Research Trends and Outlooks in Assembly Line Balancing Problems

This paper presents the findings from the survey of articles published on the assembly line balancing problems (ALBPs) during 2014-2018. Before proceeding a comprehensive literature review, the ineffectiveness of the previous ALBP classification structures is discussed and a new classification scheme based on the layout configurations of assembly lines is subsequently proposed. The research trend in each layout of assembly lines is highlighted through the graphical presentations. The challenges in the ALBPs are also pinpointed as a technical guideline for future research works

Type-E Parallel Two-Sided Assembly Line Balancing Problem: Mathematical Model and Ant Colony Optimisation based Approach with Optimised Parameters

Copyright © 2015 Elsevier. This is a PDF file of an unedited manuscript that has been accepted for publication in Computers and Industrial Engineering (doi:10.1016/j.cie.2014.12.037). The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.There are many factors which affect the performance of a complex production system. Efficiency of an assembly line is one of the most important of these factors since assembly lines are generally constructed as the last stage of an entire production system. Parallel two-sided assembly line system is a new research domain in academia though these lines have been utilised to produce large sized products such as automobiles, trucks, and buses in industry for many years. Parallel two-sided assembly lines carry practical advantages of both parallel assembly lines and two-sided assembly lines. The main purpose of this paper is to introduce type-E parallel two-sided assembly line balancing problem for the first time in the literature and to propose a new ant colony optimisation based approach for solving the problem. Different from the existing studies on parallel assembly line balancing problems in the literature, this paper aims to minimise two conflicting objectives, namely cycle time and number of workstations at the same time and proposes a mathematical model for the formal description of the problem. To the best of our knowledge, this is the first study which addresses both conflicting objectives on a parallel two-sided assembly line configuration. The developed ant colony optimisation algorithm is illustrated with an example to explain its procedures. An experimental design is also conducted to calibrate the parameters of the proposed algorithm using response surface methodology. Results obtained from the performed computational study indicate that minimising cycle time as well as number of workstations help increase system efficiency. It is also observed that the proposed algorithm finds promising results for the studied cases of type-E parallel two-sided assembly line balancing problem when the results are compared with those obtained from other three well-known heuristics

A mathematical model and genetic algorithm-based approach for parallel two-sided assembly line balancing problem

Copyright © 2015 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in Production Planning & Control on 27 April 2015, available online: http://dx.doi.org/10.1080/09537287.2014.994685Assembly lines are usually constructed as the last stage of the entire production system and efficiency of an assembly line is one of the most important factors which affect the performance of a complex production system. The main purpose of this paper is to mathematically formulate and to provide an insight for modelling the parallel two-sided assembly line balancing problem, where two or more two-sided assembly lines are constructed in parallel to each other. We also propose a new genetic algorithm (GA)-based approach in alternatively to the existing only solution approach in the literature, which is a tabu search algorithm. To the best of our knowledge, this is the first formal presentation of the problem as well as the proposed algorithm is the first attempt to solve the problem with a GA-based approach in the literature. The proposed approach is illustrated with an example to explain the procedures of the algorithm. Test problems are solved and promising results are obtained. Statistical tests are designed to analyse the advantage of line parallelisation in two-sided assembly lines through obtained test results. The response of the overall system to the changes in the cycle times of the parallel lines is also analysed through test problems for the first time in the literature

A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in Smart Remanufacturing

Remanufacturing prolongs the life cycle and increases the residual value of various end-of-life (EoL) products. As an inevitable process in remanufacturing, disassembly plays an essential role in retrieving the high-value and useable components of EoL products. To disassemble massive quantities and multi-types of EoL products, disassembly lines are introduced to improve the cost-effectiveness and efficiency of the disassembly processes. In this context, disassembly line balancing problem (DLBP) becomes a critical challenge that determines the overall performance of disassembly lines. Currently, the DLBP is mostly studied in straight disassembly lines using single-objective optimization methods, which cannot represent the actual disassembly environment. Therefore, in this paper, we extend the mathematical model of the basic DLBP to stochastic parallel complete disassembly line balancing problem (DLBP-SP). A novel simulated annealing-based hyper-heuristic algorithm (HH) is proposed for multi-objective optimization of the DLBP-SP, considering the number of workstations, working load index, and profits. The feasibility, superiority, stability, and robustness of the proposed HH algorithm are validated through computational experiments, including a set of comparison experiments and a case study of gearboxes disassembly. To the best of our knowledge, this research is the first to introduce gearboxes as a case study in DLBP which enriches the research on disassembly of industrial equipment

