A Survey on Cost and Profit Oriented Assembly Line Balancing

http://www.nt.ntnu.no/users/skoge/prost/proceedings/ifac2014/media/files/0866.pdfInternational audienceProblems, approaches and analytical models on assembly line balancing that deal explicitly with cost and profit oriented objectives are analysed. This survey paper serves to identify and work on open problems that have wide practical applications. The conclusions derived might give insights in developing decision support systems (DSS) in planning profitable or cost efficient assembly lines

Balancing of parallel U-shaped assembly lines

Copyright © 2015 Elsevier. This is a PDF file of an unedited manuscript that has been accepted for publication in Computers & Operations Research (doi: 10.1016/j.cor.2015.05.014). As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable 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. Please cite this article as: Ibrahim Kucukkoc, David Z. Zhang, Balancing of parallel U-shaped assembly Lines, Computers & Operations Research, http://dx.doi.org/10.1016/j.cor.2015.05.014A new hybrid assembly line design, called Parallel U-shaped Assembly Line system, is introduced and characterised along with numerical examples for the first time. Different from existing studies on U-shaped lines, we combine the advantages of two individual line configurations (namely parallel lines and U-shaped lines) and create an opportunity for assigning tasks to multi-line workstations located in between two adjacent U-shaped lines with the aim of maximising resource utilisation. Utilisation of crossover workstations, in which tasks from opposite areas of a same U-shaped line can be performed, is also one of the main advantages of the U-shaped lines. As in traditional U-shaped line configurations, the newly proposed line configuration also supports the utilisation of crossover workstations. An efficient heuristic algorithm is developed to find well-balanced solutions for the proposed line configurations. Test cases derived from existing studies and modified in accordance with the proposed system in this study are solved using the proposed heuristic algorithm. The comparison of results obtained when the lines are balanced independently and when the lines are balanced together (in parallel to each other) clearly indicates that the parallelisation of U-shaped lines helps decrease the need for workforce significantly.Balikesir UniversityTurkish Council of Higher Educatio

Mixed-integer linear programming approach to U-line balancing with objective of achieving proportional throughput per worker in a dynamic environment

One of the major challenges of manufacturing companies is to remain competitive in a very dynamic environment dictated by fluctuations in production rate and customer demand. These challenges may be attributed to frequent changes in customer expectations, unsteady economic conditions or failure to reach the projected throughput due to inefficiencies in production systems. Survival in such a dynamic environment is contingent on implementing manufacturing systems that are able to adapt to change quickly and economically. The U-Shaped production cell is considered to be one of the most flexible techniques for changing the number of workers in the cell to match cell cycle time to planned cycle time. However, companies currently use a trial-and-error method to develop walk-paths. It is a very iterative and time consuming process that does not always guarantee an optimal solution. Walk-paths need to be performed for all possible number of workers. Fluctuations are adapted to by altering only the number of workers and the worker’s walk-path without changing the number of stations and task allocations. Selecting the best configuration (i.e. optimal number of stations and task allocation) is dependant upon the linearity metric i.e. the measurement of the proportional throughput per worker. Designing the production cell by considering the linearity helps to keep direct labor costs per unit at a minimum for any number of workers employed. This thesis proposes a mixed integer linear model for U-shaped lines that determines the best cell configuration for various number of workers with the objective function of achieving proportional throughput per worker and decreasing the iteration time. The problem originated at Delphi Corporation but has been generalized to be applicable to other Lean systems. The model has been constructed using OPL Studio 3.7

A bibliographic review of production line design and balancing under uncertainty

This bibliography reviews the solution methods developed for the design and balancing problems of production lines such as assembly and disassembly lines. The line design problem aims in determining the number of workstations along with the corresponding assignment of tasks to each workstation, while the line balancing problem seeks an assignment of tasks, to the existing workstations of the line, which ensures that the workloads are as equal as possible among the workstations. These two optimisation problems can be also integrated and treated as a multi-objective optimisation problem. This review considers both deterministic and stochastic formulations for disassembly lines and is limited to assembly line design and balancing under uncertainty. This bibliography covers more than 90 publications since 1976 for assembly and 1999 for disassembly

The Effect of Learning on Assembly Line Balancing: A Review

Classical assembly line balancing (ALB) models assume constant cycle times during production. However, this assumption oversimplifies the actual situation, especially in small batch production of up to a few hundred units, since employees can significantly improve their performance thanks to the learning effect, causing task times to decrease. Several researchers have realised the importance of the effect of learning in ALB. However, only a limited number of papers have so far addressed this issue. This is problematic, since ignoring the learning effect in ALB may lead to inaccurate results and by extension misleading conclusions. This study summarises the main contributions in the field of ALB that focus on the learning effect. First, assembly lines (ALs) and ALB problems are characterised. Next, the importance of the learning effect in ALB is highlighted, and the main learning curve (LC) models are introduced. Finally, an exhaustive review of the main contributions in the field of ALB and learning effect is provided. The results highlight that many problems in this area need to be investigated further, in relation to both conceptual model building and the development of algorithms for solving practical size problems

Re-balancing problem for assembly lines: new mathematical model and exact solution method

