A simulated annealing algorithm for multi-manned assembly line balancing problem

Assembly line balancing problems with multi-manned workstations usually occur in plants producing high volume products (e.g. automotive industry) in which the size of the product is reasonably large to utilize the multi-manned assembly line configuration. In these kinds of assembly lines, usually there are multi-manned workstations where a group of workers simultaneously performs different operations on the same individual product. However, owing to the high computational complexity, it is quite difficult to achieve an optimal solution to the balancing problem of multi-manned assembly lines with traditional optimization approaches. In this study, a simulated annealing heuristic is proposed for solving assembly line balancing problems with multi-manned workstations. The line efficiency, line length and the smoothness index are considered as the performance criteria. The proposed algorithm is illustrated with a numerical example problem, and its performance is tested on a set of test problems taken from literature. The performance of the proposed algorithm is compared to the existing approaches. Results show that the proposed algorithm performs well.     

Mixed model U-line balancing type-1 problem: A new approach

Avoiding work overload (imbalance) in mixed model U-line production systems entails an investigation into both balancing and sequencing problems at the same time and that is why some authors have considered both planning problems simultaneously. However because of the existing differences between planning horizons of balancing and sequencing problems (the former is a long to mid-term planning problem whereas the latter has a short term planning horizon) this simultaneous approach is only practical under very special conditions. It is also known that installation of an assembly line usually needs considerable capital investments and consequently it is necessary to design and balance such a system so that it works as efficiently as possible. To do so, in this paper, we develop a new approach to balance a mixed model U-shaped production system independent of what product sequences may be. This new approach is based on minimization of crossover workstations. Due to utilization of crossover workstations, balancing mixed model assembly lines in U-shaped line layouts is more complicated than that of straight lines. Some kind of issues including the ‘model mixes’ appearing in such workstations and the time taken for an operator to move from one side of the line to another increase the complexity of mixed model U-line balancing problems (MMULBP). Therefore it seems reasonable to develop a model in which minimizing the number of crossover workstations and maximizing the line efficiency are considered at the same time. Such a model is presented in this paper. In the proposed model, minimizing the variation of workload is also considered and taking into account operator's travel times, an extra time is assigned to workload of crossover workstations. Furthermore a genetic algorithm (GA) is proposed and a number of well-known test problems are solved by the GA and the related results are illustrated. Finally, the conclusion is presented.     

2-ANTBAL: An ant colony optimisation algorithm for balancing two-sided assembly lines

Two-sided assembly lines are a special type of assembly lines in which workers perform assembly tasks in both sides of the line. This type of lines is of crucial importance, especially in the assembly of large-sized products, like automobiles, buses or trucks, in which some tasks must be performed at a specific side of the product. This paper presents an approach to address the two-sided mixed-model assembly line balancing problem. First, a mathematical programming model is presented to formally describe the problem. Then, an ant colony optimisation algorithm is proposed to solve the problem. In the proposed procedure two ants ‘work’ simultaneously, one at each side of the line, to build a balancing solution which verifies the precedence, zoning, capacity, side and synchronism constraints of the assembly process. The main goal is to minimise the number of workstations of the line, but additional goals are also envisaged. The proposed procedure is illustrated with a numerical example and results of a computational experience that exhibit its superior performance are presented.     

A hybrid algorithm for allocating tasks,operators, and workstations in multi-manned assembly lines

In a car, there are approximately 30,000 parts produced by many different industries. This is due to the complexity and enormity of the automotive industry chain. The vehicle assembly process comprises welding, painting, prefabrication, and final entire-vehicle assembly. The assembly line has the largest labor force, which should be arranged and balanced to increase production efficiency and reduce labor force requirements. Unlike traditional studies on assembly line balancing problems (ALBPs), this study considers the characteristics of the automotive industry, such as multi-manned workstations, minimization in terms of the numbers of operators and workstations for streamlined production, budget constraints, the optimization of both task and operator allocation among workstations, and the determination of the start/end processing time of each task at different workstations. To address these NP-hard problems, a hybrid heuristic approach that combines the procedure of building feasible balancing solutions and the simulated annealing algorithm is proposed to map out an optimal line balancing plan for multi-manned workstations and to reduce the required workspace for shop operations. Based on the design and analysis of experiments, the effects of the maximum number of allowed operators per workstation and those of the cycle time on ALBP solutions are explored. The optimal combination of algorithm parameters is also determined. The results of this study can serve as a practical reference in planning the allocation of tasks, workstations, and operators in the industry.     

