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The purpose of this paper is to provide a knowledge-enabled digital twin for smart design (KDT-SD) of aircraft assembly line (AAL) to enhance the AAL efficiency, performance and visibility. Modern AALs usually need to have capabilities such as digital-physical interaction and self-evaluation that brings significant challenges to traditional design method for AAL. The digital twin (DT) combining with reusable knowledge, as the key technologies in this framework, is introduced to promote the design process by configuring, understanding and evaluating design scheme.

The proposed KDT-SD framework is designed with the introduction of DT and knowledge. First, dynamic design knowledge library (DDK-Lib) is established which could support the various activities of DT in the entire design process. Then, the knowledge-driven digital AAL modeling method is proposed. At last, knowledge-based smart evaluation is used to understand and identify the design flaws, which could further improvement of the design scheme.

By means of the KDT-SD framework proposed, it is possible to apply DT to reduce the complexity and discover design flaws in AAL design. Moreover, the knowledge equips DT with the capacities of rapid modeling and smart evaluation that improve design efficiency and quality.

The proposed KDT-SD framework can provide efficient design of AAL and evaluate the design performance in advance so that the feasibility of design scheme can be improved as much as possible.

This study seeks to present a simple assembly line design and its balance for a low‐volume manufacturing company.

The study presents experiences with the design and implementation of a simple assembly line. The implementation concerns three aspects; design and construction of the assembly line, the assembly analysis of the product, and then balancing of the line. It also discusses construction and implementation difficulties of this tactical tool in the case company.

The study presents some outcomes from the design, implementation, and balancing of an assembly line for SMEs.

The study is limited by the case company and its experience.

This study is not pure theoretical study, it has application stages for industry, and it provides some real interface for the people from SMEs.

The approach has an original value in respect of implementation of assembly line for a small manufacturing company which has many limitations.

The paper's aim is to assess the impact of product related features on the performances of assembly line manufacturing systems, also providing a specific Design for Manufacturing and Assembly rating index to assess the goodness of a product design solution with respect to assembly line performances.

A computer simulation‐based parametric analysis was carried out to assess the impact of four major product‐related parameters. 216 different assembly line balance problem instances were evaluated. Findings allowed to develop a DFMA rating index specific for assembly line manufacturing as well as design guidelines.

Assembly sequence degrees of freedom and the ratio of the average task duration to the maximum duration are the most influencing parameters. While the former should be maximized, only a moderate task duration variability was found beneficial. The influence of other factors resulted less marked and changing on a case‐specific basis.

Complex interactions between product design features and line performances prevent generalization. The performed numerical experimentation, although extensive, remains somewhat limited respect all possible practical situations. The proposed rating index should be utilized while maintaining an overall perspective about the mutual influence of all parameters. Some suggested guidelines imply a trade off with traditional DFMA guidelines.

Product designers are given useful insights, tools and guidelines to develop better producible products. With the proposed ranking index a designer can easily rate his choices when selecting assembly tasks and sequences, as well as rank alternative product designs solutions.

The paper presents an original discussion about the impact of product design choices on assembly line performances. The developed DFMA rating index and guidelines are new.

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.

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.

Optimizing material handling within the factory is one of the key problems of modern assembly line systems. The purpose of this paper is to focus on simultaneously balancing a robotic assembly line and the scheduling of material handling required for the operation of such a system, a topic that has received limited attention in academia. Manufacturing industries focus on full autonomy because of the rapid advancements in different elements of Industry 4.0 such as the internet of things, big data and cloud computing. In smart assembly systems, this autonomy aims at the integration of automated material handling equipment such as automated guided vehicles (AGVs) to robotic assembly line systems to ensure a reliable and flexible production system.

This paper tackles the problem of designing a balanced robotic assembly line and the scheduling of AGVs to feed materials to these lines such that the cycle time and total tardiness of the assembly system are minimized. Because of the combination of two well-known complex problems such as line balancing and material handling and a heuristic- and metaheuristic-based integrated decision approach is proposed.

A detailed computational study demonstrates how an integrated decision approach can serve as an efficient managerial tool in designing/redesigning assembly line systems and support automated transportation infrastructure.

This study is beneficial for production managers in understanding the main decisional steps involved in the designing/redesigning of smart assembly systems and providing guidelines in decision-making. Moreover, this study explores the material distribution scheduling problems in assembly systems, which is not yet comprehensively explored in the literature.

This study aims to investigate how to identify and address production levelling problems in assembly lines utilising an intensive manual workforce when higher productivity levels are urgently requested to meet market demands.

A mixed-methods approach was used in the research design, integrating case study analysis, interviews and qualitative/quantitative data collection and analysis. The methodology implemented also introduces to the literature on operational performance a novel combination of data analysis methods by introducing the use of the Natural Language Understanding (NLU) methods.

