A Decision-Support Model for Prioritizing Factory Equipment Sensorization Under the CUATRO Program

Abstract

Factory equipment sensorization is a practical entry point for smart manufacturing because it can convert existing machines into measurable assets without requiring immediate machine replacement. However, not all firms, facilities, or equipment types should be sensorized at the same time. For small and medium enterprises (SMEs), DOST regional offices, shared service facilities, laboratories, and demonstration sites, sensorization should be applied selectively where machine use, downtime, energy consumption, equipment criticality, and site readiness justify the intervention. This paper proposes an Equipment Sensorization Priority Index (ESPI) for the Connected and Unified Autonomous Technologies with Automation and Robotics (CUATRO) program of the Department of Science and Technology-Metals Industry Research and Development Center. The model synthesizes recent literature on digital retrofitting, predictive maintenance, SME Industry 4.0 adoption, and decision support to define seven prioritization criteria: production criticality, downtime concern, energy and resource impact, data visibility gap, technical sensing feasibility, site readiness, and policy demonstration value. A weighted scoring procedure and decision rules are presented to classify equipment into highpriority, conditional, low-priority, or non-applicable sensorization cases. The proposed model supports CUATRO by helping implementation teams select where sensorization can generate meaningful operational insight and policy evidence.