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

Improving the resolution of the simple assembly line balancing problem type E

The simple assembly line balancing problem type E (abbreviated as SALBP-E) occurs when the number of workstations and the cycle time are variables and the objective is to maximise the line efficiency. In contrast with other types of SALBPs, SALBP-E has received little attention in the literature. In order to solve optimally SALBP-E, we propose a mixed integer liner programming model and an iterative procedure. Since SALBP-E is NP-hard, we also propose heuristics derived from the aforementioned procedures for solving larger instances. An extensive experimentation is carried out and its results show the improvement of the SALBP-E resolution

Solving the accessibility windows assembly line problem level 1 and variant 1 (AWALBP-L1-1) with precedence constraints

Assembly line balancing problems (ALBPs) are among the most studied combinatorial optimization problems due to their relevance in many production systems. In particular, the accessibility windows ALBP (AWALBP) may arise when the workpieces are larger than the workstations, which implies that at a given instant the workstations have access to only a portion of the workpieces. Thus, the cycle is split into forward steps and stationary stages. The workpieces advance during the forward steps and the tasks are processed during the stationary stages. Several studies have dealt with the AWALBP assuming that there are no precedence relationships between tasks. However, this assumption is not always appropriate. In this work we solve the first level of AWALBP (AWALBP-L1) considering the existence of precedence relationships. Specifically, this work deals with variant 1 (AWALBP-L1-1), in which each task can be performed at only one workstation and, therefore, only the stationary stages and the starting instants in which the tasks are performed have to be decided. We design a solution procedure that includes pre-processing procedures, a matheuristic and a mixed integer linear programming model. An extensive computational experiment is carried out to evaluate its performance.Peer ReviewedPostprint (author's final draft

A case study at the Nissan Barcelona factory to minimize the ergonomic risk and its standard deviation in a mixed-model assembly line

This work examines a balancing problem wherein the objective is to minimize both the ergonomic risk dispersion between the set of workstations of a mixed-model assembly line and the risk level of the workstation with the greatest ergonomic factor. A greedy randomized adaptive search procedure (GRASP) procedure is proposed to achieve these two objectives simultaneously. This new procedure is compared against two mixed integer linear programs: the MILP-1 model that minimizes the maximum ergonomic risk of the assembly line and the MILP-2 model that minimizes the average deviation from ergonomic risks of the set of workstations on the line. The results from the case study based on the automotive sector indicate that the proposed GRASP procedure is a very competitive and promising tool for further research.Peer ReviewedPostprint (published version

Mixed integer linear programming models for minimizing ergonomic risk dispersion in an assembly line at the Nissan Barcelona factory

We present a variant of the approach to the assembly line balancing problems, with the aim of reducing the ergonomic risk for operators of mixed-model assembly lines (MILP-3). Specifically, the MILP-3 model is focused on minimizing the average range between ergonomic risk values of workstations. Using a case study from Nissan’s plant in Barcelona, not only are the differences between levels of ergonomic risk of stations reduced, but we attempt to reduce the average maximum ergonomic risk of the assembly line. The new model is compared with two others, MILP-1 and MILP-2, which minimize the average maximum ergonomic risk and the average absolute deviation of the risks, respectively.Postprint (published version

Combining simulation and optimization models on a production line problem: A case study

To improve the performance of a production line of a company of the Bosch Group, an optimization model was developed, which produces the optimum allocation of tasks to workstations and workers, according to a set of constraints. These results can thereafter be used in the simulation model, to estimate performance indicators, which would be difficult to estimate with other approaches, namely: waiting times, times spent with displacements and utilization rates. Thus, the purpose of this paper is twofold. First, it describes the combined use of the optimization and the simulation models. Thereafter, it presents the results obtained for 2 scenarios: one without displacements and another with displacements. The former was used to compare the simulation and the optimization models, whilst the later was used to assess the impact of displacements in the production line. By analyzing the results, it was possible to verify that the displacements increased the total time required to produce the devices in more than 10%. Furthermore, it was shown that the displacements caused considerable changes in the remaining performance indicators, indicating the relevance of considering them. This work also brings insights to the Industry 4.0 by proposing an approach to virtualize a production line system, providing the benefits of the 3D visualization of the simulation tool used in this research.This research was partially sponsored by the Portugal Incentive System for Research and Technological Development. Project in co-promotion nº 002814/2015 (iFACTORY 2015-2018) and has been partially supported by FCT –Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019

