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Intelligent optimization of component onsertion in multi-head concurrent operation PCBA machines
TLDR
A knowledge-based component placement system (CPS) which incorporates optimization algorithms is presented for a sophisticated but popular multi-head concurrent assembly machine.
Supply chain dynamics and optimization
TLDR
It is shown that reduction of coordination dynamics is an alternative solution to structural re‐engineering, e.g. shortening manufacturing and transport lead times and investigates the dynamic performance of both centralized and decentralized coordination mechanisms.
CPS: a productivity tool for component placement in multi-head concurrent operation PCBA machines
The placement of surface-mounted components is an essential stage in printed circuit board assembly (PCBA). A reduction in production time of placement through efficient process planning will
A case for intelligent representation of dynamic resources in simulation
TLDR
A new multiple type knowledge based method to model machine and labour without introducing additional complexity is proposed, which integrates fuzzy and precise symbolic knowledge, deterministic and stochastic numerical knowledge to efficiently take all dynamic and Stochastic attributes into consideration.
ON IMPROVING THE PERFORMANCE OF HARD DISK DRIVE FINAL ASSEMBLY VIA KNOWLEDGE INTENSIVE SIMULATION
Traditional simulation studies focus almost exclusively on representing stochastic systems using random dynamics and/or precise dynamics. However, between these polar states lies the concept of muddy
Modelling business processes and enterprise activities at the knowledge level
TLDR
A formalism based on the computer-integrated manufacturing open-system architecture (CIMOSA) reference model is presented to specify the business processes and enterprise activities at the knowledge level to systematically represent enterprise behavior and functionality.
Intelligent Control Paradigm for Dynamic Discrete Event System Simulation
TLDR
A robust control mechanism is presented that is believed to add significant value to discrete event dynamic system, which utilises neural network feedforward control plus robust proportional derivative feedback control to achieve control performance and output stability.
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