| In manufacturing enterprise, based on continuous production in workshop, companies need to guarantee the storage capacity of finished product warehouse and its turnover efficiency to further ensure that finished product output into the market successfully. In the process, the optimization of finished product warehousing logistics has become an important issue, namely, how to arrange the pallet in the workshop offline buffer to get into the warehouse. As the most essential tool in that transportation work, the proper task assigned to forklift is of paramount importance. In this thesis, we are studying of the technological process of the finished product warehouse-in of the X Paint Manufacturing Enterprise in Guangdong province. At this enterprise, the forklift needs to transport end products into finished product warehouse promptly and locate them in right place. Due to the large number of workshops and warehouses and the forklift’s frequent move between workshops and warehouses, there are lots of difficulties in the task assigned to the forklift. First, the lack of efficient identification during the process of warehousing causes the forklift operator operating the warehousing only by memory and experience, which is time-consuming and error-prone, greatly reducing the efficiency and the accuracy of data collection. Second, the forklift managers have no effective mechanism of task allocation. They assign forklift transportation task by their experience. Thus, work efficiency is low overall. The two problems mentioned above lead to the failure in continuous production and the chaotic location planning in the warehouse because of the narrow space in the workshop offline buffer, which further affect cost and competitiveness of the entire enterprise.Internet of things (IOT) collect information on real-time monitoring and information sharing to achieve optimal allocation of inside manufacturing forklift tasks. This thesis chooses IOT technology to solve the forklift during transport information collection difficult problem, and real-time data collection as the basis for research forklift optimization task allocation problem.Firstly, according to the operation mode characteristics of the enterprise’s production and offline in each workshop, the warehouse location plan and the forklift transportation operation, the key issues on forklift transportation operation is analyzed and the resources of forklift transportation operation is transformed by using IOT. A forklift transportation working environment and an AUTOM basic information architecture on the IOT have been set up.Secondly, when it comes to a optimal task allocation of forklift transportation in the finished product warehousing logistics, a dynamic task allocation mechanism is presented, and a task-ranking mathematical model has been established, and a genetic algorithm (GA) based on the IOT environment has been designed.Finally, a optimal task allocation module of forklift transportation has been designed and developed on the foundation of the finished product logistics management system on the IOT. The module uses B/S structure. Besides, mechanism of optimal task allocation of forklift transportation is applied to the core function of the module---automatic task allocation, which has realized the automatic optimization of the forklift transportation task allocation. The system has been operated at X Paint Manufacturing Enterprise in Guangdong province, bringing significant improvements in the efficiency of workshops and warehouses. Workshop’s continuous product rate has increased more than 95%. Warehouses location has realized rapid release and turnover---on average every single stock reduces taking time by more than 20%. |
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