Work allocation strategies for serial assembly lines under high labour turnover

Labour turnover can be very detrimental to the performance of traditional serial assembly lines. It has been shown that high turnover rates can reduce annual production throughput in serial assembly lines by more than 16% when these lines operate under a balanced work allocation strategy. This paper investigates whether alternative production methods, such as Bucket Brigades, can out-perform traditional lines by utilizing dynamic work allocation and active operator replacement policies in order to absorb better the variability introduced by labour turnover. The study performed was divided into two phases. Phase I consisted of using a simple three-station linear assembly line to compare the performance of the Bucket Brigades method against a traditional line (fixed work allocation, static operator replacement), and a method using fixed work allocation along with a dynamic replacement policy. In Phase II, a six-station serial assembly line was used to compare the performance of Bucket Brigades against the traditional balanced line method. The analyses were based on simulation models that used monthly turnover rates of 0, 6 and 12%. Phase I showed that the Bucket Brigade method outperformed the other two methods consistently when operating under moderate (6%) and high (12%) turnover rates. Phase II demonstrated that the Bucket Brigade method was better than the traditional production method in every instance, including the case with 0% turnover.     

A factory-level dynamic operator allocation policy: the bubble allocation

In this paper, we propose a factory-level dynamic operator allocation policy called the bubble allocation policy. This policy is commonly implemented in labour-intensive industries in the presence of different operator speeds, high labour turnover, and learning effects. We prove the optimality of bubble allocation in several typical scenarios under deterministic and exponential processing time and different operator speed assumptions. When labour turnover and learning effects were considered, the effects of the bubble allocation were verified through simulation. Bubble allocation had a more significant positive effect on system throughput than the passive operator allocation policy. The positive effects of bubble allocation are enhanced with a larger production system scale (more parallel lines and more stations), higher turnover rate and slower learning process. Compared with active allocation policies such as work-sharing policy, bubble allocation policy has no requirements for additional cross-training and is not sensitive to the switching time of tasks. The bubble allocation policy stands out when the system is large and the flow line is designed in a balanced way.     

Sustainable operator assignment in an assembly line using genetic algorithm

This paper addresses the operator assignment in predefined workstations of an assembly line to get a sustainable result of fitness function of cycle time, total idle time and output where genetic algorithm is used as a solving tool. A proper operator assignment is important to get a sustainable balanced line. To improve the efficiency and meet the desired target output within the time limit, a balanced assembly line is a must. Real world lines consist of a large number of tasks and it is very time consuming and crucial to choose the most suitable operator for a particular workstation. In addition, it is very important to assign the suitable operator at the right place as his skill of operating machines finally reflects in productivity or in the cost of production. To verify better assignments of workers, a genetic algorithm is adopted here. A heuristic is proposed to find out the sustainable assignment of operators in the predefined workstations.     

Assembly line sequencing for model mix

This paper describes a model sequencing algorithm for model-mix assembly lines. A new formulation of the sequencing problem is proposed, the objective function of which is to minimize the overall assembly line-length for no operator interference. Lower bounds for the overall line-length are developed.

Two types of work station interfaces are considered; ‘closed’, where boundaries cannot be violated, and ‘open’ where defined boundaries do not exist—adjacent operators being allowed to enter each others apparent work areas without causing any interference.

A complete factorial experiment was made on five factors to determine their influence on the overall assembly line length. These are, the number of models, the model cycle time deviation, the production demand deviation for each model, the operator time deviation, and the number of stations in the assembly line. The main conclusions of this experiment are discussed and recommendations made for the selection of parameters used in the design of model-mix assembly lines.

Also discussed is an approach for accommodating small changes in production demand for existing assembly lines.     

Static and dynamic operator allocation problems in cellular manufacturing systems

This paper addresses the static and dynamic operator allocation problems in cellular manufacturing systems (CMS). An assembly environment is considered where each component going into the final product is manufactured in an individual cell. There are m such cells and it is required to manufacture n varieties of products where n > m . Algorithms for static and dynamic allocation of operators to the cells to balance workload and to minimize makespan are developed and tested.     

应用SIMOGRAMS方法解决装配生产线瓶颈

详细介绍了SIMOGRAMS,一种新的人机操作分析、联合操作分析的新方法.针对某轮胎公司现有生产能力无法满足市场需求的实际问题,首先确定瓶颈车间-成型车间,然后运用SIMOGRAMS工具,从该车间装配生产的主要产品装配流程入手,对整个装配过程进行联合操作分析,提出了初步改善方案并分析改善效果.最后将装配线从固定式布置改变为产品式布置,根据各基本工作单元所包含的工作量将其组合成工作量基本相等的工作包,并将这些工作包分派给每个操作者或工作站,形成基于几种产品的细胞单元,大幅度提高了手工装配线的生产能力和灵活性.     

