STATISTICAL QUALITY-CONTROL AND NAVY SHIP REPAIR

Since the end of the Cold War, there have been demands in the United States to step down defense costs. One effect of these demands is a shift in accent within the U.S. Navy from acquisition to maintenance in order to make ships and ship systems last longer. Inevitably, this will mean more work for the ship repair industry, public and private. At the same time, the Navy is concerned about quality improvement in its industrial base and is encouraging the use of strategies generally known as Total Quality Management. However, the characteristics of Navy ship repair challenge many of the TQM methods that work so well in manufacturing. Government contracts restrict such quality strategies as single sourcing and just-in-time inventory. Government quality assurance requirements rely heavily upon final inspection. Navy business methods such as fragmentation of the work package among independent performers and constant and universal interface between customer and performer impede cohesive control. Finally, Navy ship repair, unlike the automaton factory, requires labor intensive, high skill, non-rote craftsmanship across many thousands of low volume activities. The quality objective is this: to measure, control, and improve the processes of ship repair in order to reduce variation from target values and to provide customer satisfaction. This can be done through statistical process control adapted to job shop operation. This paper describes how SQC methods can be applied to production, logistics, quality control, and test programs in order to control the critical path and quantify the quality character of the shipyard. Control is maintained through a closed loop management model which uses key state variables for process measurement. Quality is determined by characteristic curves and quantified by process control limits.