An Application of Systems Modelling in Steel Production Scheduling

1985 ◽  
pp. 949-962 ◽  
Author(s):  
Jeff R. Wright ◽  
Mark H. Houck
Keyword(s):  
Production Scheduling ◽  
Steel Production ◽  
Systems Modelling

A new knowledgeable encapsulation method of steel production scheduling model

2020 ◽  
Vol 234 (14) ◽  
pp. 1673-1685
Author(s):  
Xiaowu Chen ◽  
Guozhang Jiang ◽  
Gongfa Li ◽  
Ying Zuo ◽  
Feng Xiang
Keyword(s):  
Production Scheduling ◽  
Steel Production ◽  
Mapping Method ◽  
Interface Model ◽  
The Core ◽  
Scheduling Model ◽  
Encapsulation Method ◽  
The Relationship ◽  
Knowledge Encapsulation ◽  
Web Platform

The steel production scheduling is a typical continuous/discrete hybrid process; it is dynamic and difficult to predict. The scheduling model is the core object of steel production scheduling, and its modeling methods directly affect the precise decision-making and execution efficiency of scheduling. However, the current linear program and simulation model do not yet realize the scheduling model quick reuse and dynamic construction. Therefore, a new model knowledgeable encapsulation method is proposed, which consists of a knowledgeable encapsulation framework and knowledgeable mapping method. The knowledgeable encapsulation framework includes the model knowledge description interface, model knowledge publication interface, model knowledge behavior interface, and a web platform. The interfaces and the platform are designed to help model providers to encapsulate the scheduling model in an open network environment. The mapping method is constructed to strengthen the relationship between the model knowledge. Finally, a knowledge encapsulation platform is established to verify the effectiveness of the model knowledge encapsulation method.

Steelmaking-Hot Rolling Scheduling Model and Method for Integrated Management in Iron and Steel Enterprises

2013 ◽  
Vol 860-863 ◽  
pp. 3094-3099 ◽  
Author(s):  
Bao Lin Zhu ◽  
Shou Feng Ji
Keyword(s):  
Production Scheduling ◽  
Integrated Management ◽  
Steel Production ◽  
Optimal Solution ◽  
Scheduling Problems ◽  
Planning And Scheduling ◽  
Iron And Steel ◽  
Scheduling Model ◽  
General Production ◽  
Iron And Steel Production

Iron and steel production scheduling problems are different from general production scheduling in machine industry. They have to meet special demands of steel production process. The CCR production manner dramatically promotes the revolution in technology and management, especially to planning and scheduling. In this paper, a scheduling model is presented to integrate the three working procedures and the lagrangian relaxation technology is proposed to get the optimal solution of the scheduling model. Finally, numerical examples are given to demonstrate the effectiveness of the integrated model and method.

scholarly journals OPTIMASI JUMLAH PRODUKSI BAJA RINGAN MENGGUNAKAN METODE LINEAR PROGRAMMING

2020 ◽  
Vol 3 (2) ◽  
pp. 313
Author(s):  
Willis Thedra ◽  
Iwan B. Santoso
Keyword(s):  
Linear Programming ◽  
Mild Steel ◽  
Production Planning ◽  
Production Scheduling ◽  
Raw Materials ◽  
Steel Production ◽  
Working Hours ◽  
The Real ◽  
Different Thickness ◽  
Production Target

AbstractLinear programming can analyze various constraints related to the real conditions in the company and provide the best solution. In this research, light steel production planning is carried out for 6 working days, where there are 4 types of mild steel products with different thickness. With this method, production scheduling is obtained per day and the profit gained during the week is, when the price of raw materials is normal, a profit of Rp 179,005,800 was obtained; when the price of raw materials decreased, a profit of Rp 171,143,000 was obtained, and when the price of raw materials rose, a profit of Rp 205,766,400 was obtained. In this study several scenarios were conducted, such as scenario 1, the machine used must not be damaged on the first day of production because the production target will not be achieved, then for scenario 2 an increase in the number of requests was 10% and for scenario 3 the reduction in working hours was obtained for a maximum of one hour, if more than one hour the production target will not be achieved.AbstrakPemrograman linier dapat menganalisis berbagai kendala terkait dengan kondisi nyata di perusahaan dan memberikan solusi terbaik. Pada penelitian ini dilakukan perencanaan produksi baja ringan untuk 6 hari kerja, dimana terdapat 4 jenis produk baja ringan dengan ketebalan yang berbeda-beda. Dengan metode ini didapatkan penjadwalan produksi per hari dan keuntungan yang didapat selama seminggu yaitu, pada saat harga bahan baku normal maka diperoleh keuntungan sebesar Rp 179.005.800,-; saat harga bahan baku turun diperoleh keuntungan sebesar Rp 171.143.000,-, dan saat harga bahan baku naik diperoleh keuntungan sebesar Rp 205.766.400,-. Pada penelitian ini juga dilakukan beberapa skenario seperti skenario 1 mesin yang dipakai tidak boleh mengalami kerusakan pada hari pertama produksi karena target produksi tidak akan tercapai, kemudian untuk skenario 2 peningkatan jumlah permintaan sebesar 10% dan untuk skenario 3 pengurangan jam kerja diperoleh maksimal selama satu jam, jika lebih dari satu jam maka tidak akan tercapai target produksi.