Allocation of buffers to serial production lines with bottlenecks

The optimal placement of a predetermined amount of buffer capacity in balanced serial production lines is a well-understood problem: in lines with moderate variability, the optimal allocation involves equal numbers of buffers at each site; in lines with severe variability, the equal allocation is modified slightly to place more buffers toward the center of the line. Buffering unbalanced lines is a much less well-understood problem. We study the problem of buffering serial lines with moderate variability and a single bottleneck; i.e., a single station with a larger mean processing time than all other stations. Our analysis shows that a bottleneck station draws buffers toward it, but the optimal allocation depends on the location and severity of the bottleneck, as well as the number of buffers available. Furthermore, relatively large imbalances in mean processing times are required to shift the optimal buffer allocation away from an equal allocation. Finally, line length appears to have a relatively small effect on the optimal allocation with a given bottleneck. These results suggest that, at least for the class of lines studied here, equal buffer allocations may be optimal except in severely unbalanced lines. Furthermore, in severely unbalanced lines, throughput appears to be insensitive to the allocation of buffers.     

Minimising work overload in mixed-model assembly lines with different types of operators: a case study from the truck industry

This paper considers the problem of sequencing mixed-model assembly lines (MMALs). Our goal is to determine the sequence of products to minimise work overload. This problem is known as the MMAL sequencing problem with work overload minimisation: we explicitly use task operation times to find the product sequence. This paper is based on an industrial case study of a truck assembly line. In this industrial context, as a reaction to work overloads, operators at the workstations finish their tasks before the product reaches the next workstation, but at the expense of fatigue. Furthermore, there are different types of operators, each with different task responsibilities. The originality of this work is to model this new way of reacting against work overloads, to integrate three operator types in the sequencing model and to apply the developed methods in a real industrial context. To solve this problem, we propose three meta-heuristic procedures: genetic algorithm, simulated annealing and a combination of these two meta-heuristics. All the methods proposed are tested on industrial data and compared to the solutions obtained using a mixed-integer linear programme. The results show that the proposed methods considerably improve the results of the current procedure used in the case study.     

Stochastic two-sided U-type assembly line balancing: a genetic algorithm approach

In this paper, a novel stochastic two-sided U-type assembly line balancing (STUALB) procedure, an algorithm based on the genetic algorithm and a heuristic priority rule-based procedure to solve STUALB problem are proposed. With this new proposed assembly line design, all advantages of both two-sided assembly lines and U-type assembly lines are combined. Due to the variability of the real-life conditions, stochastic task times are also considered in the study. The proposed approach aims to minimise the number of positions (i.e. the U-type assembly line length) as the primary objective and to minimise the number of stations (i.e. the number of operators) as a secondary objective for a given cycle time. An example problem is solved to illustrate the proposed approach. In order to evaluate the efficiency of the proposed algorithm, test problems taken from the literature are used. The experimental results show that the proposed approach performs well.     

Dynamic operator assignment based on shifting machine loading

This study proposes a way to improve the efficiency of semiconductor wafer fabrications by better allocating operator resources. A semiconductor wafer fabrication facility produces multiple products using unreliable machines, and each product follows a different route. Random machine failures and demand fluctuations make machine loading change from time to time. Thus, the operator assignment needs adjustment accordingly to maintain a high factory throughput rate. We propose methods to make this dynamic adjustment. By using simulation models, we demonstrate that proportionally allocating operators among all work stations based on their utilization requirements can improve overall factory efficiency. We also show that frequent short term dynamic allocation of operators produces more output than conventional long term static allocation.     

Increasing the production rate of a just-in-time production system with variable operation times

This paper examines a just-in-time (JIT) system with kanbans with three subassembly lines feeding a final assembly station. Variability in operation times exists and variability effects are reduced by increasing work in process levels or by unbalancing the subassembly lines through assignment of work content at each station. Of the several unbalancing methods that were analysed in this study, only the high-medium-low showed a consistent improvement in the output rate of the JIT production system. The output rates with unbalanced stations were always superior to the output rate of the perfectly balanced configurations used as controls. The extent of improvement over the output rate of balanced systems increased directly with the variability in operation times in final assembly and subassembly stations and inversely with the interstage buffer capacity allowed in the system.     

Modelling and solving a cost-oriented resource-constrained multi-model assembly line balancing problem

A line balancing problem considers the assignment of operations to workstations in an assembly line. While assembly lines are usually associated to mass production of standardised goods, their advantages have led to their widespread use whenever a product-oriented production system is applicable and the benefits of the labour division and specialisation are significant, even when some of its characteristics may deviate from classical assembly lines. In this work, we study a line balancing problem found in the textile industry in which the line must be balanced for multiple types of goods taking into account resource requirements. In order to solve the problem, a hybrid method that combines classical methods for line balancing with an Estimation of Distribution Algorithm is proposed. Computational experiments show that the new procedure improves upon the state of the art when compared using a benchmark set derived from the literature, as well as when compared using data from the manufacturer that originated this research work.     