Modelling and Solving Mixed-model Parallel Two-sided Assembly Line Problems

The global competitive environment and the growing demand for personalised products have increased the interest of companies in producing similar product models on the same assembly line. Companies are forced to make significant structural changes to rapidly respond to diversified demands and convert their existing single-model lines into mixed-model lines in order to avoid unnecessary new line construction cost for each new product model. Mixed-model assembly lines play a key role in increasing productivity without compromising quality for manufacturing enterprises. The literature is extensive on assembling small-sized products in an intermixed sequence and assembling large-sized products in large volumes on single-model lines. However, a mixed-model parallel two-sided line system, where two or more similar products or similar models of a large-sized product are assembled on each of the parallel two-sided lines in an intermixed sequence, has not been of interest to academia so far. Moreover, taking model sequencing problem into consideration on a mixed-model parallel two-sided line system is a novel research topic in this domain. Within this context, the problem of simultaneous balancing and sequencing of mixed-model parallel two-sided lines is defined and described using illustrative examples for the first time in the literature. The mathematical model of the problem is also developed to exhibit the main characteristics of the problem and to explore the logic underlying the algorithms developed. The benefits of utilising multi-line stations between two adjacent lines are discussed and numerical examples are provided. An agent-based ant colony optimisation algorithm (called ABACO) is developed to obtain a generic solution that conforms to any model sequence and it is enhanced step-by-step to increase the quality of the solutions obtained. Then, the algorithm is modified with the integration of a model sequencing procedure (where the modified version is called ABACO/S) to balance lines by tracking the product model changes on each workstation in a complex production environment where each of the parallel lines may a have different cycle time. Finally, a genetic algorithm based model sequencing mechanism is integrated to the algorithm to increase the robustness of the obtained solutions. Computational tests are performed using test cases to observe the performances of the developed algorithms. Statistical tests are conducted through obtained results and test results establish that balancing mixed-model parallel two-sided lines together has a significant effect on the sought performance measures (a weighted summation of line length and the number of workstations) in comparison with balancing those lines separately. Another important finding of the research is that considering model sequencing problem along with the line balancing problem helps algorithm find better line balances with better performance measures. The results also indicate that the developed ABACO and ABACO/S algorithms outperform other test heuristics commonly used in the literature in solving various line balancing problems; and integrating a genetic algorithm based model sequencing mechanism into ABACO/S helps the algorithm find better solutions with less amount of computational effort

Algorithms and Methods for Designing and Scheduling Smart Manufacturing Systems

This book, as a Special Issue, is a collection of some of the latest advancements in designing and scheduling smart manufacturing systems. The smart manufacturing concept is undoubtedly considered a paradigm shift in manufacturing technology. This conception is part of the Industry 4.0 strategy, or equivalent national policies, and brings new challenges and opportunities for the companies that are facing tough global competition. Industry 4.0 should not only be perceived as one of many possible strategies for manufacturing companies, but also as an important practice within organizations. The main focus of Industry 4.0 implementation is to combine production, information technology, and the internet. The presented Special Issue consists of ten research papers presenting the latest works in the field. The papers include various topics, which can be divided into three categories—(i) designing and scheduling manufacturing systems (seven articles), (ii) machining process optimization (two articles), (iii) digital insurance platforms (one article). Most of the mentioned research problems are solved in these articles by using genetic algorithms, the harmony search algorithm, the hybrid bat algorithm, the combined whale optimization algorithm, and other optimization and decision-making methods. The above-mentioned groups of articles are briefly described in this order in this book

Optimization of two sided assembly line balancing with resource constraint

Two-sided assembly line balancing (2S-ALB) problems are practically useful in improving the production of large-sized high-volume products. Many research has proposed various approaches to study and balance this well-known ALB problem. Although much attention has been given to solve and optimize 2S-ALB, the majority of the research assumed the workstation has similar capabilities. This research has been conducted in an automotive assembly line, where most of the equipment used in assembly is different from one workstation to another. The assumption that all workstation has similar capabilities lead to inefficient resource utilization in assembly line design. This research aims to model and optimize 2S-ALB with resource constraints. Besides optimizing the line balancing, the proposed model also will minimize the number of resources in the two-sided assembly line. The research begins with problem formulation by establishing four optimization objectives. The considered optimization objectives were to minimize the number of workstations, number of mated-workstation, total idle time, and number of resources. For optimization purpose, Particle Swarm Optimization is modified to find the best solution besides reducing the dependencies on a single best solution. This is conducted by replacing the best solution with the top three solutions in the reproduction process. A set of benchmark problems for 2S-ALB were used to test the proposed Modified Particle Swarm Optimization (MPSO) in the computational experiment. Later, the proposed 2S-ALB with resource constraint model and algorithm was validated using a case study problem. The computational experiment result using benchmark test problems indicated that the proposed MPSO was able to search for better solution in 91.6% of the benchmark problems. The good performance of MPSO is attributed to its ability to maintain particle diversity over the iteration. Meanwhile, the case study result indicated that the proposed 2S-ALB with resource constraint model and MPSO algorithm are able to be utilized for the real problem. In the future, the multiobjective optimization problem will be considered to be optimized for other types of general assembly lines