The ASALB problem with processing alternatives involving different tasks: definition, formalization and resolution

The Alternative Subgraphs Assembly Line Balancing Problem (ASALBP) considers assembly alternatives that determine task processing times and/or precedence relations among the tasks. Capacho and Pastor formalized this problem and developed a mathematical programming model (MILP) in which the assembly alternatives are determined by combining all available processing alternatives of each existing sub-assembly. In this paper an extended definition of the ASALBP is presented in which assembly subprocesses involving different tasks are also considered. Additionally, a mathematical programming model is proposed to formalize and solve the extended version of the ASALBP, which also improves the performance of the former MILP model. Some computational results are included.Peer Reviewe

An analysis of task assignment and cycle times when robots are added to human-operated assembly lines, using mathematical programming models

Abstract Adding robots to a human-operated assembly line influences both the short- and long-term operation of the line. However, the effects of robots on assembly line capacity and on cycle time can only be studied if appropriate task assignment models are available. This paper shows how traditional assembly line balancing models can be changed in order to determine the optimal number of workstations and cycle time when robots with different technological capabilities are able to perform a predetermined set of tasks. The mathematical programming models for the following three cases are presented and analysed: i) only workers are assigned to the workstations; ii) either a worker or a robot is assigned to a workstation; iii) a robot and a worker are also assigned to specific workstations. The data of an assembly line producing power inverters is used to illustrate the proposed calculations. Both the assignment of tasks and the changes of cycle time are analysed within the AIMMS modelling environment. The computational characteristics of the proposed mathematical programming models are also examined and tested using benchmark problems. The models presented in this paper can assist operations management in making decisions relating to assembly line configuration

A Methodology to Design and Balance Multiple Cell Manufacturing Systems

Manufacturing cell formation and its balance in just-in-time (JIT) type production environments have usually been studied separately in the literature. This practice is unrealistic since both problems interact and affect each other when the cells are operating. This chapter proposes a methodology to design multiple manufacturing cells and simultaneously balance their workload. The cells considered are U-shaped and process mixed models of product families. A nonlinear integer programming mathematical model is proposed, which integrates cell formation and their balancing, considering various production factors. For illustration, the method is applied to the redesign of a rack manufacturing process

Time and space multi-manned assembly line balancing problem using genetic algorithm

Purpose: Time and Space assembly line balancing problem (TSALBP) is the problem of balancing the line taking the area required by the task and to store the tools into consideration. This area is important to be considered to minimize unplanned traveling distance by the workers and consequently unplanned time waste. Although TSALBP is a realistic problem that express the real-life situation, and it became more practical to consider multi-manned assembly line to get better space utilization, few literatures addressed the problem of time and space in simple assembly line and only one in multi-manned assembly line. In this paper the problem of balancing bi-objective time and space multi-manned assembly line is proposed Design/methodology/approach: Hybrid genetic algorithm under time and space constraints besides assembly line conventional constraints is used to model this problem. The initial population is generated based on conventional assembly line heuristic added to random generations. The objective of this model is to minimize number of workers and number of stations. Findings: The results showed the effectiveness of the proposed model in solving multi-manned time and space assembly line problem. The proposed method gets better results in solving real-life Nissan problem compared to the literature. It is also found that there is a relationship between the variability of task time, maximum task time and cycle time on the solution of the problem. In some problem features it is more appropriate to solve the problem as simple assembly line than multi-manned assembly line. Originality/value: It is the first article to solve the problem of balancing multi-manned assembly line under time and area constraint using genetic algorithm. A relationship between the problem features and the solution is found according to it, the solution method (one sided or multi-manned) is definedPeer Reviewe