A hybrid multi-criteria decision-making and cost-constrained optimisation framework for circular economy-oriented zero-defect intelligent manufacturing

Manufacturers pursuing smart digital transformations face the challenge of eliminating production defects while adhering to Circular Economy mandates under strict budget and labor boundaries. To bridge the gap between high-level sustainability preferences and discrete technology selection, this study proposes an integrated decision-making framework that combines the Decision-Making Trial and Evaluation Laboratory (DEMATEL), the Analytic Network Process (ANP), and Zero–One Goal Programming (ZOGP). DEMATEL first establishes the systemic causal interdependencies, revealing that Digital Manufacturing is the primary driver of Quality Management, which in turn delivers Circular Value and Financial ROI as downstream outcomes. ANP then incorporates network feedback to derive converged priority weights, establishing that financial viability and zero-defect quality reliability serve as mandatory survival gatekeepers, with data acquisition and precision inspection emerging as top strategic module priorities. Finally, ZOGP optimises discrete module selection under real-world operational limitations. Applied to a precision machinery manufacturer facing phased consulting budgets, certification limits, and internal labor capacity constraints, the model identifies the optimal implementation portfolio for the initial phase. Sensitivity analysis confirms that this core portfolio remains robust across strategic preference shifts and budget contractions. The proposed framework offers operations managers an empirically validated, financially viable, and non-disruptive roadmap for implementing zero-defect intelligent manufacturing systems.