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

A mathematical model and artificial bee colony algorithm for the lexicographic bottleneck mixed-model assembly line balancing problem

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Typically, the total number of required workstations are minimised for a given cycle time (this problem is referred to as type-1), or cycle time is minimised for a given number of workstations (this problem is referred to as type-2) in traditional balancing of assembly lines. However, variation in workload distributions of workstations is an important indicator of the quality of the obtained line balance. This needs to be taken into account to improve the reliability of an assembly line against unforeseeable circumstances, such as breakdowns or other failures. For this aim, a new problem, called lexicographic bottleneck mixed-model assembly line balancing problem (LB-MALBP), is presented and formalised. The lexicographic bottleneck objective, which was recently proposed for the simple single-model assembly line system in the literature, is considered for a mixed-model assembly line system. The mathematical model of the LB-MALBP is developed for the first time in the literature and coded in GAMS solver, and optimal solutions are presented for some small scale test problems available in the literature. As it is not possible to get optimal solutions for the large-scale instances, an artificial bee colony algorithm is also implemented for the solution of the LB-MALBP. The solution procedures of the algorithm are explored illustratively. The performance of the algorithm is also assessed using derived well-known test problems in this domain and promising results are observed in reasonable CPU times

Second order conic approximation for disassembly line design with joint probabilistic constraints

A problem of profit oriented disassembly line design and balancing with possible partial disassembly and presence of hazardous parts is studied. The objective is to design a production line providing a maximal revenue with balanced workload. Task times are assumed to be random variables with known normal probability distributions. The cycle time constraints are to be jointly satisfied with at least a predetermined probability level. An AND/OR graph is used to model the precedence relationships among tasks. Several lower and upper–bounding schemes are developed using second order cone programming and convex piecewise linear approximation. To show the relevance and applicability of the proposed approach, a set of instances from the literature are solved to optimality

New matrix methodology for algorithmic transparency in assembly line balancing using a genetic algorithm

© 2022. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/This article focuses on the Mixed-Model Assembly Line Balancing single-target problem of type 2 with single-sided linear assembly line configurations, which is common in the industrial environment of small and medium-sized enterprises (SMEs). The main objective is to achieve Algorithmic Transparency (AT) when using Genetic Algorithms for the resolution of balancing operation times. This is done by means of a new matrix methodology that requires working with product functionalities instead of product references. The achieved AT makes it easier for process engineers to interpret the obtained solutions using Genetic Algorithms and the factors that influence decisions made by algorithms, thereby helping in the later decision-making process. Additionally, through the proposed new matrix methodology, the computational cost is reduced with respect to the stand-alone use of Genetic Algorithms. The AT produced using the new matrix methodology is validated through its application in an industry-based paradigmatic example.Peer ReviewedPostprint (published version

Analysing and levelling manufacturing complexity in mixed-model assembly lines

In recent years, the automotive industry has witnessed a rapid increase in model variety and customization. New models, which are mainly being introduced in response to consumers demand, feature long lists of choices in terms of variants (engine model, comfort level, colour palette, etc.) and options (entertainment system, start/stop functionality, etc.). This high variability increases the complexity of factory processes and workstations and thus impacts directly upon the complexity of the manufacturing system as a whole. The shift from mass production to mass customized production is a trend that looks likely to continue in the foreseeable future, driven by automotive manufacturers' struggle to maintain market share in their traditional markets and seize market share in new, fast-growing markets. To cope with this intensified customization, automotive assembly platforms are designed to be capable of assembling a large range of relatively different models. That is they become mixed-model assembly lines. This implies that a high variety of tasks are to be performed at each workstation. As a consequence, the manufacturing complexity at these workstations increases. Mixed-model assembly lines are flow-line production systems that typically encounter the assembly line balancing problem (ALBP), a combinatorial optimization problem involving the optimal partitioning of assembly work among the workstations with a particular objective in mind. Subsequently, solving mixed-model assembly line balancing problems (MMALBPs) is much more complex than single-model cases, as workload must be smoothed for all workstations and all models in order to avoid overload or idle time. Despite the recent focus on manufacturing complexity and the extensive study of the ALBP, little research has explored how complexity can be applied to optimize line efficiency. Manufacturing complexity has been a key concern of many researchers and manufacturers in recent years, however, practical procedures to level complexity have not yet been considered and investigated when balancing the assembly lines. Analysing, measuring and monitoring complexity while creating line balancing solutions is a new and unexplored topic, especially when using real industry scenarios. In this dissertation, we propose an approach that can be used to monitor manufacturing complexity at each workstation while balancing the mixed-model assembly lines. The research carried out relies on an investigation of real MMAL's aiming to develop a deep analysis of complexity. The goal is to understand what and how complexity is generated, in order to cope and reduce the high complexity and its impacts in the line. During several visits and workshops carried out in collaboration with manufactures, we could observe that work load distribution is directly related with models variety, as tasks' time might differ from model to model. We first explored the existing scientific literature on the mixed-model assembly line balancing problem and manufacturing complexity in Chapter 2. Then, manufacturing complexity is investigated using two approaches: (1) an empirical analysis approach based on data collected in the Field and (2) a quantitative analysis approach measuring the level of uncertainty by means of entropy