Optimization of decoupling point position using metaheuristic evolutionary algorithms for smart mass customization manufacturing.

ABSTRACT: In this paper, we present two metaheuristic evolutionary algorithms-based approaches to position the customer order decoupling point (CODP) in smart mass customization (SMC). SMC tries to autonomously mass customize and produce products per customer needs in Industry 4.0. SMC shown here is from the perspective of arriving at a CODP during manufacturing process flow designs meant for fast moving and complex product variants. Learning generally needs several repetitive cycles to break the complexity barrier. We make use of fruit fly and particle swarm optimization (PSO) evolutionary algorithms with the help of MATLAB programming to constantly search better fitting consecutive process modules in manufacturing chain. CODP is optimized by increasing modularity and reducing complexity through ev

SUBMITTER: James CD 

PROVIDER: S-EPMC7785933 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature