Research On Flexible Jop Shop Scheduling Model For Energy Consumption And Development Of Data Monitoring System

Reducing energy consumption and solving the unreasonable distribution of processing tasks are one of the basic guidelines for the sustainable development of China's machinery manufacturing industry.Relevant research has been conducted on the innovation of flexible jop shop scheduling optimization model for energy consumption and the development of data monitoring systems.Part of the necessary theoretical reference is provided for the efficient use of energy in flexible operation workshops of machinery manufacturing enterprises.First of all,the operation status of the machine in a flexible processing workshop in a complete processing cycle is divided into some stages.Analyze the energy consumption characteristics and duration of each stage of machine.Introduce the energy consumption model of machine into the two factors of the batch of workpieces and whether the machine is adjusted.Taking the energy consumption of machine tools and the completion time of workpieces as optimization goals and establishing a flexible job shop scheduling model for direct production equipment energy consumption.Full consideration of the energy consumption caused by auxiliary equipment such as workpiece transportation and environmental maintenance in the processing process will also have a significant impact on the on-site production scheduling to a certain extent.First,analyze the energy consumption characteristics and running time of auxiliary equipment.The total energy consumption composed of direct production energy consumption and auxiliary energy consumption is defined as workshop energy consumption.The workshop energy consumption and completion time of the workpiece are the common optimization goals and a set of flexible job shop scheduling models oriented to the workshop energy consumption is established.Secondly,the method of solving the scheduling model is studied.In order to quickly find an accurate solution,the basic genetic operator is improved and the crossover and mutation probability that can be adaptively changed.Verify the performance and effectiveness of the algorithm.Faced with the occurrence of randomness of dynamic events,a theoretical method of dynamic scheduling rescheduling is proposed.Aiming at the data requirements of the scheduling model in solving engineering,a real-time data monitoring system for multiple machine tool stations in the machining workshop with PLC as the core was developed.The system's hardware framework,program execution process and development process to elaborate.Finally,the application cases are introduced into two sets of flexible job shop scheduling models for energy consumption and accurate and fast solution.By comparing the data of four different scheduling schemes,the best static initial scheme is selected.The entire batch of single-process processing data is used to verify the validity and practicability of the scheduling model.Taking the newly added workpiece insertion orders and machine tool failures as dynamic events,the method of dynamic scheduling of flexible job shop is studied.