Worker allocation in lean U-shaped production lines

U-shaped lines are widely used in lean systems. In U-shaped production lines, each worker handles one or more machines on the line: the worker allocation problem is to establish which machines are handled by which worker. This differs from the widely-investigated U-line assembly line balancing problem in that the assignment of tasks to line locations is fixed. This paper address the worker allocation problem for lean U-shaped production lines where the objectives are to minimize the quantity of workers and maximize full work: such allocations provide the opportunity to eliminate the least-utilized worker by improving processes accordingly. A mathematical model is developed: the model allows for any allocation of machines to workers so long as workers do not cross paths. Walking times are considered, where workers follow circular paths and walk around other worker(s) on the line if necessary. A heuristic algorithm for tackling the problem is developed, along with a procedure representing the ‘traditional’ approach of constructing standard operations routines. Computational experiments considering three line sizes (up to 20 machines) and three takt time levels are performed. The results show that the proposed algorithm both improves upon the traditional approach and is more likely to provide optimal solutions.     

TECHNICAL NOTE: Dynamic Manning of Long Cycle Assembly Lines With Learning Effect

This paper presents a model to design assembly lines which require long cycle times and complete relatively few products. Work-force requirements in such lines are dynamic in nature, since due to learning, worker's performance time is a decreasing function of the number of units already being assembled.

Instead of balancing the cycle time at all stages, the model permits the cycle time to decrease in time. An iterative linear programming approach is used to minimize total cost, including labor cost, hiring and lay off by varying the cycle time of the line.     

Integrating human factors into discrete event simulation: a proactive approach to simultaneously design for system performance and employees’ well being

The aim of this research is to: (1) Develop an approach to integrating both human fatigue-recovery patterns and human learning into Discrete Event Simulation models of a production system to predict productivity and quality; (2) Validate the predicted fatigue against operators’ perceived fatigue; and (3) Demonstrate how this Human Factors-enabled simulation approach can be applied in a case study comparing two manufacturing line designs in the context of electronics assembly. The new approach can predict the accumulation of operator fatigue, fatigue-related quality effects and productivity changes based on system design configurations. In the demonstration comparison, fatigue dosage was 7–33% lower in the proposed system where HF was taken into consideration at the engineering design (ED) stage. In the existing system, the fatigue dose measure correlated with quality deficits with 26% of the variance accounted for – a large portion given the multi-causal nature of production deficits. ED models that do not include human aspects may provide unreliable results in terms of productivity and quality estimates. This research shows that it is possible to design production systems that are more productive while being less hazardous for the system operator.     

A stochastic network simulation model for production line systems†

This paper presents an application of a new network-based simulation model to a class of production line systems and compares this with a closed form procedure. The new model is capable of analysing more realistic production lines by allowing variable work element times (normal and others), parallel stations, in-process inventory, and merging subassembly lines. Furthermore, the model is capable of handling mixed model and batched assembly situations as well as the single product assembly lines. The inclusion of cost and resource options, as integral components makes the model a powerful tool of analysis. The cost option allows evaluation of alternative configurations based on the total cost of the system; whereas, the resource feature enables one to analyse the constrained resource situations. The model can be used to optimize the design of new processing lines and to balance existing lines with a fixed production requirement.     

Robotic U-shaped assembly line balancing using particle swarm optimization

Automation in an assembly line can be achieved using robots. In robotic U-shaped assembly line balancing (RUALB), robots are assigned to workstations to perform the assembly tasks on a U-shaped assembly line. The robots are expected to perform multiple tasks, because of their capabilities. U-shaped assembly line problems are derived from traditional assembly line problems and are relatively new. Tasks are assigned to the workstations when either all of their predecessors or all of their successors have already been assigned to workstations. The objective function considered in this article is to maximize the cycle time of the assembly line, which in turn helps to maximize the production rate of the assembly line. RUALB aims at the optimal assignment of tasks to the workstations and selection of the best fit robot to the workstations in a manner such that the cycle time is minimized. To solve this problem, a particle swarm optimization algorithm embedded with a heuristic allocation (consecutive) procedure is proposed. The consecutive heuristic is used to allocate the tasks to the workstation and to assign a best fit robot to that workstation. The proposed algorithm is evaluated using a wide variety of data sets. The results indicate that robotic U-shaped assembly lines perform better than robotic straight assembly lines in terms of cycle time.     

PACING EFFECTS ON MANNED ASSEMBLY LINES

A computer simulation of an assembly line enforcing pacing on manned sequential stations indicates that unpaced station operations are superior to paced. Using the variability and work-time distribution of operator performance on repetitive tasks, a number of studies were carried out which show that an assembly line cannot perform at maximum efficiency (in terms of operator idle time and units completed) unless queues are provided before each work station. Studies of various station speed configurations indicate that the generally preferred configuration is Fast-Medium-Slow (short-medium-long cycle time) and that there is little difference among various configurations when the inter-arrival time is larger than any of the operator mean cycle times.     

Balancing flexible lines for car components assembly

The design and balancing of a line which assembles car heaters is examined. To accomplish a balance, the general assembly line balancing model is extended to cope with some restrictions due to the physical structure of the production line: namely, incompatibilities among operations and operations that must be necessarily performed by certain work stations. A polynomial time dynamic programming algorithm is provided to balance the workloads among the work stations taking into account these additional constraints, exploiting the special structure of the operation graph. The algorithm was applied to two designs: a single line on which all the heater components are assembled, and also to several segmented lines, which collectively assemble heaters. Demand volume variations are also addressed.