A Multidimensional Data Flow Driven-Based Quality Fluctuation Evaluation for Manufacturing Process

Abstract

Real-time evaluation quality fluctuation is an important way to ensure product quality in manufacturing process. This study proposes a multidimensional data flow driven-based quality fluctuation evaluation. Firstly, the multidimensional decomposition and transition mode analysis is carried out to reveal the essence of quality fluctuation. Then, the technique uses hierarchical network architecture to model the process, and quality fluctuation network is built to track fluctuation evolution trend; then, the node relative entropy measure is defined to statistically analyze the change of net-node state fluctuation. Finally, a case study is used to verify the proposed quality fluctuation evaluation approach.

A Network Modeling and Analysis Approach for Pharma Industry Regulatory Assessment

“…In another approach network modelling has been used to study phenomena occurring in interacting economical agents, such as bank bankruptcies, as well as relationships between shareholders, board directors, and stock prices [31]. In business ecosystems in particular, networks have been used to represent relationships and interactions between stakeholders, processes, products, and financial entities to identify bottlenecks, inefficiencies, and opportunities for improvement [19], [20], [32][33][34][35][36][37]. Recent research indicates that the simulated network structure flow can undergo changes over a specific period due to various events or changing circumstances, and hence, can be applied in dynamic environments as well (e.g.…”