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Smart manufacturing nudging design and personalization for human-automation symbiosis: conjoint prospect theoretic modeling of behavioral economics
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DOI：10.1080/0951192X.2026.2628816.png)
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Abstract
En 中文
Industry 5.0 advances a human‑centric paradigm where human – automation symbiosis (HAS) depends on aligning operator cognition with automated precision. This paper proposes manufacturing nudging as an engineering mechanism to steer operator behavior while preserving autonomy and develops a complete pipeline for nudge design and personalization at production scale. First, a conjoint prospect‑theoretic model captures dual stakeholder valuations – operators (workload, burden) and managers (quality, cycle time) – and aggregates multiple nudging features via cumulative prospect theory to reflect realistic risk, loss‑aversion, and probability‑weighting effects. Second, hierarchical Bayesian parameterization supports customization (segment‑level) and personalization (operator‑level) with coherent prior constraints and MCMC‑based estimation. Third, an engineering‑cost model estimates operation cycle time with a neural network trained on operator – nudge – scenario data. Finally, a two‑dimensional genetic algorithm (2D‑GA) optimizes operator‑to‑nudge assignments, exploiting a matrix encoding that preserves operator × feature structure and thereby circumvents the sparsity and locality issues of 1D encodings. A jet‑engine assembly case study with AR‑based nudges demonstrates increased symbiotic value with controlled cycle‑time cost; optimizing purely for behavioral value yields only a 0.15% gain but a 3.33% higher cost, whereas the multi‑objective formulation attains near‑maximal value at substantially lower cost. The results establish a rigorous, scalable, and interpretable approach to nudging for HAS in complex
Keywords:
Behavioral economics
nudging design
smart manufacturing
human-automation symbiosis
human-centric production systems
prospect theory
industry 5.0
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