| Emerging technologies such as big data,the Internet of Things,and cloud computing are profoundly changing the development concepts and methods of traditional manufacturing,and promote the development of manufacturing in the direction of automation,information,and intelligence.The Internet of Manufacturing Things(Io MT)is produced by the deep integration of Internet of Things technology,communication technology,information technology,and manufacturing.It is a new type of intelligent manufacturing mode that can obtain real-time information about various manufacturing resources in the workshop by constructing a production process perception network.This paper takes the workshop real-time data-driven production scheduling as the main line of research.First,it studied the discrete workshop data perception,data transmission and data processing methods under the Io MT,then studied the discrete workshop static and dynamic scheduling models and algorithms.Finally,a set of intelligent workshop management system was developed based on the research results of this article,and it was applied and verified in a typical discrete manufacturing workshop.The specific work is as follows:(1)The current research status of this topic at home and abroad was analyzed and explained from the perspectives of the Io MT,discrete workshop intelligent perception and discrete workshop production scheduling.(2)The intelligent perception and production scheduling problems of discrete workshops under the Io MT was analyzed.First,this paper clarified the definition,technical characteristics and architecture of the Io MT,and then analyzed the intelligent perception objects,feasible perception methods and communication technology for discrete workshops.Finally,the characteristics of the discrete workshop scheduling problem and the commonly used evaluation indicators were analyzed.(3)The intelligent perception platform of discrete workshop based on the Io MT was studied.First the overall architecture of the platform was planned,and then the implementation of each level of the platform was studied: In terms of data perception,this paper designed the RFID perception network and coding rules for the discrete manufacturing environment,and established the OPC UA abstract model of the discrete workshop equipment;in the aspect of data transmission,this paper designed a Io MT gateway to make the different communication protocol which collected from the workshop uniformly convert to the MQTT protocol;in terms of data processing,this paper developed an improved sliding window RFID data cleaning algorithm and established a dynamic and static correlation model of multi-source data in the workshop.Complex event processing technology was used to define workshop event extraction rules and obtain various basic and complex events from the associated data.Finally,the performance of the platform was verified through instances.(4)The discrete workshop scheduling algorithm driven by complex events was studied.First,this paper established a discrete workshop static and dynamic scheduling model,and then studied an improved hybrid Jaya algorithm,combined with the NSGA-II algorithm and the neighborhood search algorithm.This paper developed a Jaya discrete update operator,improved the elite retention strategy,and designed a new neighborhood search structure.The performance of the algorithm was verified by the algorithm comparison and example simulation;for dynamic job shop scheduling problems,a complex event-driven dynamic rescheduling strategy was proposed.This paper introduced the driving mechanism,built the rescheduling object model,and studied the rescheduling decision method.The effectiveness of the dynamic rescheduling strategy was verified through examples.(5)A set of intelligent workshop management system for discrete manufacturing was developed based on the research results in this paper.The functional modules,technical architecture and database structure of the system were introduced,and finally the actual operation of the system was shown. |
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