Optimization Of Just-in-time Material Distribution For Mixed Model Assembly Line Considering AGV Energy Consumption

Implementing the strategy of "Made in China 2025",green and innovative development is the sure way for intelligent transformation and upgrading and sustainable development of China’s manufacturing industry.In the context of smart factory,mixed model assembly line plays the advantage of multi-item quantity and small batch production mode in product diversification and economic batch.With the wide application of AGV for material distribution in mixed model assembly line,how to optimize just-in-time material distribution decision by taking into account distribution efficiency and environmental economy objectives is still one of the practical problems that restrict mixed model assembly line to play the maximum design capacity.The paper presents a review of domestic and international research on material distribution and distribution AGV scheduling in mixed model assembly line.On the basis of the classical just-in-time material distribution model for mixed model assembly line,a dynamic planning method is used to construct a just-in-time material distribution model for mixed model assembly line considering the energy consumption of AGVs in a given assembly plan,against the background of the start-up sequence of mixed model assembly line and the known material demand of each workstation for different parts.(1)Based on the principle of cycle scheduling and energy efficiency objectives,the minimum lineside inventory and minimum energy consumption of AGVs are taken as the objectives,and the influence of the in-transit status of AGVs on the energy consumption of AGVs and their operation time is considered to determine the optimal number of cycles and the task combination scheme of each cycle to reduce the lineside inventory and energy consumption in the distribution process.(2)Based on the economic objectives,the optimal number of AGVs and the task and scheduling plan of AGVs are determined with the objectives of minimizing the number of AGVs and minimizing the lineside inventory,taking into account the high operating costs caused by too many AGVs and the risk of stock-outs caused by too few AGVs.A two-stage multi-objective integer planning model is developed,taking into account the economic and energy efficiency objectives.The paper also applies the Pareto optimal hybrid taboo search algorithm(P-TS algorithm for short)to jointly solve the two-stage optimization model,and the sensitivity analysis of the model parameters shows that the model has validity and stability;the analysis of different scale arithmetic cases shows that the model and algorithm are valid,and the energy saving effect of the model is demonstrated,and the sensitivity analysis of the model parameters shows that the total number of workstations N is a sensitive factor.Therefore,reasonable decision on the number of workstations for material supermarket and AGV service can further reduce the energy consumption and the amount of lineside material storage.