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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.

To respond to customer needs and achieve customized manufacturing, the manufacturing industry, as represented by electronics assembly companies, has embarked on a path of business model transformation (customer to manufacturer [C2M]). The purpose of this paper is to examine the practical application of assembly line-Seru conversion in a Chinese electronics assembly company during the C2M transition.

To begin with, this paper proposed a production line improvement scheme suitable for the conversion of C2M manufacturing enterprise assembly line-Seru based on an analysis of the difficulties encountered in the existing production line of A company in China. Then, a mathematical model was presented for the minimum value of the makespan and the maximum workers’ expenditure between Serus. Finally, the SA-NSGA-II algorithm and the entropy-weight TOPSIS approach were used to determine the optimal scheme for Seru unit, batch, product type and worker distribution.

Seru production and multiskilled workers are more suited to the C2M business model. The most effective strategy for worker allocation can reduce the number of employees and makespan in Serus. Additionally, the performance of the SA-NSGA-II algorithm and the method of selecting the optimal solution from the Pareto solution by the entropy-weighted TOPSIS method is also demonstrated.

Through a detailed study of how to transform the production line, other companies can apply the methods outlined in this article to shorten the delivery time, make full use of the abilities of workers and assign workers to specific positions, thereby reducing the number of workers, workers’ expenditure and improving the balance rate of production lines.

Given the scarcity of studies on the production method of C2M-type firms in the prior literature, this paper examined the assembly line-Seru conversion problem with the goal of minimizing the makespan and worker expenditure. To address the NSGA-II algorithm’s insufficient convergence, the simulated annealing process is incorporated into the method, which improves the optimization performance.

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.

This paper proposes an integrated value stream mapping (VSM) for a complex assembly line to improve the leanness of a complex automotive component manufacturing organization.

This study depicts the application of VSM at the case organization, where top management is concerned about the challenges of higher cycle time and lower productivity. Gemba walks were conducted to establish the concept of “walk the flow, create the flow” along the assembly line. The multi-hierarchical cross-functional team developed the current value stream map to know the “as-is” state. Then, the team analysed the current VSM and proposed the future VSM for the “to-be” state.

The integrated VSM shows different processes and work cells, various wastes, non-value-added activities, cycle time, uptime and the material and information flows for both products of the assembly line on the same map. The integrated VSM reduced cycle time, non-value-added activities, work in process inventory and improved line efficiency and production per labour hour for both the products, simultaneously.

The limitation of the study is that the study focussed only on the application of VSM for one complex assembly only. Future research may be conducted using the developed integrated VSM approach in other complex production environments.

Managers can identify and reduce system waste by incorporating the concept of integrated VSM in a complex production or assembly environment where two or more products are being manufactured/assembled with low similarity.

The application of VSM for assembly lines is highly challenging because of merging flows, a large number of child parts in the lines and assembly of more than one product on the same line.

This paper aims to propose a parallel automated assembly line system to produce multiple products in a semi-continuous system.

The control system developed in this research consists of a manufacturing system for two-level hierarchical dynamic decisions of autonomous/automated/automatic-guided vehicles (AGVs) dispatching/next station selection and machining schedules and a station control scheme for operational control of machines and components. In this proposed problem, the assignment of multiple AGVs to different assembly lines and the semi-continuous stations is a critical objective. AGVs and station scheduling decisions are made at the assembly line level. On the other hand, component and machining resource scheduling are made at the station level.

The proposed scheduler first decomposes the dynamic scheduling problems into a static AGV and machine assignment during each short-term rolling window. It optimizes weighted completion time of tasks for each short-term window by formulating the task and resource assignment problem as a minimum cost flow problem during each short-term scheduling window. A comprehensive decision making process and heuristics are developed for efficient implementation. A simulation study is worked out for validation.

Several assembly lines are configured to produce multiple products in which the technologies of machines are shared among the assembly lines when required. The sequence of stations is pre-specified in each assembly line and the components of a product are kept in machine magazine. The transportation between the stations in an assembly line (intra assembly line) and among stations in different assembly lines (inter assembly line) are performed using AGVs.

Reducing production auxiliary time is the key to improve the efficiency of the existing mixed-flow assembly line. This paper proposes a method combining improved genetic algorithm (GA) and Flexsim software. It also investigates mixed-flow assembly line scheduling and just-in-time (JIT) parts feeding scheme to reduce waste in production while taking the existing hill-drop mixed-flow assembly line as an example to verify the effectiveness of the method.

In this research, a method is presented to optimize the efficiency of the present assembly line. The multi-objective mathematical model is established based on the objective function of the minimum production cycle and part consumption balance, and the solution model is developed using multi-objective GA to obtain the mixed flow scheduling scheme of the hill-drop planter. Furthermore, modeling and simulation with Flexsim software are investigated along with the contents of line inventory, parts transportation means, daily feeding times and time points.