First, the findings unveil the impacts on operational performance that transportation, limited documentation and waiting times play in assembly lines composed of an intensive workforce. Second, the paper unveils the understanding of the role that a limited understanding of how the assembly line functions play in productivity. Finally, the authors provide actionable insights into the levelling problems in manual assembly lines.

This research supports industries operating assembly lines with intensive utilisation of manual workforce to improve operational performance. The paper also proposed a novel conceptual model prescriptively guiding quick and long-term improvements in intensive manual workforce assembly lines. The article assists industrial decision-makers with subsequent turnaround strategies to ensure higher efficiency levels requested by the market.

The paper offers actionable findings relevant to other manual assembly lines utilising an intensive workforce looking to improve operational performance. Some of the methods and strategies examined in this study to improve productivity require minimal capital investments. Lastly, the study contributes to the empirical literature by identifying production levelling problems in a real context.

Assembly line is a common production form and has been effectively used in many industries, but the imprecise processing time of each process makes production line balancing and capacity forecasting the most troublesome problems for production managers. In this paper, uncertain man-hours are represented as interval grey numbers, and the optimization problem of production line balance in the case of interval grey man-hours is studied to better evaluate the production line capacity.

First, this paper constructs the basic model of assembly line balance optimization for the single-product scenario, and on this basis constructs an assembly line balance optimization model under the multi-product scenario with the objective function of maximizing the weighted greyscale production line balance rate, second, this paper designs a simulated annealing algorithm to solve problem. A neighborhood search strategy is proposed, based on assembly line balance optimization, an assembly line capacity evaluation method with interval grey man-hour characteristics is designed.

This paper provides a production line balance optimization scheme with uncertain processing time for multi-product scenarios and designs a capacity evaluation method to provide managers with scientific management strategies so that decision-makers can scientifically solve the problems that the company's design production line is quite different from the actual production situation.

There are few literary studies on combining interval grey number with assembly line balance optimization. Therefore, this paper makes an important contribution in this regard.

This study aims to deliver an approach of how lightweight robot systems can be used to automate manual processes for higher efficiency, increased process capability and enhanced ergonomics. As a use case, a new collaborative testing system for an automated water leak test was designed using an image processing system utilized by the robot.

The “water leak test” in an automotive final assembly line is often a significant cost factor due to its labour-intensive nature. This is particularly the case for premium car manufacturers as each vehicle is watered and manually inspected for leakage. This paper delivers an approach that optimizes the efficiency and capability of the test process by using a new automated in-line inspection system whereby thermographic images are taken by a lightweight robot system and then processed to locate the leak. Such optimization allows the collaboration of robots and manual labour, which in turn enhances the capability of the process station.

This paper examines the development of a new application for lightweight robotic systems and provides a suitable process whereby the system was optimized regarding technical, ergonomic and safety-related aspects.

A new automated testing process in combination with a processing algorithm was developed. A modular system suitable for the integration of human–robot collaboration into the assembly line is presented as well.

To optimize and validate the system, it was set up in a true to reality model factory and brought to a prototypical status. Several original equipment manufacturers showed great interest in the system. Feasibility studies for a practical implementation are running at the moment.

The direct human–robot collaboration allows humans and robots to share the same workspace without strict separation measures, which is a great advantage compared with traditional industrial robots. The workers benefit from a more ergonomic workflow and are relieved from unpleasant, repetitive and burdensome tasks.

A lightweight robotic system was implemented in a continuous assembly line as a new area of application for these systems. The automated water leak test gives a practical example of how to enrich the assembly and commissioning lines, which are currently dominated by manual labour, with new technologies. This is necessary to reach a higher efficiency and process capability while maintaining a higher flexibility potential than fully automated systems.

Design, balancing, and sequencing are the key issues associated with assembly lines (ALs). The purpose of this paper is to identify AL design issues and to develop an integrated methodology for mixed‐model assembly line balancing (MMALB) and sequencing. Primarily, mixed‐model lines are utilized for high‐variety, low‐volume job shop or batch production. Variation of a generic product is important for the manufacturers as the demand is mostly customer driven in the present global market.

Different AL design norms, performance indexes, and AL workstation indexes have been identified in the initial stage of this work. As the paper progresses, it has focused towards an integrated approach for MMALB and sequencing addressed for small‐ and medium‐scale assembly plants. A small‐scale practical problem has been justified with this integrated methodology implemented by MATLAB.

ALs execution in the production floor require many important factors to be considered. Different line orientations, production approaches, line characteristics, performance and workstation indexes, problem definitions, balancing and product sequencing in accordance with the objective functions are needed to be taken into account by the line designer.

This paper has highlighted the important AL design characteristics and also provided an integrated approach for balancing mixed‐model assembly lines (MMALs) combined with sequencing heuristic. The findings of this paper can be helpful for the designers while designing an AL. The integrated approach for balancing and sequencing of MMALs can be used as a functional tool for assembly‐based contemporary industries.