An integrated model for production line balancing planning

Automobile manufacturing is one of the most important industries in the world.The production line is one of the main supply chain of this industry.The production line consists of four shops.The shops include many stations. Each station has several variables such as car parts,materials, task's number,cycle time,number of workers,etc.The task's numbers depend on the number of car parts and pieces depending on the type of car.To complete tasks at the station,the workers need time to weld the pieces to the structure of the car.The cycle times of these tasks are not equal in each station and shop.The unbalance cycle time stations create queuing and idle time.The Production Line Balancing Problem (PLBP) is one of the main focuses of research in automobile manufacturing.The problem in PLBP is the queuing and the idle time during task achievement that is an obstacle to efficient assembly line.Moreover,the unbalancing problems also include the tasks number and the number of workers among the stations.In addition,the unbalancing problem includes the unbalance between the quantity of the customers demand and the production quantity,which are the Production Line Planning (PLP) problems.This study used a new method to solve these problems.The new method is the Multi-Objectives Model (MOM) combined with the Genetic Algorithm(GA)system (MOM/GA). Furthermore,the Simulation Model(SM)is used to solve the PLP problem to achieve the customer order by increasing the quantity of production.The new approach is called Hybrid Model of the Production Line (HMPL) which is a combination of MOM,GA,and SM.This approach is employed to solve the production line problems and to develop the efficiency of the production line.As a result,the Mixed Model(MM)that combines the MOM and GA is developed to solve the PLBP and efficiency of the Production Line System(PLS)in order to reduce the queuing and the idle time to obtain the best balance among the stations.Also the MM is applied to PLS to re-regulate the tasks'number and re-distribute the jobs to the workers among the stations in order to obtain the optimum solution.On the other hand,the SM is applied to solve the planning problem to make new plans then to make several strategies to solve the PLP problem and to achieve the customer orders.The aim of this study is to combine MM and SM to develop the efficiency of the production line and to solve both problems by using the output of MM as an input for SM and vice versa.This is a new method to obtain the best or the optimum balance among the stations and also between the quantity of customers demand and the production quantity.The method increased the ratio of production and reduced the queuing and idle time by minimizing the queuing and idle time and maximizing the productions,as well as balancing the tasks’number and distributing the jobs to the workers evenly