Defence manufacturing follows a near-zero tolerance for quality failure, however, AI applications in manufacturing quality continue to be heavily researched in the context of civilians. This literature review attempts to summarize 58 articles under four themes – intelligent quality inspection and predictive quality management, smart factories, manufacturing reliability and resilience, and human-AI collaboration along with associated security and implementation issues – in order to understand how smart manufacturing driven by AI can contribute towards quality improvement in the context of defence manufacturing. Through a thematic synthesis based on PRISMA guidelines, it has been found that although inspection, predictive maintenance and cyber-physical systems in factories have reached technological maturity in the civilian domain, the same has not been verified in the classified environment of defence manufacturing, especially in the Indian scenario of defence indigenization. Six research gaps are presented and a future research agenda is proposed, besides presenting an integrative conceptual framework which associates the four enablers in a defence manufacturing-specific context with quality improvement in defence manufacturing.
Download
Download XML