Optimal inter-process steel production scheduling

1988 ◽  
Vol 15 (6) ◽  
pp. 497-507 ◽  
Author(s):  
Timothy L. Jacobs ◽  
Jeff R. Wright ◽  
Arthur E. Cobbs
Keyword(s):  
Production Scheduling ◽  
Steel Production

Design of integrated steel production scheduling knowledge network system

2017 ◽  
Vol 22 (S4) ◽  
pp. 10197-10206 ◽  
Author(s):  
Le Yang ◽  
Guozhang Jiang ◽  
Xi Chen ◽  
Gongfa Li ◽  
Tingting Li ◽  
...  
Keyword(s):  
Production Scheduling ◽  
Steel Production ◽  
Knowledge Network ◽  
Network System

Hot Rolling Batch Planning Problem Model Based on Genetic Algorithm

2012 ◽  
Vol 433-440 ◽  
pp. 2042-2046
Author(s):  
Hai Tao Li ◽  
Su Jian Li ◽  
Di Wu ◽  
Fang Han ◽  
Fang Wang
Keyword(s):  
Genetic Algorithm ◽  
Hot Rolling ◽  
Production Scheduling ◽  
Steel Production ◽  
Planning Problem ◽  
Planning Model ◽  
Improved Genetic Algorithm ◽  
Problem Model ◽  
Iron And Steel ◽  
Batch Planning

To solve the hot rolling batch planning problem in production scheduling of iron and steel enterprises, a hot rolling batch planning model is formulated based on multiple travelling salesmen problem(MTSP) model. The objective is to minimize the total limit penalty value of adjacent stripped steels in width, thickness and hardness. The main constraints include jumps in width, thickness and hardness between adjacent stripped steels, which are essential for steel production process. An improved genetic algorithm is designed to solve the model. A simulation example shows the reasonability of the model and validity of the algorithm.

scholarly journals Improving the Flexibility of Production Scheduling in Flat Steel Production Through Standard and AI-Based Approaches: Challenges and Perspectives

2021 ◽  
pp. 619-632
Author(s):  
Vincenzo Iannino ◽  
Valentina Colla ◽  
Alessandro Maddaloni ◽  
Jens Brandenburger ◽  
Ahmad Rajabi ◽  
...  
Keyword(s):  
Production Scheduling ◽  
Optimization Problems ◽  
Steel Production ◽  
Mixed Integer ◽  
Resource Exploitation ◽  
Product Price ◽  
Market Situation ◽  
Multi Agent ◽  
Flat Steel

AbstractIn recent years, the European Steel Industry, in particular flat steel production, is facing an increasingly competitive market situation. The product price is determined by competition, and the only way to increase profit is to reduce production and commercial costs. One method to increase production yield is to create proper scheduling for the components on the available machines, so that an order is timely completed, optimizing resource exploitation and minimizing delays. The optimization of production using efficient scheduling strategies has received ever increasing attention over time and is one of the most investigated optimization problems. The paper presents three approaches for improving flexibility of production scheduling in flat steel facilities. Each method has different scopes and modelling aspects: an auction-based multi-agent system is used to deal with production uncertainties, a multi-objective mixed-integer linear programming-based approach is applied for global optimal scheduling of resources under steady conditions, and a continuous flow model approach provides long-term production scheduling. Simulation results show the goodness of each method and their suitability to different production conditions, by highlighting their advantages and limitations.

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