SME Production Resilience: A Four-Layer AI Use Case Selection Approach

Small and medium sized manufacturers (SME) face recurring disruptions which can be addressed by an increase of resilience. Current solutions based on Artificial Intelligence (AI) offer a possibility to meet requirements in terms of resilience while offering high business efficiency. However, the identification of suitable use cases shows a high complexity due to its innovative character and multiple solutions being introduced in a short time. This paper proposes an approach for early-stage use case identification that combines corporate domains to frame the application context, resilience dimensions to specify the intended effect, and a compact self-assessment of technical and organizational prerequisites. The approach derived to identify use cases is implemented in a web-based IT-demonstrator that guides users through four decision layers and delivers an individualized selection of AI use cases aligned with the SME context and resilience objective. To test comprehensibility, practical plausibility, and usefulness across heterogeneous SME conditions the demonstrator and selection logic were refined and validated with industry experts.