance metrics that may then be managed by supervisors using wireless technology.
This will be achieved by implementing an effective system that is proven through pilot testing. The goal of this project is to provide a modern business and technical system that gives the worker a clear understanding of his task and enables him to assess the quality of his work daily at his work site. The system also provides a data collection function via handheld devices; the resulting information will guide structural improvements in training, qualifications and job classifications.