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Walking-worker assembly lines can be regarded as an effective method to achieve the above-mentioned characteristics. In such systems, workers, following each other, travel workstations in sequence by performing all of the required tasks of their own product. As the eventual stage of assembly line design, efforts should be made for capacity adjustments to meet the demand in terms of allocating tasks to workers via assembly line balancing. In this context, the purpose of this study is to address the balancing problem for multi-model walking-worker assembly systems, with the aim of improving planning capability for such systems by means of developing an optimization methodology.

Two linear integer programming models are proposed to balance a multi-model walking-worker assembly line optimally in a sequential manner. The first mathematical programming model attempts to determine number of workers in each segment (i.e. rabbit chase loop) for each model. The second model generates stations in each segment to smooth workflow. What is more, heuristic algorithms are provided due to computational burden of mathematical programming models. Two segment generation heuristic algorithms and a station generation heuristic algorithm are provided for the addressed problem.

The application of the mathematical programming approach improved the performance of a tap-off box assembly line in terms of number of workers (9.1 per cent) and non-value-added time ratio (between 27.9 and 26.1 per cent for different models) when compared to a classical assembly system design. In addition, the proposed approach (i.e. segmented walking-worker assembly line) provided a more convenient working environment (28.1 and 40.8 per cent shorter walking distance for different models) in contrast with the overall walking-worker assembly line. Meanwhile, segment generation heuristics yielded reduction in labour requirement for a considerable number (43.7 and 49.1 per cent) of test problems. Finally, gaps between the objective values and the lower bounds have been observed as 8.3 per cent (Segment Generation Heuristic 1) and 6.1 (Segment Generation Heuristic 2).

The proposed study presents a decision support for walking-worker line balancing with high level of solution quality and computational performance for even large-sized assembly systems. That being the case, it contributes to the management of real-life assembly systems in terms of labour planning and ergonomics. Owing to the fact that the methodology has the potential of reducing labour requirement, it will present the opportunity of utilizing freed-up capacity for new lines in the start-up period or other bottleneck processes. In addition, this study offers a working environment where skill of the workers can be improved within reasonable walking distances.

To the best knowledge of the author, workload balancing on multi-model walking-worker assembly lines with rabbit chase loop(s) has not yet been handled. Addressing this research gap, this paper presents a methodology including mathematical programming models and heuristic algorithms to solve the multi-model walking-worker assembly line balancing problem for the first time.

Rabbit chase (RC) is used as one of the most effective techniques in manufacturing systems, as such systems have high level of adaptability and increased productivity in addition to providing uniform workload balancing and skill improving environment. In assembly systems, RC inspires the development of walking worker assembly line (WWAL). On the other hand, U-type assembly lines (UALs) may provide higher worker utilization, lower space requirement and more convenient internal logistics when compared to straight assembly lines. In this context, this study aims to improve assembly line performance by generating RC cycles on WWAL with respect to task assignment characteristics of UAL within reasonable walking distance and space requirement. Therefore, a novel line configuration, namely, segmented rabbit chase-oriented U-type assembly line (SRCUAL), emerges.

The mathematical programming approach treats SRCUAL balancing problem in a hierarchical manner to decrease computational burden. Firstly, segments are generated via the first linear programming model in the solution approach for balancing SRCUALs to minimize total number of workers. Then, stations are determined within each segment for forward and backward sections separately using two different pre-emptive goal programming models. Moreover, three heuristics are developed to provide solution quality with computational efficiency.

The proposed mathematical programming approach is applied to the light-emitting diode (LED) luminaire assembly section of a manufacturing company. The adaptation of SRCUAL decreased the number of workers by 15.4% and the space requirement by 17.7% for LED luminaire assembly system when compared to UAL. Moreover, satisfactory results for the proposed heuristics were obtained in terms of deviation from lower bound, especially for SRCUAL heuristics I and II. Moreover, the results indicate that the integration of RC not only decreased the number of workers in 40.28% (29 instances) of test problems in U-lines, but also yielded less number of buffer points (48.48%) with lower workload deviation (75%) among workers in terms of coefficient of variation.

This study provides convenience for capacity management (assessing capacity and adjusting capacity by changing the number of workers) for industrial SRCUAL applications. Meanwhile, SRCUAL applications give the opportunity to increase the capacity for a product or transfer the saved capacity to the assembly of other products. As it is possible to provide one-piece flow with equal workloads via walking workers, SRCUAL has the potential for quick realization of defects and better lead time performance.

To the best of the authors’ knowledge, forward–backward task assignments in U-type lines have not been adapted to WWALs. Moreover, as workers travel overall the line in WWALs, walking time increases drastically. Addressing this research gap and limitation, the main innovative aspect of this study can be considered as the proposal of a new line design (i.e. SRCUAL) which is sourced from the hybridization of UALs and WWAL as well as the segmentation of the line with RC cycles. The superiority of SRCUAL over WWAL and UAL was also discussed. Moreover, operating systematic for SRCUAL was devised. As for methodical aspect, this study is the first attempt to solve the balancing problem for SRCUAL design.

