BOMR-based Order-grouping&Charging Structure Optimization In Steel Enterprises

In recent years, the steelmaking manufacturing was facing a serious over-capacity problem in our country, the excessive output growth brought about abnormal fluctuation in steel prices, lowering the responsiveness to market diversification seriously in steel industry. Frequently fluctuation in raw material prices, dynamic bottleneck resources in the production process, with the multi-varieties and low volume production mode, making the traditional mode was no longer fit the steelmaking industry. All this brought great challenge to organization and management, causing extremely complication of manufacturing resource allocation and high production cost. The key to improve the situation is to design the mechanism of manufacturing resource allocation, solve the problem of decision optimization, thereby realizing the MTO production mode and capacity release.Reasonable modeling of manufacturing resources is the prerequisite and basis for its coordination and information sharing. The concept of Bill of Manufacturing Resources(BOMR) was defined, while the characteristics of product composition, process, capacity and production flows were analyzed in steelmaking enterprises. BOMR model was presented for steelmaking enterprises based on process disassembling&characteristic matching. In different production phases,"product-process" allocation describing matrixes and "process-capacity" consumption describing matrixes were constructed by means of processes identified information, and "Product-Process-Capacity" resources information relating framework was built to steel product manufacturing processes.Take the steelmaking-casting as example, manufacturing resource allocation process was introduced and order-grouping&charging composition optimization was proposed based on BOMR. Taking constraints of product structure, processing characteristics and due time, etc into consideration, firstly, an order-grouping optimization model, whose objective function was the minimization of redundant steel and penalties of tardiness/lead time, was built based on rules of order consolidation. Furnace number and processing path was derived. Afterward, according to information of product composition and capacity condition, a charging composition optimization model, whose objective function was the minimization of raw material cost and the minimum deviation of target component, was built based on rules of alloy formula in refining furnace. PSO algorithm was designed separately to solve above problems. The numerical experimental results show that BOMR were proved to be effective and practical for the configuration and integrity of manufacturing resources data description. The amount of redundant molten steel and the cost of alloy raw material were decreased while meeting the demand of due time. BOMR collated the corresponding relation of product demands and capacity in processes, and it can support manufacturing resources coordinating allocation and integration production management on complete&consistent process base-data information.