Workers’ rest allowance and smoothing of the workload in assembly lines

Ergonomic aspects have a crucial role in manual assembly systems. They impact on the workers’ health, final product quality and productivity. For these reasons, there is the necessity to integrate them into the assembly line balancing phase as, whereas, only time and cost variables are considered. In this study, human energy expenditures are considered as ergonomic aspects and we integrate them, for the first time, into the assembly line balancing problem type 2 through the rest allowance evaluation. We consider as an objective function the minimization of the smoothness index. Firstly, a new optimal method based on mixed integer linear programming and a new linearization methodology are proposed. Then, a heuristic approach is introduced. To complete the study, a computational experimentation is presented to validate the mathematical model and to compare the methodologies proposed in terms of computational time, complexity and solution. Additionally, we provide a detailed analysis of the impact that rest allowance evaluation can have on productivity comparing the results obtained, taking into account the rest allowance integration before, during and after the assembly balancing process.     

Balancing mixed-model assembly lines: a computational evaluation of objectives to smoothen workload

Mixed-model assembly lines are widely used in a range of production settings, such as the final assembly of the automotive and electronics industries, where they are applied to mass-produce standardised commodities. One of the greatest challenges when installing and reconfiguring these lines is the vast product variety modern mixed-model assembly lines have to cope with. Traditionally, product variety is bypassed during mid-term assembly line balancing by applying a joint precedence graph, which represents an (artificial) average model and serves as the input data for a single model assembly line balancing procedure. However, this procedure might lead to considerable variations in the station times, so that serious sequencing problems emerge and work overload threatens. To avoid these difficulties, different extensions of assembly line balancing for workload smoothing, i.e. horizontal balancing, have been introduced in the literature. This paper presents a multitude of known and yet unknown objectives for workload smoothing and systematically tests these measures in a comprehensive computational study. The results suggest that workload smoothing is an essential task in mixed-model assembly lines and that some (of the newly introduced) objectives are superior to others.     

Cost minimization and workload balancing in printed circuit board assembly

We consider an operation assignment problem arising from a Printed Circuit (PC) board assembly process. The research was inspired by applications at Hewlett-Packard Company where hundreds of types of PC boards require the insertion of thousands of types of components. The components can be inserted manually or by automated insertion machines. The machines can only hold a limited number of different component types. We investigate how to assign the boards and components to the machines and manual process so as to minimize cost while at the same time balancing machine workloads. We first present a Binary Integer Program (BIP) formulation of the problem. We then develop optimality results that allow us to reduce significantly the size of the BIP. Using the improved BIP formulation, and upper bounds generated using a Cost Minimizing Workload Balancing (CMWB) heuristic that we develop, we show how branch-and-bound can be used to find optimal solutions to small and medium-sized problems in reasonable time. We also show that the CMWB heuristic finds solutions in seconds of CPU time that are within a few percent of optimal. In addition, the CMWB heuristic outperforms the heuristic that has been used at Hewlett-Packard, as well as the longest expected processing time heuristic. Although this paper specifically addresses a problem of partially-automated PC board assembly, the results apply to a more general set of problems, including job and tool assignment in flexible manufacturing systems, and general operation assignment problems.     

Optimization of the assignment of circuit cards to assembly lines in electronics assembly

Process planning is an important and integral function for ensuring efficient operations in printed circuit card assembly systems. This paper presents a new approach for solving the circuit card to assembly line assignment problem to minimize assembly time. This problem occurs frequently in process planning for electronic assembly systems and involves considering other interelated process planning problems. The line assignment problem is formulated as a large-scale mixed-integer programming problem and then solved using problem decomposition along with the branch-and-bound algorithm. Techniques for improving the solution time are discussed, and the solution approach is demonstrated using industry representative data sets from Lucent Technologies. For the data sets considered, the solution approach provides solutions within 3% of optimal in approximately 6 min of computation time on a Sun UltraSparc 2 Workstation. The solution approach developed for addressing the line assignment problem can serve as a useful decision-support tool by offering significant opportunities to improve the productivity and throughput of the assembly lines with improved process plans. The approach also allows planning engineers to respond faster to changes in production requirements. This research will be of interest to researchers in printed circuit card assembly systems and to practitioners in both original equipment manufacturing and contract assembly firms.     

