摘要
Abstract
This study established a comprehensive chlorine balance early warning and control system based on Six Sigma(6σ)management and intelligent IoT technology.By developing a dynamic equilibrium mathematical model for Cl-involving six input sources(wood chips,mi-rabilite,NaOH,fresh water,recycled water,auxiliary materials)and five output categories(waste ash water,pulp,pulp residue,coarse resi-due,green mud,evaporation condensate),a blockchain-based material geographic information system(GIS)traceability platform was devel-oped.Integrating multi-parameter intelligent early warning algorithms,a closed-loop management system featuring a four-in-one approach of"monitoring-assessment-early warning-regulation"was constructed.Industrial validation demonstrated that after implementation at a pulp and paper enterprise,Cl-content in alkali ash from the recovery system stabilized at 20.1 g/kg(down from 22.3 g/kg),and waste ash water dis-charge from the alkali ash treatment system optimized from 9.40 m3/h to 8.55 m3/h,reducing alkali furnace ash accumulation.This minimized ash accumulation in the alkali furnace,maintained higher thermal efficiency,and decreased furnace cleaning frequency.关键词
Cl-平衡调控/智能预警系统/化学品流失控制/6σ管理/动态建模Key words
Cl-balance regulation/intelligent early warning system/chemical loss control/Six Sigma management/dynamic modeling分类
轻工纺织