Theoretical analysis and simulation experiments are carried out in this paper while taking an example of a hill-drop planter mixed-flow assembly line. The results indicate that the method can effectively reduce the idle and overload of the assembly line, use the transportation resources rationally and decrease the accumulation of the line inventory.

The method of combining improved GA and Flexsim software was used here for the first time intuitively and efficiently to study the balance of existing production lines and JIT feeding of parts. Investigating the production scheduling scheme provides a reference for the enterprise production line accompanied by the quantity allocation of transportation tools, the inventory consumption of the spare parts along the line and the utilization rate of each station to reduce the auxiliary time and apply practically.

The development of the moving automobile final assembly line was a major milestone in manufacturing. The techniques required to make it work are demanding, but the resulting increase in productivity is phenomenal. Consequently, and not surprisingly, some people have claimed a major role in its development. The initial date for this innovation is either July 1908, or August 1913 and credit is given to Henry Ford, Charles Sorensen, Clarence Avery, or W.C. Klann, depending on whom one reads. This paper tries to clarify what happened on these dates and who was responsible. Investigation reveals that each of these men did play a role in development of the moving automobile assembly line.

The purpose of this paper is to develop an intelligent robot assembly system for the moving production line. Moving production lines are widely used in many manufacturing factories, including automotive and general industries. Industrial robots are hardly used to perform any tasks on the moving production lines. One of the main reasons is that it is difficult for conventional industrial robots to adjust to any sort of change. Therefore, more intelligent industrial robotic systems have to be developed to adopt the random motion of the moving production lines. This paper presents an intelligent robotics system that performs an assembly process while the object is moving, using synergic combination of visual servoing and force control technology.

The developed intelligent robotic system includes some rules to ensure the success of the assembly processes. Also visual servoing and force control are used to deal with the random motion of the moving objects. Since the objects on the moving production lines are moving with random speed, visual servoing is adopted to tracking the motion of the moving object. Force control is also integrated to control the motion of the robot and keep the robotic system compliant with the moving objects to avoid the damage of the whole system.

The developed intelligent robotic technology has been successfully implemented. The wheel loading process is used as example.

Since the developed technology is based on the low‐level motion control, safety has to be considered. Currently, it is done by motion supervision.

The developed technology can be used to perform assemblies in the moving production lines. Since the developed platform is based on the synergic combination of visual servoing and force control technology, it can be used in other areas, such as seam tracking and seat loading, etc.

This paper provides a practical solution of performing assemblies on the moving production lines, which is not available on the current industrial robot market.

In a kitting supply system, the occurrence of material-handling errors is unavoidable and will cause serious production losses to an assembly line. To minimize production losses, this paper aims to present a dynamic scheduling problem of automotive assembly line considering material-handling mistakes by integrating abnormal disturbance into the material distribution problem of mixed-model assembly lines (MMALs).

A multi-phase dynamic scheduling (MPDS) algorithm is proposed based on the characteristics and properties of the dynamic scheduling problem. In the first phase, the static material distribution scheduling problem is decomposed into three optimization sub-problems, and the dynamic programming algorithm is used to jointly optimize the sub-problems to obtain the optimal initial scheduling plan. In the second phase, a two-stage rescheduling algorithm incorporating removing rules and adding rules was designed according to the status update mechanism of material demand and multi-load AGVs.

Through comparative experiments with the periodic distribution strategy (PD) and the direct insertion method (DI), the superiority of the proposed dynamic scheduling strategy and algorithm is verified.

To the best of the authors’ knowledge, this study is the first to consider the impact of material-handling errors on the material distribution scheduling problem when using a kitting strategy. By designing an MPDS algorithm, this paper aims to maximize the absorption of the disturbance caused by material-handling errors and reduce the production losses of the assembly line as well as the total cost of the material transportation.

Assembly systems require uninterrupted components' availability to feed workstations. This paper aims to propose a methodology to help managers in evaluating and selecting the most suitable policy for materials delivery to the shop floor. The analysis focuses on three basic policies, namely kitting, just in time kanban‐based continuous supply and line storage, even including class‐based hybrid policies.

Descriptive models are developed to design components' delivery systems and to compute their performances. Empirical criteria are utilized to associate specific policies to components classes in order to implement customized hybrid line feeding policies. A case study is then included to exemplify the method application and to show its capabilities as a decision making tool.

Hybrid feeding policies may be preferable to a single feeding policy common to all components. This is shown in a representative case study. However, in general there is a priori superior method and only a comparison of alternative feeding policies based on objective performance measures can determine the best approach in specific industrial applications.

The methodology is aimed at preliminary sizing and selection of alternative line feeding systems in deterministic environments. It is not intended for detailed performance analysis of assembly systems.

Production managers are given quantitative decision tools to properly select the components' delivery method at an early decision stage. This allows trade‐offs between alternatives to be explored in order to deploy customized feeding policies differentiated on components basis to better fit specific company requirements.

The paper extends previous descriptive models for line feeding systems and includes the possibility of hybrid policies.