Component allocation to balance workload in printed circuit card assembly systems

Component allocation in printed circuit card assembly systems is a special case of the classical mixed-model assembly line balancing problem and involves assigning component types to machines to achieve specific production objectives. In this paper the component allocation problem is considered for the scenario where there are two or more placement machines (possibly nonidentical) and the objective is to balance, for every card type, a combination of the card assembly time and the machine setup time. A mathematical formulation of the problem is developed for a class of placement machines. Two alternative solution approaches are presented: a list-processing-based heuristic for a simple version of the problem, and a linear-programming-based branch-and-bound procedure for the general component allocation problem. Industrial case study results are presented for each approach that indicate expected throughput improvements of up to 8-10% over the company's current procedure, with much less direct effort required by the process engineer.     

Balancing parallel two-sided assembly lines

Two-sided assembly lines are usually designed to produce large-sized products such as automobiles, trucks and buses. In this type of production line, both left-side and right-side of the line are used. In parallel assembly lines, one or more product types are produced on two or more assembly lines located in parallel to each other. Both production lines have several serious practical advantages. For this purpose, in this paper, two or more two-sided assembly lines located in parallel to each other are considered and a tabu search algorithm which combines the advantages of both types of production lines is developed. To assess the effectiveness of the proposed algorithm, a set of test problems are solved. The proposed algorithm is illustrated with two examples, and some computational properties of the algorithm are given.     

Balancing stochastic two-sided assembly lines

In a two-sided assembly line, tasks can be executed simultaneously on both sides of the line. One task cannot be started until both of its direct predecessors on the left and right sides are completed. Therefore, the start time of the task is the maximum of the two predecessors’ finish times. In many realistic situations, it is assumed that the task times are independent and normally distributed with known means and variances. However, the maximum of two normal variables is not normally distributed, but can be well approximated by results from extreme value theory. In this paper, we utilise these results to develop a solution methodology to balance two-sided assembly lines with stochastic task times, minimising the line length and the number of stations while guaranteeing all tasks are completed within the cycle time with a given confidence level.     

Flow control of two-level assembly lines

The paper addresses the flow control problem in two-level assembly production lines composed of a unique assembly machine and multiple upper level machines. In order to obtain a finished product, the assembly machine needs components produced by different upper level machines. We assume that the production capacity of each machine is constant and the demand is known over the whole problem horizon. Backlogging is not allowed. The flow control problem consists of adjusting the production of the machines in order to minimize the total cost incurred by holding components and finished products. Properties of the optima) solutions are given. Based on these properties, we propose a simple analytical solution.     

Improving the applicability of workload control (WLC): the influence of sequence-dependent set-up times on workload controlled job shops

Simulation has demonstrated that the workload control (WLC) concept can improve performance in job shops, but positive empirical results are scarce. A key reason for this is that the concept has not been developed to handle a number of practical considerations, including sequence-dependent set-up times. This paper investigates the influence of sequence-dependent set-up times on the performance of a workload-controlled job shop. It introduces new set-up-oriented dispatching rules and assesses the performance impact of controlled order release. Simulation results demonstrate that combining an effective WLC order release rule with an appropriate dispatching rule improves performance over use of a dispatching rule in isolation when set-up times are sequence dependent. The findings improve our understanding of how this key implementation challenge can be overcome. Future research should investigate whether the results hold if set-up time parameters are dynamic and set-up times are not evenly distributed across resources.     

Rebalancing the assembly lines: exact solution approaches

In this study, we consider an assembly line rebalancing problem with disruptions caused by workstation breakdowns or shutdowns. After the disruption, we aim to find a rebalance so as to catch the trade-off between the efficiency measure of cycle time and stability measure of number of tasks assigned to different workstations in the original and new balances. Our aim is to generate all nondominated objective vectors with respect to the efficiency and stability measures. We develop two optimisation algorithms: a Mixed Integer Linear Programming-based algorithm and a Branch and Bound algorithm. The results of our experiments have shown the favourable performances of both algorithms and the superiority of the Branch and Bound algorithm.     