It has become increasingly critical to design and maintain flexible and rapid assembly systems due to unpredictable and varying market conditions. The first stage of developing such systems is to restructure the existing assembly system. After designing the manufacturing system, efforts should be made for capacity adjustments to meet the demand in terms of allocating tasks to workers. Walking-worker assembly systems can be regarded as an effective method to achieve flexibility and agility via rabbit chase (RC) approach in which workers follow each other around the assembly cell or line and perform each task in sequence. In this paper, a novel mathematical programming approach is developed with the aim of integrating RC in assembly processes. Therefore, this study is thought to add value to industrial assembly systems in terms of effectively raising engineering control for task allocation activities.

Two consecutive mathematical models are developed, since such a hierarchical approach provides computational convenience for the problem. The initial mathematical programming model determines the number of workers in each RC loop for each segment. In addition, the number of stations and the distribution of station times in the segments is essential. Therefore, the succeeding mathematical programming model generates stations in each segment and provides convenience for the workflow in RC loops. The output of mathematical programming models are the parameters of simulation model for performance assessment.

The effectiveness of the proposed approach was validated by an application in a real-life chair production system. The application resulted in performance improvements for labour requirement (12.5 per cent) and production lead time (9.6 per cent) when compared to a classical assembly system design (CASD) where one stationary worker exists in each station. In addition, it is worth to note that RC leads to a reduced number of workers for a considerable number (39.4 per cent) of test problems. What is more, input as well as output factors have been determined via discriminant analysis and their impacts to the utilization of RC were analyzed for different levels.

This study is thought to add value to the industry in terms of effectively providing convenience during production planning and task allocation in assembly lines and cells.

To the best knowledge of the author, optimization models for RC considering a real industrial application have not yet been developed. In this context, this paper presents an approach which models RC by the use of mathematical programming in manual assembly processes to address this research gap. The contribution of the paper to the relevant literature is the development of hierarchical mixed integer linear programming models to solve RC problem for the first time.

This paper aims to present a multi-response robust design (RD) optimization approach for U-shaped assembly cells (ACs) with multi-functional walking-workers by using operational design (OD) factors in a simulation setting. The proposed methodology incorporated the design factors related to the operation of ACs into an RD framework. Utilization of OD factors provided a practical design approach for ACs addressing system robustness without modifying the cell structure.

Taguchi’s design philosophy and response surface meta-models have been combined for robust simulation optimization (SO). Multiple performance measures have been considered for the study and concurrently optimized by using a multi-response optimization (MRO) approach. Simulation setting provided flexibility in experimental design selection and facilitated experiments by avoiding cost and time constraints in real-world experiments.

The present approach is illustrated through RD of an AC for performance measures: average throughput time, average WIP inventory and cycle time. Findings are in line with expectations that a significant reduction in performance variability is attainable by trading-off optimality for robustness. Reductions in expected performance (optimality) values are negligible in comparison to reductions in performance variability (robustness).

ACs designed for robustness are more likely to meet design objectives once they are implemented, preventing changes or roll-backs. Successful implementations serve as examples to shop-floor personnel alleviating issues such as operator/supervisor resistance and scepticism, encouraging participation and facilitating teamwork.

ACs include many activities related to cell operation which can be used for performance optimization. The proposed framework is a realistic design approach using OD factors and considering system stochasticity in terms of noise factors for RD optimization through simulation. To the best of the authors’ knowledge, it is the first time a multi-response RD optimization approach for U-shaped manual ACs with multi-functional walking-workers using factors related to AC operation is proposed.

Various staff methodologies of a just‐in‐time (JIT) apparel assembly cell with various numbers of walking workers, and various levels of process time variation were discussed and evaluated by simulation models. Decouplers are placed between two workstations (or subcells) to improve capability and flexibility in an apparel cell. Decouplers enable JIT pull cells to operate with minimum stock‐on‐hand and allow parts and information to flow in opposite directions. Decouplers also provide the JIT pull cell with “make one, check one, and pass one on” capability. A manned assembly cell’s throughput rate depends on the number of workers in the cell and on the variation in each worker’s processing time. Normally, as the processing time variation increases, the throughput rate decreases. However, these simulation studies show that doubling the decoupler capacity increases the cell’s output, even as the processing time variation increases.

This paper aims to provide a framework for the choice, design, set-up and management of a fully flexible assembly system (F-FAS). Many industrial applications for small batch productions require highly flexible automated manufacturing systems. Moreover, some extensions of the F-FAS concept are provided.

The paper reviews recent findings regarding the F-FAS with a top-down approach, and defines an integrated implementation framework. This framework is structured into three strictly correlated phases, and the presented procedure is organized to be readily used for new industrial applications. Practical applications are presented to show how the system can satisfy flexibility demands in a variety of cases.

The proposed framework is organized in three steps: convenience analysis of the F-FAS compared to a traditional flexible assembly system; an optimal design of the feeder; a choice of the set-up and sequencing algorithm yielding the highest throughput. Following these steps, the F-FAS can become an effective solution for small batch productions with frequent reconfigurations. However, due to the limited throughput, the system is not well suited for large batches.