Multi-rule Multi-objective Simulated Annealing Algorithm for Straight and U Type Assembly Line Balancing Problems

The task of balancing of assembly lines is of considerable industrial importance. It consists of assigning operations to workstations in a production line in such a way that (1) no assembly precedence constraint is violated, (2) no workstations in the line takes longer than a predefined cycle time to perform all tasks assigned to it, and (3) as few workstations as possible are needed to perform all the tasks in the set. This paper presents a new multiple objective simulated annealing (SA) algorithm for simple (line) and U type assembly line balancing problems with the aim of maximizing “smoothness index” and maximizing the “line performance” (or minimizing the number of workstations). The proposed algorithm makes use of task assignment rules in constructing feasible solutions. The proposed algorithm is tested and compared with literature test problems. The proposed algorithm found the optimal solutions for each problem in short computational times. A detailed performance analysis of the selected task assignment rules is also given in the paper.     

Modeling and solving mixed-model assembly line balancing problem with setups. Part I: A mixed integer linear programming model

This paper is the first one of the two papers entitled “modeling and solving mixed-model assembly line balancing problem with setups”, which has the aim of developing the mathematical programming formulation of the problem and solving it with a hybrid meta-heuristic approach. In this current part, a mixed-integer linear mathematical programming (MILP) model for mixed-model assembly line balancing problem with setups is developed. The proposed MILP model considers some particular features of the real world problems such as parallel workstations, zoning constraints, and sequence dependent setup times between tasks, which is an actual framework in assembly line balancing problems. The main endeavor of Part-I is to formulate the sequence dependent setup times between tasks in type-I mixed-model assembly line balancing problem. The proposed model considers the setups between the tasks of the same model and the setups because of the model switches in any workstation. The capability of our MILP is tested through a set of computational experiments. Part-II tackles the problem with a multiple colony hybrid bees algorithm. A set of computational experiments is also carried out for the proposed approach in Part-II.     

A genetic algorithm based approach to the mixed-model assembly line balancing problem of type II

Mixed-model assembly lines allow for the simultaneous assembly of a set of similar models of a product, which may be launched in the assembly line in any order and mix. As current markets are characterized by a growing trend for higher product variability, mixed-model assembly lines are preferred over the traditional single-model assembly lines.

This paper presents a mathematical programming model and an iterative genetic algorithm-based procedure for the mixed-model assembly line balancing problem (MALBP) with parallel workstations, in which the goal is to maximise the production rate of the line for a pre-determined number of operators.

The addressed problem accounts for some relevant issues that reflect the operating conditions of real-world assembly lines, like zoning constraints and workload balancing and also allows the decision maker to control the generation of parallel workstations.     

Bacterial Foraging Optimization Algorithm for assembly line balancing

Assembly line balancing is the problem of assigning tasks to workstations by optimizing a performance measure while satisfying precedence relations between tasks and cycle time restrictions. Many exact, heuristic and metaheuristic approaches have been proposed for solving simple straight and U-shaped assembly line balancing problems. In this study, a relatively new optimization algorithm, Bacterial Foraging Optimization Algorithm (BFOA), based heuristic approach is proposed for solving simple straight and U-shaped assembly line balancing problems. The performance of the proposed algorithm is evaluated using a well-known data set taken from the literature in which the number of tasks varies between 7 and 111, and results are also compared with both an ant-colony-optimization-based heuristic approach and a genetic-algorithm-based heuristic approach. The proposed algorithm provided optimal solutions for 123 out of 128 (96.1 %) test problems in seconds and is proven to be promising.     

A multi-agent-based approach for personnel scheduling in assembly centers

This paper presents a multi-agent-based approach for personnel scheduling problems in the context of a paced multi-product assembly center. Our purpose is to elaborate daily assignment of employees to workstations in order to minimize simultaneously the operational costs and personnel dissatisfactions. The proposed approach considers the individual competencies, mobility and preferences of each employee, as well as the personnel and competency requirements associated with each assembly activity given both the current master assembly schedule and the line balancing for each product. To benchmark the performance of the multi-agent approach, we use optimal solutions obtained through a linear programming model resolution using a commercial solver. Experimental results show that our multi-agent approach can produce high-quality and efficient solutions in a short computational time.     

An agent-based algorithm for personnel shift-scheduling and rescheduling in flexible assembly lines

This article is about a multi-agent based algorithm for personnel scheduling and rescheduling in a dynamic environment of a paced multi-product assembly center. The purpose is first to elaborate daily employees?? assignment to workstations so as to minimize the operational costs as well as personnel dissatisfactions; the second is to generate an alternative planning when the first solution has to be rescheduled due to disturbances related to absenteeism. The proposed approach takes into account individual competencies, mobility and preferences of each employee, along with the competency requirements associated with each assembly activity, with respect to both the current master assembly schedule and the line balancing for each product. We use solutions obtained through a simulated annealing algorithm in order to benchmark the performance of the multi-agent approach. Experimental results show that our multi-agent approach can produce high-quality and efficient solutions in a short computational time.     

