|Keyword||Case-based Reasoning, Integrated System, Quality Designing, Scheduling, Process Control, Steel Industry|
|Abstract||To cope with the rapid changes in business environment, typical large-scale complex industries such as the steel industry are in the process of building computer integrated production systems to strengthen competitiveness by promoting the flexibility and productivity of the production system. In particular, the promotion of the productivity and flexibility of the production process in the steel industry has been regarded as a core element in effectively meeting changes in the market. Despite such importance, however, few studies have been conducted to promote productivity and flexibility during the process of solving various problems in the steel industry. Promoting productivity and flexibility in the steel industry requires appropriate planning and execution of quality design and process control. The problem is extremely difficult and complicated because not only should the basic restraints in the quality design stage be considered but also the process planning and process capability during the process control stage be taken into account to realize said purposes.
To date, research activities carried out to solve such problems have approached overall problems by segregating them into several stages. However, it still is difficult to obtain an optimal solution even for the segregated problem within a realistic timetable. In addition, it raises yet another problem, i.e., difficulty to set targets that enhance the achievement level in process management during the quality design stage. This study is a result of an effort to develop a structure and solution of an integrated system that can make decisions regarding quality design, scheduling, and process control. At the same time, the solution improves the flexibility of the steelmanufacturing process by integrating and solving problems related to quality design and process management in the steel industry.
The proposed integration system is composed of a structure that solves the entire problem by linking three modules: (1) “quality design generation module,” which creates quality design; (2) “module that maximizes productivity in scheduling,” which considers the alternatives derived from quality design, and; (3) “process control module,” which seeks to achieve the optimum level of accomplishment in the process where the deduced quality design and scheduling are executed.
The quality design formation module presents a solution that creates optimum quality design using the case-based reasoning methodology. This module proposes and uses a fuzzy similarity index and a productivity maximization index to evaluate similar cases. It also presents a solution that can deduce a new alternative plan for quality design according to the requirements of customers, thereby suggesting its superiority as verified through experiments.
The scheduling creation module is based on the formulation of the Bin-Packing problem, which is characterized by several alternative plans for quality design and many customer orders. After developing the corresponding solution, the appropriateness and efficiency of the solution were verified through experiments.
Finally, the process control module seeks to achieve the optimum accomplishment level of the steel-making process where quality design and scheduling are executed. It proposes a forecast module for process control using a case-based reasoning methodology. The application of the model to experimental problems and to real industrial problems proved the superiority of the proposed solution. Moreover, since the process control module may work independently from the quality design and scheduling modules, it can be used effectively in the existing steel industry.
From the experiments, the resulting integrated approach exhibited superiority in terms of the accomplishment level compared to the existing step by step approach. Since the difference tends to increase gradually as the number of alternatives for quality design increases, the integrated approach is found to be more useful in solving actual problems.
This study contributed in raising productivity of the steel industry by integrating and giving solutions to quality design and process control problems of the steel industry, where alternative plans for quality design exist.
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