Abstract
Production system flexibility has become an important factor to meet the needs of diversified markets in an ever-changing and turbulent market environment. Thus, this paper addresses the problems of flexibility evaluation for decision making by evaluation method driven by digital twin, which models, predicts, and evaluates the flexibility of a given production system design scheme (PSDS). Based on the definition and characteristic analysis of flexibility in the production system design phase, and combined with data modelling (static function model (SFM) and dynamic prediction model (DPM)) and data analysis (AHP-based and simulation-based analysis), the proposed framework evaluates system flexibility from the static and dynamic levels, helps enterprises quickly obtain the system’s comprehensive flexibility evaluation index, realizing the rapid screening of the production system design scheme (PSDS). The successful application of the evaluation framework in case enterprise has fully proved the feasibility and effectiveness of the method.
Highlights
Customized production systems have become an important means for enterprises to meet the current manufacturing market in facing the demand for multivariety and personalized products [1–3]
It can be seen that the comprehensive flexibility evaluation index of Scheme B is 6.19905, which is larger than 1.51175 in Scheme A
To meet the needs of diversified markets in an ever-changing and turbulent market environment, a novel digital-twin-driven approach for rapid flexibility evaluation of production systems is proposed, which contribute to the production system design scheme (PSDS)
Summary
Customized production systems have become an important means for enterprises to meet the current manufacturing market in facing the demand for multivariety and personalized products [1–3]. Digital twin refers to the process and method of describing and modelling a physical object’s characteristics, formation process, and performance using digital technology It can simulate the behaviour and performance of the entities in real time based on information collection and sharing [18]. The digital model realizes the analysis of system performance in the production system design phase (real-time data sharing cannot be automatically realized) It is the basis for the construction of flexibility-oriented digital twin in the production and operation of the actual production system. Driven by the digital twin technology, there are still many challenges in building a flexibility-oriented digital model for production systems, as well as to study system flexibility and help system development.
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