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The purpose of this paper is to provide an understanding of how the materials feeding design at a workstation impacts the assembly process performance, in terms of manufacturing flexibility, process support, materials planning and work task efficiency.

The empirical data are based on two embedded case studies performed in close corporation with two Swedish automotive companies; additional observations from more than 20 company visits in Japan, and small‐scale case studies performed in Japanese companies. To fully assess the work measurement figures, video recordings, work instructions and layout drawings were used to plot the operators' walking patterns, and it was then possible to map the whole work cycle for an operator. Industrial engineers, managers, group leaders, team leaders and operators were interviewed. Based on the literature review and personal experience from the small‐scale case studies carried out in Japan, the existing assembly systems' component racks were conceptually re‐designed. This led to two hypothetical assembly systems, which could be used for understanding the impact of materials feeding design on assembly process performance. The design of the new component racks and the choice of packaging types were made together with practitioners.

The paper shows that the design of component racks and choice of packaging types have a major impact on the assembly process performance. Component racks with a large depth and small width and tailored packages create important advantages over traditional Swedish component racks designed for EUR‐pallets. Line stocking is not always the best choice for materials feeding, but this paper shows that line stocking, especially in Swedish assembly systems, can be improved. Sequencing can thus be reduced, resulting in fewer problems when there are sequence breaks in the production flow. Component racks with small packages and large depth increase the work task efficiency, volume, mix, new products and modification flexibility. For example, free space is an important issue for these types of flexibilities. Component racks that are portable and easy to rearrange, together with free space, greatly facilitate handling of new product introductions or modifications of products. The new and old component can be displayed and fed to the same workstation, and if there is a larger change a whole segment of a component rack can easily be replaced by a new one between work shifts.

The scope of the study is limited to the conditions at workstations. Consequences for the materials flow upstream (i.e. internal materials handling, warehousing, transport, supplier processes, etc.) are not included, but must in further studies also be considered to avoid sub‐optimisation.

The paper highlights the fact that a shift in focus is necessary when designing workstations with component racks in Swedish companies, meaning that operators become the customers rather than the transport company or materials handler.

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.

Computer simulation techniques are used to evaluate the performance of a welding assembly line which requires modification to achieve some of the philosophies of a just‐in‐time manufacturing environment. The simulation of the existing line using GPSS/H confirmed the operational problems which had been previously identified, and allowed the validation of the computer model. The computer model was then altered to evaluate the performance of several alternative modified assembly lines which would avoid the present operational problems. Discusses some of the techniques used to develop these models, their simulation using the GPSS/H simulation language, and the benefits of using simulation in analysing manufacturing processes.

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.

The purpose of this study is to develop a new mathematical model and an exact solution method for an assembly line rebalancing problem. When an existing assembly line has to be adapted to a new production context, the line balancing, resources allocation and component management solutions have to be revised. The objective is to minimize the number of modifications to be done in the initial line in order to reduce the time and investment needed to meet new production requirements. The proposed model is evaluated via a computational experiment. The obtained results the efficacy of the proposed method.

This paper develops a new mathematical model and an exact solution method for an assembly line rebalancing problem with the objective to minimize the number of modifications to be done in the initial line to reduce the time and investments needed to meet new production requirements.

The computational experiments show the efficacy of the proposed method.

These reconfiguration costs were analysed for different part-feeding policies that can be adopted in an assembly line.

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 paper aims to review and discuss four aspects of mixed-model assembly line balancing (MMALB) problem mainly on the optimization angle. MMALB is a non-deterministic polynomial-time hard problem which requires an effective algorithm for solution. This problem has attracted a number of research fields: manufacturing, mathematics and computer science.

This paper review 59 published research works on MMALB from indexed journal. The review includes MMALB problem varieties, optimization algorithm, objective function and constraints in the problem.

Based on research trend, this topic is still growing with the highest publication number observed in 2016 and 2017. The review indicated that the future research direction should focus on human factors and sustainable issues in the problem modeling. As the assembly cost becomes crucial, resource utilization in the assembly line should also be considered. Apart from that, the growth of new optimization algorithms is predicted to influence the MMALB optimization, which currently relies on well-established algorithms.

The originality of this paper is on the research trend in MMALB. It provides the future direction for the researchers in this field.

The purpose of this paper is to address the adoption of Lean-Kaizen approach to process improvement by the largest manufacturer of steering systems for passenger car and utility vehicle market in India. The company was facing severe liquidity crunch due to falling customer demand (25 percent lower than forecasted), rising cost of raw material and bank borrowing rates. In order to survive in such stiff scenario, the company systematically deployed Kaizen events and drastically improved their internal efficiency.

The study categorically illustrates the employment of value stream mapping (VSM) to target the areas for Kaizen improvement events. Current state VSM was developed to display the non-value-added activities in the existing assembly process. Future state VSM was proposed. After identifying root cause of wastes using 5 Why, three Kaizen events were proposed.

The current state VSM revealed cumulative inventory of 61 days in the entire process, long distances travelled by subassembly for final assembly (294 meters) and a high defect rate (879 parts per million). After modifying the assembly line using lean strategies, the company reduced its inventory levels by 66 percent, defect rate reduced by 32 percent and achieved other benefits such as reduced equipment, production staff and storage space. These reductions helped the company in saving the working capital and also contributed significantly to its profitability.

The study exhibits implementation of Lean-Kaizen approach for redesigning assembly line in an auto component manufacturing unit. The proposed lean strategies are considered to be highly valuable for manufacturer of steering for passenger cars and utility vehicles market.

Assembly line balancing problems that occur in real world situations are dynamic and are fraught with various sources of uncertainties such as the performance of workers and the breakdown of machinery. This is especially true in the clothing industry. The problem cannot normally be solved deterministically using existing techniques. Recent advances in computing technology, especially in the area of computational intelligence, however, can be used to alleviate this problem. For example, some techniques in this area can be used to restrict the search space in a combinatorial problem, thus opening up the possibility of obtaining better results. Among the different computational intelligence techniques, genetic algorithms (GA) is particularly suitable. GAs are probabilistic search methods that employ a search technique based on ideas from natural genetics and evolutionary principles. In this paper, we present the details of a GA and discuss the main characteristics of an assembly line balancing problem that is typical in the clothing industry. We explain how such problems can be formulated for genetic algorithms to solve. To evaluate the appropriateness of the technique, we have carried out some experiments. Our results show that the GA approach performs much better than the use of a greedy algorithm, which is used by many factory supervisors to tackle the assembly line balancing problem.

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.