Optimization of A Real Time Multi Mixed Make-To-Order Assembly Line to Reduce Positive Drift

ThesisAssembly lines are critical for the realization of product manufacture. In recent times, there has been a shift from the make-to-stock (mass production) approach to a make-to-order (mass customization) approach and this has brought on a strong emphasis on product variety. Although variety can be included to a product at various phases of production, literature shows that by providing each functional module of the product with several variants, assembly lines provide the most cost-effective approach to achieve high product variety. However, there are certain challenges associated with using assembly lines to achieve product variety. One of these challenges is assembly line balancing. Assembly line balancing is the search for an optimum assignment of tasks, such that given precedence constraints according to pre-defined single or multi objective goal are met. These objectives include reducing the number of stations for a given cycle time or minimizing the cycle time for a given number of stations. Cycle time refers to the amount of time allotted to accomplish a certain process in an assembly process. This deviation from the optimal cycle time is technically referred to as drift. Drift can be negative or positive. Negative drift represents the time span during which an assembly line is idle, due to work being finished ahead of prescribed cycle time. Positive drift, meanwhile, represents time span in which an assembly line exceeds the prescribed cycle time. The problems caused by drift, especially positive drift, is so vast that there is a research niche are dedicated to this study called Assembly Line Balancing Problems. Various authors have proposed numerous solutions for solving assembly line balancing problems created by positive drift. However, there is very little information on optimizing multi model make-to order systems with real time inputs so as to reduce the effects of positive drift. This study looks at how such a system can be optimized by using the case study of a water bottling plant. This is done by initially looking at the literature in the field of assembly line balancing to isolate the research gap this study aims to fill. Secondly, the water bottling plant, described as the case study, is modelled using MATLAB/Simulink. Thirdly, the different optimization methodologies are discussed and applied to the created model. Finally, the optimized model is tested and the results are analysed. The results of this study show that positive drift, which can be a major challenge in a real time multi mixed assembly line, can be reduced by the optimization of assembly lines. The results of this study can also be seen as an addition to the knowledge base of the broader research on mixed model assembly line balancing

Assembly Line

An assembly line is a manufacturing process in which parts are added to a product in a sequential manner using optimally planned logistics to create a finished product in the fastest possible way. It is a flow-oriented production system where the productive units performing the operations, referred to as stations, are aligned in a serial manner. The present edited book is a collection of 12 chapters written by experts and well-known professionals of the field. The volume is organized in three parts according to the last research works in assembly line subject. The first part of the book is devoted to the assembly line balancing problem. It includes chapters dealing with different problems of ALBP. In the second part of the book some optimization problems in assembly line structure are considered. In many situations there are several contradictory goals that have to be satisfied simultaneously. The third part of the book deals with testing problems in assembly line. This section gives an overview on new trends, techniques and methodologies for testing the quality of a product at the end of the assembling line

A mixed-integer programming model for cycle time minimization in assembly line balancing: Using rework stations for performing parallel tasks

[EN] In assembly lines, rework stations are generally used for reprocessing defective items. On the other hand, using rework stations for this purpose only might cause inefficient usage of the resources in this station especially in an assembly line with a low defective rate. In this study, a mixed-integer programming model for cycle time minimization is proposed by considering the use of rework stations for performing parallel tasks. By linearizing the non-linear constraint about parallel tasks using a variate transformation, the model is transformed to a linear-mixed-integer form. In addition to different defective rates, different rework station positions are also considered using the proposed model. The performance of the model is analyzed on several test problems from the related literature.Cavdur, F.; Kaymaz, E. (2020). A mixed-integer programming model for cycle time minimization in assembly line balancing: Using rework stations for performing parallel tasks. 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