The presented framework allows to implement an F-FAS for a given industrial application, and to evaluate its efficacy with respect to other assembly technologies. Moreover, with the same implementation framework, the F-FAS concept can be applied to production fields that are different from assembly, as shown by the provided examples. This represents an important element of originality and of interest for its strong practical implications in different production environments.

The purpose of this paper is to solve the asynchrony problem between the logistics stream and the information stream in the complex product assembly executive process.

States of assembly and logistics are described by transitions, and implemented via logistics agents and assembly agents. Events in the assembly executive process are described by places, and mapped to radio frequency identification (RFID) tags' states. An agent‐based complex product assembly framework is proposed. Mobile agents are used to encapsulate task and data, and RFID tags' states are able to trigger dispatching of assembly agents and executing of assembly tasks. Assisted by mobile agents' retraction mechanism, on‐site data are carried back when assembly tasks are finished.

An assembly executive process Petri net and a mobile agent‐based complex product assembly framework are proposed.

Dynamic matching mechanism between assembly tasks and materials is achieved, and controlling and monitoring methods of complex product assembly executive process are enhanced.

The purpose of this paper is to present a new way of manufacturing process in the plant of the leading weedicide manufacturing company in Korea, Dongbu.

This paper explains a design of Auto‐ID based weedicide manufacturing process, introduces new mechanism for assembly machine and presents simulation approach to understand potential benefit.

In Dongbu, there was no information matching among bottle, box and pallet levels. Another issue was error propagation. Because, the allowance range for weight difference is different depending on the level of unit, the small weight difference (i.e. deviation) within allowance range in bottle level can create errors when accumulated for boxing. The proposed method improved performance measures such as cycle time and cost of raw materials by introducing Auto‐ID technology. As in the simulation results, it is considered that adoption of radio frequency identification together with this automatic module will improve manufacturing performance drastically.

The research was based on the real world implementation of Auto‐ID based manufacturing in weedicide manufacturing company and discussed a new approach which addresses the current issues of industry.

Multi-manned assembly lines are designed to produce large-sized products, such as automobiles. In this paper, a multi-manned assembly line balancing problem (MALBP) is addressed in which a group of workers simultaneously performs different tasks on a workstation. The key idea in this work is to improve the workstation efficiency and worker efficiency of an automobile plant by minimizing the number of workstations, the number of workers, and the cycle time of the MALBP.

A mixed-integer programming formulation for the problem is proposed. The proposed model is solved with benchmark test problems mentioned in research papers. The automobile case study problem is solved in three steps. In the first step, the authors find the task time of all major tasks. The problem is solved in the second step with the objective of minimizing the cycle time for the sub-tasks and major tasks, respectively. In the third step, the output results obtained from the second step are used to minimize the number of workstations using Lingo 16 solver.

The experimental results of the automobile case study show that there is a large improvement in workstation efficiency and worker efficiency of the plant in terms of reduction in the number of workstations and workers; the number of workstations reduced by 24% with a cycle time of 240 s. The reduced number of workstations led to a reduction in the number of workers (32% reduction) working on that assembly line.

For assembly line practitioners, the results of the study can be beneficial where the manufacturer is required to increased workstation efficiency and worker efficiency and reduce resource requirement and save space for assembling the products.

This paper is the first to apply a multi-manned assembly line balancing approach in real life problem by considering the case study of an automobile plant.

This paper aims to analyze the dominant stray parameters of the DC bus bar and focus on weakening the influence of the stray parameters instead of reducing the value of the stray parameters in DC bus bar while switching. By finding the mechanisms to reduce the effects of stray parameters on switching transient, the simple and straightforward optimization methods could be given for the engineering designer.

The investigations are focused on the equivalent circuit by segmented impedance evaluation in the low-frequency band and the energy propagation by wave impedance evaluation in the high frequency band. This paper proposes an equivalent impedance calculation model to locate the dominant stray parameters in the DC bus bar and takes the energy propagation characteristics using wave impedance into consideration, which can simplify the optimization design of DC bus bar.

According to the equivalent circuit and electromagnetic field analysis, this paper proves the existence of the dominant stray parameters in DC bus bar that is widely used on high-power converters and certifies that not all the stray parameters in different areas of DC bus bar have the same effects on switching process, which can give a good guidance for the optimization design of DC bus bar.

The positions of DC-link capacitors, resulting in only part of stray parameters in DC bus bar has more impact during switching, are significant to the DC bus bar optimization design. These stray parameters named dominant stray parameters in this paper play a leading role in the switching transient process. The area of DC bus bar, which is close to IGBTs and far from DC-link capacitors, contains the dominant stray parameters in the switching transient process. Therefore, the distance between DC-link capacitors and IGBTs should be shortened as much as possible. Based on the results, the efficiency for the DC bus bar optimization design could be improved by weakening the influence of the stray parameters, such as reducing the dominant stray parameters only. Therefore, it can save the cost and time of DC bus bar optimization design.