Dynamic resequencing at mixed-model assembly lines

In this paper, we investigate a dynamic resequencing problem covering realistic properties of a mixed-model assembly line. To this end, we present a mathematical model that addresses dynamically supplied blocking information and viable due dates. We developed two different strategies that use a static resequencing algorithm as a subroutine. One strategy integrates each unblocked order immediately into the planned sequence, whereas the other strategy waits for good positions that do not conflict with the due dates. All algorithms construct guaranteed feasible sequences. Using industrial test data, we show that both strategies perform significantly better than a simple method derived from practice. A replanning procedure that tries to improve the current planned sequence whenever computing time suffices yields an additional improvement for both strategies.     

Improving electromigration reliability in Al-alloy lines

We present a method that utilizes surface topography to control the distribution of grain sizes, single grain segment lengths and polygrain cluster lengths in Al---Cu thin films. Microstructural data for the grain size and segment/cluster length distribution parameters are presented that demonstrate the influence of various topographical features adjacent to conductor lines. Experimental results show the impact of these features on electromigration failure times. Our results demonstrate that the relationship between median failure time and segment length is consistent with the critical threshold length concept for long interconnects containing large numbers of single grain segments and polygrain clusters. These results demonstrate the importance of the segment length and type in controlling electromigration mass transport.     

The application of workload control in assembly job shops: an assessment by simulation

Workload control (WLC) is a production planning and control concept developed to meet the needs of small- and medium-sized make-to-order companies, where a job shop configuration is common. Although simulation has shown WLC can improve job shop performance, field researchers have encountered significant implementation challenges. One of the most notable challenges is the presence of ‘assembly job shops’ where product structures are more complex than typically modelled in simulation and where the final product consists of several sub-assemblies (or work orders) which have to be co-ordinated. WLC theory has not been developed sufficiently to handle such contexts, and the available literature on assembly job shops is limited. In response, this paper extends the applicability of WLC to assembly job shops by determining the best combination of: (i) WLC due date (DD) setting policy, (ii) release method and (iii) policy for coordinating the progress of work orders. When DDs are predominantly set by the company, the DD setting policy should play the leading role while the role of order release should be limited and the progress of work orders should not be co-ordinated in accordance with the DD of the final product. But when DDs are predominantly specified by customers, the importance of order release as a second workload balancing mechanism increases and work orders should be coordinated by backward scheduling from the DD of the final product. Results indicate that WLC can improve performance in assembly job shops and outperform alternative control policies. Future research should implement these findings in practice.     

Order-oriented cooperative sequencing optimisation in multi-mix-model assembly lines

Order-oriented products assembly sequence among different assembly lines becomes a critical problem for mass customisation manufacturing systems. It significantly affects system productivity, delivery time, and manufacturing cost. In this paper, we propose a new approach to extend the traditional products sequencing from mixed model assembly line (MMAL) to multi-mixed model assembly lines (MMMALs) to obtain the optimal assembly sequence with the objectives of minimising consumption waviness of each material in the lines, assembly line setup cost, and lead-time. A multi-objective optimisation algorithm based on variable neighbourhood search methods (VNS) is developed. We perform an industrial case study in order to demonstrate the practicality and effectiveness of the proposed approach.     

Scheduling learning dependent jobs in customised assembly lines

The large variety of product models required by customised markets implies lot size reduction. This strongly affects manual-based production activities, since workers need to promptly adapt to the specifications of the next model to be produced. Completion times of manual-based activities tend to be highly variable among workers, and are difficult to estimate. This affects the scheduling of those activities since scheduling precision depends on reliable estimates of job completion times. This paper presents a method that combines learning curves and job scheduling heuristics aimed at minimising the total weighted earliness and tardiness. Workers performance data is collected and modelled using learning curves, enabling a better estimation of the completion time of jobs with different size and complexity. Estimated completion times are then inputted in new scheduling heuristics for unrelated parallel workers, equivalent to machines in this study, created by modifying heuristics available in the literature. Performance of the proposed heuristics is assessed analysing the difference between the optimal schedule objective function value and that obtained using the heuristics, as well as the workload imbalance among workers. Some contributions in this paper are: (i) use of learning curves to estimate completion times of jobs with different sizes and complexities from different teams of workers; and (ii) use of a more complex scheduling objective function, namely the total weighted earliness and tardiness, as opposed to most of the developments in the current scheduling literature. A shoe manufacturing application illustrates the developments in the paper.     

