Production scheduling in a steelmaking-continuous casting plant

Pacciarelli, Dario; Pranzo, Marco

doi:10.1016/j.compchemeng.2004.08.031

Cited by 114 publications

(56 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In particular, the production scheduling of the enterprise can be described as the right allocation management in a production process, in which there are N machines in a workshop for production and processing, M processes are required for a product, each process is distributed on different machines, each of which can only process specific workpieces, and the next process can be performed only after one process is completed [6].…”

Section: Production Schedulingmentioning

confidence: 99%

Application and Dynamic Simulation of Improved Genetic Algorithm in Production Workshop Scheduling

Jiang¹,

Ding²,

Guo³

2018

Int. j. simul. model.

View full text Add to dashboard Cite

From the point of view of combining theories with practice, in order to better realize the effective management of production workshop scheduling and thus improve the competitiveness of manufacturing enterprises in the market, this study focuses on the simulation of production workshop scheduling based on genetic algorithm. Firstly, the study analyses the concept and characteristics of production workshop scheduling, and then proposes the objective function and scheduling rules of production workshop scheduling; the study also introduces the genetic algorithm to combine the scheduling rules, which are regarded as the genetic gene to realize the optimization of the production scheduling through the simulation calculation; in addition, in order to satisfy the dynamic production environment of manufacturing enterprises, the study put forward a dynamic scheduling model; finally, the dynamic simulation of the production workshop scheduling system is realized through the mixed programming of Matlab and VC. The simulation results show that the dynamic model can reduce the scheduling times and improve the stability of dynamic scheduling, and has a positive guiding significance for the production workshop scheduling of manufacturing enterprises.

show abstract

Section: Production Schedulingmentioning

confidence: 99%

Application and Dynamic Simulation of Improved Genetic Algorithm in Production Workshop Scheduling

Jiang¹,

Ding²,

Guo³

2018

Int. j. simul. model.

View full text Add to dashboard Cite

show abstract

“…Liu and Sun study the batch split strategy of optimal scheduling in steelmaking casting production [4]. Pacciarelli and Pranzo analyse the feasible condition of the model and the time relationship among all scheduling furnace units, and find the mass scheduling results through using the beam search algorithm [5]. Li et al develop the classic model and argue that every stage has two machines and used the rolling horizon scheduling algorithm to adjust and test [6].…”

Section: Introductionmentioning

confidence: 99%

Integrated Batch Planning Optimization Based on Fuzzy Genetic and Constraint Satisfaction for Steel Production

Su¹,

Yue²,

Jin³

2016

Int. j. simul. model.

View full text Add to dashboard Cite

This paper stablishes the model of the integrated batch planning process, and proposes an improved algorithm for this problem. The simulation results of a computerized scheduling system are given to prove the fitness of the model. The steel making casting production process scheduling problem is very difficult to get a good performance solution in practice. The scheduling of steelmaking casting production is a complicated problem of combinational optimization in the hybrid flow shop, which is an NP-Hard problem, and determining the polynomial time algorithm to arrive at the accurate optimal solution has proved to be a difficult task. An improved fuzzy genetic optimization and improved algorithm strategy are proposed. The results show that the method is very efficient in solving the steel casting production scheduling problem.

show abstract

“…2) An algorithm for rescheduling the affected operations in a job shop is presented in order to preserve as much as possible the robustness of the initial schedule, which is different from the right-shift rescheduling and complete rescheduling. 3) However, the research on scheduling method for SMCC production process focuses on static scheduling problem, [4][5][6] and rescheduling methods are rarely addressed. The development of a knowledge model including task, inference and domain, which describes the reasoning process in managing schedule disturbance in steel-making, is presented.…”

Section: Introductionmentioning

confidence: 99%

A Prediction Method for Abnormal Condition of Scheduling Plan with Operation Time Delay in Steelmaking and Continuous Casting Production Process

Yu¹

2013

ISIJ Int.

View full text Add to dashboard Cite

In the steelmaking and continuous casting (SMCC) production process, the operation time delay often occurs which may lead to planned casting break or processing conflict so that the initial scheduling plan becomes unrealizable. Existing rescheduling methods with disturbances firstly classify the disturbances according to the disturbance type and disturbance quantity only by artificial experience or rules, and then directly adjust initial scheduling plan with corresponding rescheduling method. Those methods don't analyze the influence degree of disturbances to the initial scheduling plan in detail, so the adjustment degree of initial scheduling plan is always too greater, which leads to the poor continuity and stability of initial scheduling plan. In this paper, the relation among operation time delay, planned casting break and processing conflict is deeply analyzed. Then a novel prediction method for abnormal condition of scheduling plan with operation time delay disturbance in SMCC production process is proposed including disturbance identification of operating time delay based on event-driven mechanism, analysis on charges based on reachability matrix, analysis on influence degree of disturbance and abnormal condition decision of initial scheduling plan. As a result, the real-time application shows that the proposed prediction method can timely and accurately predict the abnormal condition of the scheduling plan with operation time delay disturbance in SMCC production process, which can only adjust the affected charges that must to be rescheduled in the initial scheduling plan and reduce the frequency of complete rescheduling. The initial scheduling plan can also maintain the good continuity and stability.

show abstract

Production scheduling in a steelmaking-continuous casting plant

Cited by 114 publications

References 31 publications

Application and Dynamic Simulation of Improved Genetic Algorithm in Production Workshop Scheduling

Application and Dynamic Simulation of Improved Genetic Algorithm in Production Workshop Scheduling

Integrated Batch Planning Optimization Based on Fuzzy Genetic and Constraint Satisfaction for Steel Production

A Prediction Method for Abnormal Condition of Scheduling Plan with Operation Time Delay in Steelmaking and Continuous Casting Production Process

Contact Info

Product

Resources

About