Line configuration and balancing is to select the type of line and allot a given set of operations as well as machines to a sequence of workstations to realize high-efficiency production. Most of the current researche...Line configuration and balancing is to select the type of line and allot a given set of operations as well as machines to a sequence of workstations to realize high-efficiency production. Most of the current researches for machining line configuration and balancing problems are related to dedicated transfer lines with dedicated machine workstations. With growing trends towards great product variety and fluctuations in market demand, dedicated transfer lines are being replaced with flexible machining line composed of identical CNC machines. This paper deals with the line configuration and balancing problem for flexible machining lines. The objective is to assign operations to workstations and find the sequence of execution, specify the number of machines in each workstation while minimizing the line cycle time and total number of machines. This problem is subject to precedence, clustering, accessibility and capacity constraints among the features, operations, setups and workstations. The mathematical model and heuristic algorithm based on feature group strategy and polychromatic sets theory are presented to find an optimal solution. The feature group strategy and polychromatic sets theory are used to establish constraint model. A heuristic operations sequencing and assignment algorithm is given. An industrial case study is carried out, and multiple optimal solutions in different line configurations are obtained. The case studying results show that the solutions with shorter cycle time and higher line balancing rate demonstrate the feasibility and effectiveness of the proposed algorithm. This research proposes a heuristic line configuration and balancing algorithm based on feature group strategy and polychromatic sets theory which is able to provide better solutions while achieving an improvement in computing time.展开更多
Reconfigurable products and manufacturing systems have enabled manufacturers to provide ＂cost effective＂ variety to the market. In spite of these new technologies, the expense of manufacturing makes it infeasible to...Reconfigurable products and manufacturing systems have enabled manufacturers to provide ＂cost effective＂ variety to the market. In spite of these new technologies, the expense of manufacturing makes it infeasible to supply all the possible variants to the market for some industries. Therefore, the determination of the right number of product variantsto offer in the product portfolios becomes an important consideration. The product portfolio planning problem had been independently well studied from marketing and engineering perspectives. However, advantages can be gained from using a concurrent marketing and engineering approach. Concurrent product development strategies specifically for reconfigurable products and manufacturing systems can allow manufacturers to select best product portfolios from marketing, product design and manufacturing perspectives. A methodology for the concurrent design of a product portfolio and assembly system is presented. The objective of the concurrent product portfolio planning and assembly system design problem is to obtain the product variants that will make up the product portfolio such that oversupply of optional modules is minimized and the assembly line efficiency is maximized. Explicit design of the assembly system is obtained during the solution of the problem. It is assumed that the demand for optional modules and the assembly times for these modules are known a priori. A genetic algorithm is used in the solution of the problem. The basic premise of this methodology is that the selected product portfolio has a significant impact on the solution of the assembly line balancing problem. An example is used to validate this hypothesis. The example is then further developed to demonstrate how the methodology can be used to obtain the optimal product portfolio. This approach is intended for use by manufacturers during the early design stages of product family design.展开更多
基金Supported by Shanghai Municipal Science and Technology Commission(Grant No.12JC1408700)National Science and Technology Major Project of the Ministry of Science and Technology of China(Grant Nos.2013ZX04012-071,2011ZX04015-022)
文摘Line configuration and balancing is to select the type of line and allot a given set of operations as well as machines to a sequence of workstations to realize high-efficiency production. Most of the current researches for machining line configuration and balancing problems are related to dedicated transfer lines with dedicated machine workstations. With growing trends towards great product variety and fluctuations in market demand, dedicated transfer lines are being replaced with flexible machining line composed of identical CNC machines. This paper deals with the line configuration and balancing problem for flexible machining lines. The objective is to assign operations to workstations and find the sequence of execution, specify the number of machines in each workstation while minimizing the line cycle time and total number of machines. This problem is subject to precedence, clustering, accessibility and capacity constraints among the features, operations, setups and workstations. The mathematical model and heuristic algorithm based on feature group strategy and polychromatic sets theory are presented to find an optimal solution. The feature group strategy and polychromatic sets theory are used to establish constraint model. A heuristic operations sequencing and assignment algorithm is given. An industrial case study is carried out, and multiple optimal solutions in different line configurations are obtained. The case studying results show that the solutions with shorter cycle time and higher line balancing rate demonstrate the feasibility and effectiveness of the proposed algorithm. This research proposes a heuristic line configuration and balancing algorithm based on feature group strategy and polychromatic sets theory which is able to provide better solutions while achieving an improvement in computing time.
文摘Reconfigurable products and manufacturing systems have enabled manufacturers to provide ＂cost effective＂ variety to the market. In spite of these new technologies, the expense of manufacturing makes it infeasible to supply all the possible variants to the market for some industries. Therefore, the determination of the right number of product variantsto offer in the product portfolios becomes an important consideration. The product portfolio planning problem had been independently well studied from marketing and engineering perspectives. However, advantages can be gained from using a concurrent marketing and engineering approach. Concurrent product development strategies specifically for reconfigurable products and manufacturing systems can allow manufacturers to select best product portfolios from marketing, product design and manufacturing perspectives. A methodology for the concurrent design of a product portfolio and assembly system is presented. The objective of the concurrent product portfolio planning and assembly system design problem is to obtain the product variants that will make up the product portfolio such that oversupply of optional modules is minimized and the assembly line efficiency is maximized. Explicit design of the assembly system is obtained during the solution of the problem. It is assumed that the demand for optional modules and the assembly times for these modules are known a priori. A genetic algorithm is used in the solution of the problem. The basic premise of this methodology is that the selected product portfolio has a significant impact on the solution of the assembly line balancing problem. An example is used to validate this hypothesis. The example is then further developed to demonstrate how the methodology can be used to obtain the optimal product portfolio. This approach is intended for use by manufacturers during the early design stages of product family design.
