Research On Proactive Scheduling And State Evaluation Of Workshop Process Logistics Driven By Situation Data

The rapid development of big data and Internet of Things has brought new opportunities for the transformation and upgrading of manufacturing industry,which pushes the manufacturing industry from the traditional manufacturing mode to the advanced intelligent manufacturing.As a microcosm of the Internet of Things in the workshop,the Internet of manufacturing things makes the elements and links of workshop process logistics form a pattern of “ubiquitous and interconnection and perception”,which provides technical support for realizing the real-time macro-control of the workshop process logistics under the intelligent manufacturing mode to improve the operation efficiency of the workshop production activities.Taking the mixed discrete workshop as the research object,according to the fusion mechanism of the Internet of manufacturing things and workshop production activities and combining with the intelligent algorithm and the complex network theory,the author studied the static planning and dynamic real-time adjustment of workshop process logistics and the quantitative evaluation of process logistics status.As for the mixed production scheduling problem of workpieces,the mathematical model of process logistics is established,and a genetic algorithm with adaptive crossover and mutation probability is proposed,the initial generation method,fitness function,individual crossover method are improved and expanded.Under the conditions of equipment constraints and process constraints,and aiming at minimizing the makespan,the improved adaptive genetic algorithm is used to solve the planning problem of process logistics.As for the process delayed completion caused by internal uncertainties,the mechanism of the effect of process delay on the makespan delay rate and the character of processes scheduled are analyzed,and a proactive scheduling strategy is proposed.According to the idea of interconnection,dynamic perception and real-time control of Internet of manufacturing things,real-time monitoring the actual completion time of each process and comparing it with its own time parameters,and then the remaining process is right-shifted or partially adjusted based on the comparison results,thus reduce the makespan delay rate under the promise ofensuring that the process logistics is orderly operated according to the original scheduling plan.As for the complex coupling relationship among the workpiece and and equipment in process logistics,based on the schematic description of process logistics,a process logistics network model based on hypergraph is established from the perspective of complex network theory.The network performance and the relations among network components are quantitatively evaluated from two aspects of topological characteristics and physical attributes,and a evaluation method of equipment notes based on technique for order preference by similarity to an ideal solution(TOPSIS)and analytic hierarchy process(AHP)is proposed,which provides a basis for guiding the reliable operation of workshop production activities.At last,a prototype system with three functions of process logistics planning,real-time proactive scheduling and logistics state evaluation is developed by using MATLAB software,and an example was given to verify the correctness and feasibility of proposed models and methods.