Eliminating Quality Escapes for Zero-Defect Manufacturing: A Digital Approach

Manufacturing quality escapes have continued to affect aerospace and defense (A&D) programs throughout 2024, leaving open the question of how OEMs and MROs can best ensure the quality and safety of A&D fleets. Aircraft incidents in the commercial sector include the Boeing 737-MAX 9 Alaska Airlines incident in January and the Gulfstream G500 and G600 action by the Federal Aviation Administration (FAA) in June – both caused by missing or incorrectly installed bolts and fasteners. The Boeing incident led to quality concerns regarding subcontractor Spirit Aerosystems’ work on the B-21 bomber and the KC-46 tanker.

To improve manufacturing and aftermarket execution, Gulfstream is revising engine removal and installation procedures, and Boeing is expanding workforce training and proficiency. However, attempting to change human behavior has an inherently limited impact on safety and quality outcomes. Operators become fatigued or distracted. They are also prone to expectation bias, which causes them to assume and not verify that they have the correct fastener assembly, for example. The worsening shortage of skilled workers among A&D contractors further erodes the effectiveness of these procedural and training updates.

If quality escapes are to be eliminated, a new approach is needed. This presentation proposes a two-pronged systems approach to zero-defect manufacturing. First, digital process control is implemented to guide operators to perform the right task at the right time with the right parts and equipment. Digital process control includes electronic work instructions and buyoffs as well as mobile tablets and smartphone-size devices. Second, AI-enabled automatic inspection is applied to very large components and assemblies, achieving six sigma inspection reliability on parts as small as a cotter pin. The presentation will describe this approach, the supporting technology, and a use case in which a major A&D manufacturer transitioned from traditional manual quality control to the proposed digital quality control.