Integrated Optimization Of Production Planning And Scheduling For Fixed-Position Assembly Workshop With Rework

The rework of the non-conforming products usually contains three aspects: parts rework,products rework and after-sales products sent back to the factory for repair.It does exist in the manufacturing system.Especially in the fixed-position assembly workshop,the rework characterized by uncertainty leads directly to the production schedule infeasible,and furthermore affects the execution of production plan.Therefore,in this dissertation,focused on the fixed-position assembly workshop,the integrated optimization of production planning and scheduling under circumstances of parts,products and after-sales products rework will be investigated.In order to reduce the influence of rework disturbance on production management,the methods of adding the detecting unit,delaying rework process,and setting the dedicated process time of rework job are proposed.The models of the integrated production planning and scheduling under circumstances of parts,products and after-sales products rework in the fixed-position assembly workshop are established,and the constraints of available starting time of operations and assembly groups are proved.By studying the structure and characteristics of the integrated model,fast and effective solution techniques are developed.Examples are operated and analyzed to inspect the feasibility of the models and algorithms.Furthermore,the theoretical system of the integrated optimization of production planning and scheduling under uncertainty is supplemented.The main contents of this dissertation are summarized as follows:1.The integrated optimization of production planning and scheduling for fixed-position assembly workshop with uncertain re-entrance is studied.The integrated optimization scheme of production planning and scheduling based on stochastic expected value programming is proposed.The fixed-position assembly workshop with uncertain re-entrance exist the phenomenon that the different manufacturing processes in one job may repeat at the same equipment,and the number of repeats depends on the process result of the previous operation and is uncertain.It brings great difficulty to make the production plan.In order to meet the demand of the integration management between plants and workshops,the characteristic of fixed-position assembly workshop is analyzed.Under the condition that the passing probability distribution of jobs quality test is known,the value of expectation is used to describe the uncertainty of re-entrance and a bi-level stochastic expected value model of the integrated production planning and scheduling is presented,in which the upper-level is the production planning model with capacity restriction aiming at minimum cost and the lower-level is the scheduling model of fixed-position assembly workshop with uncertain re-entrance.Meanwhile,the recursion formula of the feasible scheduling solutions is proved.Then an alternant iterative method with a bi-level structure by modified genetic algorithm is proposed.Elite genetic algorithm is applied to solve the problem of production planning in the upper-level,and the genetic simulated annealing algorithm based on stochastic simulation is applied to solve the problem of scheduling in the lower-level.The production plan is obtained in the upper-level firstly and then put into the lower-level in order to get the schedule.In turn,the schedule is put into the upper-level to get the new plan.By such alternant iterative process,the optimization of the production planning and scheduling is achieved simultaneously.Finally,the result of simulation examples indicates that the established model and the proposed algorithm are effective.It provides a feasible method to make the production planning for fixed-position assembly workshop with uncertain re-entrance.2.The integrated optimization of production planning and scheduling for fixed-position assembly workshop with parts rework is investigated.In order to reduce the influence of rework disturbance on production management,the method of adding the assembly detecting units in the parent workpieces during assembly is presented.With the known interval data that the amount of parts rework belongs to,a bi-level model of the integrated production planning and scheduling for the fixed-position assembly workshop is established.The upper-level is the production planning model with maximum benefit.The lower-level is the mean-variance scheduling model based on scenario analysis,in which the uncertainty of rework in every detecting unit is expressed in different scenarios.Then constraints of available starting time of operations and assembly groups in every scenario are proved.By studying the structural complexity of the integrated model,an alternant iterative method with a hierarchical structure by genetic-memetic algorithm is proposed to solve the model.Meanwhile the local search criteria of the algorithm are proved.Finally,simulation examples demonstrate that the proposed method is feasible and useful.3.The integrated optimization of production planning and scheduling for fixed-position assembly workshop with nonconforming products rework is studied.An integrated optimization method for the production planning and scheduling based on delaying rework is raised.By analyzing the character of the fixed-position assembly workshop and its rework procedure,the nonconforming products of every cycle are put into the buffer,and then the production plan and schedule will be adjusted at the beginning of its next cycle.Firstly,on the condition that the nonconforming rate of every type of products in each circle is known,the model of rough-cut production planning with maximum benefit based on delaying rework is built and solved by genetic algorithm.Then this plan is delivered and performed.Aiming at the nonconforming products needing rework in practical assembly,the production plan is adjusted by dichotomy,and its corresponding schedule is optimized by memetic algorithm,in which the local search criteria is proved according to the characteristics of the model.Both of them are alternated and interacted,and identified whether to satisfy the requirement of load rate of assembly teams until optimization and balance of the production plan and schedule are achieved simultaneously.Finally examples demonstrate that developed models and the algorithm are feasible and useful.It shows that the impact of rework on the production planning and scheduling can be defused by the proposed method effectively.4.Integrated optimization problem of production planning and scheduling for fixed-position assembly workshop with uncertain after-sales products sent back to the factory for repair is discussed.Hybrid mode is presented to dispose after-sales products sent back to the factory for repair in two stages.For the first stage,the method of reserving idle time,which is used to absorb interference from the after-sales products maintenance,is proposed with estimated values of products sent back to the factory for repair.The multi-scenario model of idle time is constructed.Improved migrating birds optimization algorithm,with the feasible property of neighborhood search and the heuristic rules proved,is proposed to calculate the model.Afterwards the integrated optimization model of production planning and predictable scheduling with idle time is presented,and solved by the bi-level alternative and iterative algorithm of genetic-migrating birds optimization algorithm.Consequently,the production plan and predictable schedule including the situation of the after-sales products maintenance are obtained.For the second stage,when the maintenance events happen during executing the predictable schedule,the reactive schedule procedure is adopted on the basis of the idle time.Finally,the examples demonstrate that this method can be sure to complete the production plan,dispose the after-sales products maintenance,and finally optimize the production plan and schedule simultaneously.