A mathematical model and artificial bee colony algorithm for the lexicographic bottleneck mixed-model assembly line balancing problem

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Typically, the total number of required workstations are minimised for a given cycle time (this problem is referred to as type-1), or cycle time is minimised for a given number of workstations (this problem is referred to as type-2) in traditional balancing of assembly lines. However, variation in workload distributions of workstations is an important indicator of the quality of the obtained line balance. This needs to be taken into account to improve the reliability of an assembly line against unforeseeable circumstances, such as breakdowns or other failures. For this aim, a new problem, called lexicographic bottleneck mixed-model assembly line balancing problem (LB-MALBP), is presented and formalised. The lexicographic bottleneck objective, which was recently proposed for the simple single-model assembly line system in the literature, is considered for a mixed-model assembly line system. The mathematical model of the LB-MALBP is developed for the first time in the literature and coded in GAMS solver, and optimal solutions are presented for some small scale test problems available in the literature. As it is not possible to get optimal solutions for the large-scale instances, an artificial bee colony algorithm is also implemented for the solution of the LB-MALBP. The solution procedures of the algorithm are explored illustratively. The performance of the algorithm is also assessed using derived well-known test problems in this domain and promising results are observed in reasonable CPU times

Research Article Balancing the Production Line by the Simulation and Statistics Techniques: A Case Study

Abstract: A wide range of the real world problems in industries are related to misbalances of the production line and excessive Work in Process parts (WIP). Simulation is an effective method to recognize these problems with consuming least cost and time. Moreover, total system efficiency of a production line can be extremely improved by examining different solution scenario via the simulation techniques. In this research, we utilize the simulation technique founded upon the software Enterprise Dynamics (ED) for evaluating the cause of these problems and trying to find the improvement solutions in Sadid Pipe and Equipment Company (SPECO). Two parameters of diameter and thickness are important factors affecting the time of workstations. The effects of these factors on process time are evaluated by hypothesis tests. Two improvement scenarios have been presented. In the first scenario, the layout design of the factory has been improved with regard to production process and bottleneck station. In the second one, an essential improvement has been carried out by reduction in wastages. Regarding the accomplished simulations, it is concluded that it is possible to eliminate the existing bottleneck by implementing changes in the locations of production stations or reducing the waste in some stations. The improvements eventually result in balancing the production line

Customer demand management in the optimal assignment of tasks to work stations according to priority orders

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 algorithmIntroductionMix 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 MethodsAn 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 ResultsIn 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.ConclusionsFlexibility 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

Mixed-model parallel two-sided assembly line balancing problem: A flexible agent-based ant colony optimization approach

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Assembly lines are frequently used as a production method to assemble complex products. Two-sided assembly lines are utilized to assemble large-sized products (e.g., cars, buses, trucks). Locating two lines in parallel helps improve line efficiency by enabling collaboration between the line workers. This paper proposes a mixed-model parallel two-sided assembly line system that can be utilized to produce large-sized items in an inter-mixed sequence. The mixed-model parallel two-sided line balancing problem is defined and the advantages of utilizing multi-line stations across the lines are discussed. A flexible agent-based ant colony optimization algorithm is developed to solve the problem and a numerical example is given to explain the method systematically. The proposed algorithm builds flexible balancing solutions suitable for any model sequence launched. The dynamically changing workloads of workstations (based on specific product models during the production process) are also explored. A comprehensive experimental study is conducted and the results are statistically analyzed using the well-known paired sample t-test. The test results indicate that the mixed-model parallel two-sided assembly line system reduces the workforce need in comparison with separately balanced mixed-model two-sided lines. It is also shown that the proposed algorithm outperforms the tabu search algorithm and six heuristics often used in the assembly line balancing domain

Modelling and Solving Mixed-model Parallel Two-sided Assembly Line Problems

The global competitive environment and the growing demand for personalised products have increased the interest of companies in producing similar product models on the same assembly line. Companies are forced to make significant structural changes to rapidly respond to diversified demands and convert their existing single-model lines into mixed-model lines in order to avoid unnecessary new line construction cost for each new product model. Mixed-model assembly lines play a key role in increasing productivity without compromising quality for manufacturing enterprises. The literature is extensive on assembling small-sized products in an intermixed sequence and assembling large-sized products in large volumes on single-model lines. However, a mixed-model parallel two-sided line system, where two or more similar products or similar models of a large-sized product are assembled on each of the parallel two-sided lines in an intermixed sequence, has not been of interest to academia so far. Moreover, taking model sequencing problem into consideration on a mixed-model parallel two-sided line system is a novel research topic in this domain. Within this context, the problem of simultaneous balancing and sequencing of mixed-model parallel two-sided lines is defined and described using illustrative examples for the first time in the literature. The mathematical model of the problem is also developed to exhibit the main characteristics of the problem and to explore the logic underlying the algorithms developed. The benefits of utilising multi-line stations between two adjacent lines are discussed and numerical examples are provided. An agent-based ant colony optimisation algorithm (called ABACO) is developed to obtain a generic solution that conforms to any model sequence and it is enhanced step-by-step to increase the quality of the solutions obtained. Then, the algorithm is modified with the integration of a model sequencing procedure (where the modified version is called ABACO/S) to balance lines by tracking the product model changes on each workstation in a complex production environment where each of the parallel lines may a have different cycle time. Finally, a genetic algorithm based model sequencing mechanism is integrated to the algorithm to increase the robustness of the obtained solutions. Computational tests are performed using test cases to observe the performances of the developed algorithms. Statistical tests are conducted through obtained results and test results establish that balancing mixed-model parallel two-sided lines together has a significant effect on the sought performance measures (a weighted summation of line length and the number of workstations) in comparison with balancing those lines separately. Another important finding of the research is that considering model sequencing problem along with the line balancing problem helps algorithm find better line balances with better performance measures. The results also indicate that the developed ABACO and ABACO/S algorithms outperform other test heuristics commonly used in the literature in solving various line balancing problems; and integrating a genetic algorithm based model sequencing mechanism into ABACO/S helps the algorithm find better solutions with less amount of computational effort