Modeling and solving assembly line design problems by considering human factors with a real‐life application

Ergonomics has been playing an important role in assembly system design (ASD) that contains not only the main assembly line balancing problem but also the subassembly line balancing and assembly layout problem. The ergonomics in ASD has an impact both on productivity and on workers’ health, especially when frequent changes in the product mix occur. In this study, we propose a systematic approach in order to handle ASD, which consists of three subproblems, while considering ergonomic risk factors. The first two subproblems are solved simultaneously using the proposed rule‐based constructive search algorithm, where ergonomic risks are evaluated by OCRA method. Later, layout problem is solved under transportation constraints using local search methods with various neighborhood structures. To provide the applicability and evaluate the performance of the proposed systematic approach, a real‐life case study in a harness manufacturing company is solved and prototype productions are performed.     

A hybrid genetic algorithm for mixed model assembly line balancing problem with parallel workstations and zoning constraints

In this paper, we propose a hybrid genetic algorithm to solve mixed model assembly line balancing problem of type I (MMALBP-I). There are three objectives to be achieved: to minimize the number of workstations, maximize the workload smoothness between workstations, and maximize the workload smoothness within workstations. The proposed approach is able to address some particular features of the problem such as parallel workstations and zoning constraints. The genetic algorithm may lack the capability of exploring the solution space effectively. We aim to improve its exploring capability by sequentially hybridizing the three well known heuristics, Kilbridge & Wester Heuristic, Phase-I of Moodie & Young Method, and Ranked Positional Weight Technique, with genetic algorithm. The proposed hybrid genetic algorithm is tested on 20 representatives MMALBP-I and the results are compared with those of other algorithms.     

Model and heuristics for the Assembly Line Worker Integration and Balancing Problem

We propose the Assembly Line Worker Integration and Balancing Problem (ALWIBP), a new assembly line balancing problem arising in lines with conventional and disabled workers. The goal of this problem is to maintain high productivity levels by minimizing the number of workstations needed to reach a given output, while integrating in the assembly line a number of disabled workers. Being able to efficiently manage a heterogeneous workforce is especially important in the current social context where companies are urged to integrate workers with different profiles. In this paper we present mathematical models and heuristic methodologies that can help assembly line managers to cope with this additional complexity. We demonstrate by means of a robust benchmark how this integration can be done with losses of productivity that are much lower than expected.     

Development and evaluation of a Basestock-CONWIP pull production control strategy in balanced assembly systems

In this study, a new pull production control strategy called Basestock-Constant Work-in-Process (B-CONWIP) is proposed. It is used to control the flow of materials and information in balanced assembly production systems. This proposed control strategy uses one type of authorization cards called CONWIP card that limits the work-in-process (WIP) in the whole system. It has been applied in a single-product and a mixed-product assembly system balanced by two efficient Genetic algorithms introduced in literature. The performance of this control strategy is compared with another pull production control strategy called Basestock Kanban CONWIP (BK-CONWIP), which is a very promising production control strategy found in literature. The proposed strategy has two control parameters, CONWIP authorization cards and basestock levels while BK-CONWIP has three control parameters Kanban authorization cards, CONWIP authorization cards and basestock levels. The comparison is based on three performance measures average system WIP, percentage of satisfied customer demand (service level) and WIP variation between workstations. The performance of the proposed strategy B-CONWIP and BK-CONWIP is mainly similar in both types of assembly systems when mean demand rates are low with respect to mean service rates with the proposed strategy being easier to control and optimize. On the other hand, when mean demand rates are high with respect to mean service rates; B-CONWIP is preferable if service level is more important, while BK-CONWIP is preferable if WIP level is more important. Regarding WIP variation, it mainly depends on the efficiency of the balancing approach. The more efficient the balancing approach, the less WIP variation. Treating demand as lost instead of backordered results in decreased average system WIP and does not affect service levels in both PCSs. It is also shown that S-KDP is more flexible in dealing with situations of variable product mixes than d-KDP because control parameters can be used by any product which minimizes the effect of the unbalanced systems.     

