Document Type : Research Paper

Author

• fahimeh tanhaie

Assistant Professor, Industrial Engineering Department, Faculty of basic science and Engineering, Kosar university of Bojnord

Abstract

The mix model assembly line has attracted the attention of many industrial manufacturers due to its special features and the ability to adapt to market changes. This article has discussed and investigated a new approach in relation with customers, the results of which indicate the proper management of demand. The proposed model pays more attention to priority customers, and a parallel production line is defined that is faster than the main line and has workers with special skills. According to the rapid process of environmental changes, one of the things that can be considered to increase flexibility in the make to order environment is to set the conditions for rebalancing the line. In this article, the rebalancing of the line is also considered and included in the modeling, and the minimization of its costs is considered as another goal. Therefore, in this article, a multi-objective line balancing problem is proposed by examining rebalancing and vertical balancing problems. Benders decomposition algorithm is used to solve this problem. The results show that exact methods do not have the ability to solve large-sized problems in a reasonable time, but the solution time for Bander's decomposition method, considering the size of the problem, shows the appropriate efficiency of this algorithm
Introduction
Mix model assembly lines, known for their ability to adapt to changing market demands with minimal adjustments, are currently employed in active industries worldwide. The findings of this article also hold potential for reducing assembly line waste in the country's manufacturing sector. Drawing from the principles of lean production and the theories of Scholl and Becker, achieving an optimal production line balance can lead to the reduction of at least five out of the ten types of waste. While the topic of line balancing is crucial in itself, this research sheds light on a significant aspect often overlooked in most studies on planning mixed model assembly lines: the order-based environment. Many previous studies have focused solely on the 'make-to-order' environment and its assumptions, often neglecting balance issues. Given the paramount importance of customer roles in industries, it is imperative to introduce a framework for managing customer orders within line balancing problem models. The aim of this article is to enhance cost management and productivity in mixed assembly lines across various industries, ensuring that demands are met and assembly process constraints are addressed. To achieve this, we first develop the necessary mathematical models for each component and subsequently devise algorithms for their solutions.
Materials and Methods
An express line is defined in parallel and faster than the main line, as well as having workers with special skills. Considering the rapid process of environmental changes, another thing that can be considered to increase flexibility in the base order environment is to create conditions for rebalancing the line so that both the workload and the cost can be balanced at the same time. This reduced the reassignment of duties. From this point of view, in the proposed model in this part, rebalancing of the line is also desired and it is included in the modeling, and the minimization of its costs is considered as another goal of this model. Also, the goal of balancing the assembly line, which is to distribute the total workload between the stations as smoothly as possible, is also included in the proposed model of this part, which is also called vertical balance, so that each station has a balanced amount of work. Be in a work shift. Therefore, in this model, a multi-objective problem of determining the balance is designed by examining the problems of rebalancing and vertical balance. The orders coming into the organization are prioritized first, because in the order-based production environment, the delivery time of orders is very important, especially for high-priority orders, because customers expect an appropriate response in a short period of time. This prioritization can be done by any method, the output of which determines regular customers and priority customers. After determining the priority of the orders and paying attention to the main line and the designated vanguard, priority orders can be entered into the Parallel line, which operates faster and has multi-purpose operators.
Discussion and Results
In order to validate the model and ensure the correct performance of the combined benders algorithm with the LP metric method, first the mathematical model in a small size is solved and a comparison between the results and the proposed algorithm is done. Finally we used the proposed algorithm in the large size that the gams software is not able to determine the answer. The L-P metric method obtains the optimal solution in small sizes, but in large sizes, when we give 3600 to 10800 seconds to the solver, it cannot obtain the optimal solution and requires another method to solve. The results of the comparisons show that the LP-metric method does not have the ability to solve large-sized problems in a reasonable time, but the solution time for the benders decomposition method, considering the size of the problem and the obtained answers, shows the appropriate efficiency of this algorithm.
Conclusions
Flexibility in the production lines is very important and it should be able to respond to the demand when customer orders change. Therefore, the definition of a mix model line provides flexibility in responding to customer demand and reducing the delivery time for priority orders. When we are faced with a large volume of orders, it can be useful to do things in parallel line. This issue, which is rarely seen in research, is presented in the balance model of this article in the form of two parallel lines. This issue is especially effective in industries such as automobile manufacturing.

Keywords

• Mix model Assembly lines
• make to order environment
• line balancing
• parallel production lines

Main Subjects

• production and operations management