Automotive industry 4.0: preconditions for the economic effectiveness of collaborative and mobile robotics

Amid Kazakhstan’s accelerated digitalization and national smart-manufacturing agenda, this paper presents a practice-oriented economic framework for evaluating, at the pre-design stage, the feasibility of deploying collaborative and mobile robotics in the automotive industry. The goal is to align engineering choices with production economics before on-site trials, reducing the risk of inflated expectations and showcase-only pilots. Methodologically, the framework combines conceptual modeling with quantitative screening: it decomposes total cost of ownership into capital and operating elements; maps operational effects across body/assembly stations, quality control, and inplant logistics; and ties these effects to measurable KPIs – overall equipment effectiveness (and its Availability- Performance-Quality factors), cycle time, defect rates, planned/unplanned downtime, and safety incidents. A distinctive feature is the explicit integration of infrastructure constraints and risk factors – precision and calibration requirements, connectivity and communication quality, safety for human – robot collaboration, cybersecurity exposure, and workforce acceptance – into both the economics and a managerial go/no-go checklist. The framework yields (i) a reproducible pilot → expand → scale pathway with milestone metrics, (ii) a structured data package to enable subsequent statistical verification and learning across pilots, and (iii) adaptable accounting rules that fit local procurement and budgeting practices. By making trade-offs transparent and context-aware, the approach supports Kazakhstani automotive firms in selecting viable use cases, sizing investments, and sequencing deployments in line with national digitalization priorities

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