A Simulated Annealing algorithm for a mixed model assembly U-line balancing type-I problem considering human efficiency and Just-In-Time approach

This research deals with balancing a mixed-model U-line in a Just-In-Time (JIT) production system. The research intends to reduce the number of stations via balancing the workload and maximizing the weighted efficiency, which both are considered as the objectives of this research paper.After balancing the line and determining the number of stations, the labor assignment policy should be set. In this study, it was assumed that there are two types of operators: permanent and temporary. Both types can work in regular and overtime periods. Based on their skill levels, workers are classified into four types. The sign at each work station indicates types of workers allowed to work at that station. An alert system using the hybrid kanban systems was also considered. To solve this problem, a Simulated Annealing algorithm was applied in the following three stages. First, the balancing problem was solved and the number of stations was determined. Second, workers were assigned to the workstations in which they are qualified to work. Following that, an alert system based on the kanban system was designed to balance the work in the process inventory. This was achieved by defining control points based on the processing time and making control decisions to minimize the number of kanban cards. In the proposed SA algorithm, two methods for the temperature cooling schedule were considered and two methods were defined for determining the number of neighborhood search. The initial temperature was considered equal to the cost of the initial solution to reach the convergence situation as soon as possible. Five problems were solved in small size using the GAMS software. The results obtained from the GAMS software were compared with those obtained from the SA algorithm to determine the performance difference. The computational results demonstrated that the SA algorithm is more consistent with the answers obtained. Also seven large scale problems were solved. The results showed that the SA algorithm still have better reliability. To show the efficiency of the proposed SA algorithm, an axel assembly company was studied. To satisfy demands and reduce backlogging, a mixed model assembly line was designed for this case study. The results showed that the mixed model assembly line designed using the SA algorithm had good efficiency.     

A Lagrangian relaxation technique for the general assembly line balancing problem

This paper addresses the problem of balancing assembly or fabrication lines. In order to achieve a given production rate or to optimize the use of workstations, one has to tackle the problem of balancing the production lines. It is well known that this problem belongs to the class of NP-hard problems. In this paper the polyhedron of the feasible solutions of the assembly line balancing problem is first studied. Then a Lagrangian relaxation algorithm that incorporates the set of cycle constraints in the objective function is proposed. These constraints are the complicating restrictions in the model. The relaxed problem has the interesting property that its linear programming relaxation always has integer optimal solutions. The subgradient algorithm is then used to maximize the Lagrangian dual. A heuristic is also used to find primal feasible solutions for the original line balancing integer program. These two bounds are then used to reduce the size of the branch-and-bound tree.     

单一产品复杂装配线启发式平衡排产方法

提出了一种基于Excel的单一产品复杂装配线启发式平衡排产方法。给出了基于Excel的单一产品复杂装配线启发式平衡排产方法的总体技术方案;阐述了该方法中的五个关键技术,包括将装配优先图映射为工作表,工序后接数及阶位值计算,工序排序,装配线平衡,装配线排产;通过案例分析验证了该方法的有效性。     

Accumulated risk of body postures in assembly line balancing problem and modeling through a multi-criteria fuzzy-genetic algorithm

Monotonous body postures during repetitive jobs negatively affect assembly-line workers with the developing of Work-related Musculoskeletal Disorders (WMSDs). Ergonomics specialists have offered auxiliary posture diversity to deal with the lack of varieties, especially for high-risk ones. Meanwhile, Assembly Line Balancing (ALB) problem has been recognized as a prior thinking to (re)configure assembly lines via the balancing of their tasks among their workstations. Some conventional criteria, cycle time and overall workload are often considered during the balancing. This paper presents a novel model of ALB problem that incorporates assembly worker postures into the balancing. In addition to the conventional ALB criteria, a new criterion of posture diversity is defined and contributes to enhance the model. The proposed model suggests configurations of assembly lines via the balancing; so that the assigned workers encounter the opportunities of changing their body postures, regularly. To address uncertainties in the conventional criteria, a fuzzy goal programming is used, and an appropriate genetic algorithm is developed to deal with the model. Various computational tests are performed on the different models made with combinations of the three criteria mentioned above. Comparing the pay-offs among the combinations, results show that well balanced task allocation can be obtained through the proposed model.     

Designing an assembly line for modular products

To respond to the challenge of agile manufacturing, companies are striving to provide a large variety of products at low cost. Product modularity has become an important issue. It allows to produce different products through combination of standard components. One of the characteristics of modular products is that they share the same assembly structure for many assembly operations. The special structure of modular products provides challenges and opportunities for operational design of assembly lines. In this paper, an approach for design of assembly lines for modular products is proposed. This approach divides the assembly line into two subassembly lines: a subassembly line for basic assembly operations and a subassembly line for variant assembly operations. The design of the subassembly line for basic operations can be viewed as a single product assembly line balancing problem and be solved by existing line balancing methods. The subassembly line for the variant operations is designed as a two-station flowshop line and is balanced by a two-machine flowshop scheduling method. A three-station flowshop line for a special structure of modular products is proposed and illustrated with an example.