A multi-decision genetic approach for workload balancing of mixed-model U-shaped assembly line systems

A mixed-model assembly line is a type of production line where a variety of product models similar in product characteristics are produced. As a consequence of introducing the just-in-time (JIT) production principle, it has been recognised that a U-shaped assembly line system offers several benefits over the traditional straight line system. This paper proposes a new evolutionary approach to deal with workload balancing problems in mixed-model U-shaped lines. The proposed method is based on the multi-decision of an amelioration structure to improve a variation of the workload. This paper considers both the traditional straight line system and the U-shaped assembly line, and is thus an unbiased examination of line efficiency. The performance criteria considered are the number of workstations (the line efficiency) and the variation of workload, simultaneously. The results of experiments enhanced the decision process during multi-model assembly line system production; thus, it is therefore suitable for the augmentation of line efficiency in workstation integration and simultaneously enhancement of the variation of the workload. A case study is examined as a validity check in collaboration with a manufacturing company.     

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.     

Bicriteria sequencing for just-in-time mixed-model assembly lines

Under a Just-In-Time (JIT) pull system the sequencing of products requires the satisfaction of two main goals: (1) keeping a constant rate of usage of parts, and (2) smoothing the workload at work stations to avoid line stoppages. By using a practical observation related to JIT delivery systems we propose a two-step approach, where in the first step we consider only goal (1) by applying a benchmark heuristic. In the second step we focus on goal (2), by investigating the effectiveness of a spacing-constraint based approach, commonly used in the automotive industry, in comparison with a more general time-based one. We designed and conducted a simulation experiment based on the practical situation of final assembly lines and we found that the benchmark heuristic represents an appropriate choice for step one (based on a new performance measure that represents a lower bound on variation in parts utilization). For the second step, related to workload smoothing, the spacing-constraint based method presents better achievement than the time-based one.     

Balancing and sequencing of parallel mixed-model assembly lines

In this paper, a simulated annealing approach is developed for the parallel mixed-model assembly line balancing and model sequencing (PMMAL/BS) problem which is an extension of the parallel assembly line balancing (PALB) problem introduced by Gökçen et al. (2006 Gökçen, H and A?pak, K. 2006. A goal programming approach to simple U-line balancing problem. European Journal of Operational Research, 171(2): 577–585. [Crossref], [Web of Science ®] , [Google Scholar]). In PALB, the aim is to balance more than one assembly line together. Balancing of the lines simultaneously with a common resource is very important in terms of resource minimisation. The proposed approach maximises the line efficiency and distributes the workloads smoothly across stations. The proposed approach is illustrated with two numerical examples and its performance is tested on a set of test problems. The computational results show that the proposed approach is very effective for PMMAL/BS.     

Variability modelling and balancing of stochastic assembly lines

In a production flow line with stochastic environment, variability affects the system performance. These stochastic nature of real-world processes have been classified in three types: arrival, service and departure process variability. So far, only service process – or task time – variation has been considered in assembly line (AL) balancing studies. In this study, both service and flow process variations are modelled along with AL balancing problem. The best task assignment to stations is sought to achieve the maximal production. A novel approach which consists of queueing networks and constraint programming (CP) has been developed. Initially, the theoretical base for the usage of queueing models in the evaluation of AL performance has been established. In this context, a diffusion approximation is utilised to evaluate the performance of the line and to model the variability relations between the work stations. Subsequently, CP approach is employed to obtain the optimal task assignments to the stations. To assess the effectiveness of the proposed procedure, the results are compared to simulation. Results show that, the procedure is an effective solution method to measure the performance of stochastic ALs and achieve the optimal balance.