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

A CASE STUDY ON IMPROVING THE PRODUCTIVITY USING IE TOOLS

Assembly line balancing has been a focus of interest in Industrial Engineering for the last few years. Assembly line balancing is the problem of assigning tasks to workstations by optimizing a performance measure while satisfying precedence relations between tasks and cycle time restrictions. Line balancing is an important feature in ensuring that a production line is efficient and producing at its optimum. The process of Line balancing attempts to equalize the work load on each workstation of the production line. Mixed model assembly lines are increasing in many industries to achieve the higher production rate. This study deals with mixed-model assembly line balancing and uses Yamazumi chart to break down the work element in to the value added & Non-value added part to reduce the waste & increase the productivity

TYPE-I ASSEMBLY LINE BALANCING WITH WORKLOAD SMOOTHING

Balancing the assembly lines plays an important role in increasing the productivity of the manufacturing systems. Depending on the objectives, there are various types of this problem. In this study, a Type-1 assembly line balancing problem is considered. It is known that the distribution of workload and equal distribution of idle time in station balancing is important for worker motivation and ergonomics. Once the number of stations is minimized, which is the primary objective in solving a Type-1 problem, the optimum solution found should be analyzed in terms of the smoothness index. Otherwise, the idle time can be distributed unevenly to the stations. Hence, one of the classical problems in assembly line balancing literature, Sawyer problem, is considered in this study. Firstly, the problem is solved via integer programming with Gurobi in Python. In the second stage, the line was smoothed via two techniques including the classical one and the proposed min-max approach. Different cycle times are tested and a comparison is provided for the two techniques

Delimiting the linear area on the problems of assembly line balancing with minimal ergonomic risk

In this paper we propose to incorporate some working conditions to the assembly lines. For this, used a mathematical model to solve the assembly line balancing problem whose objective is minimizing the ergonomic risk, imposing the limitation of the cycle time, number of workstations and the maximum linear area for each station. A study is presented through a case study that corresponds to an assembly line from Nissan’s plant in Barcelona.Postprint (published version

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

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

Profit-oriented disassembly-line balancing

As product and material recovery has gained importance, disassembly volumes have increased, justifying construction of disassembly lines similar to assembly lines. Recent research on disassembly lines has focused on complete disassembly. Unlike assembly, the current industry practice involves partial disassembly with profit-maximization or cost-minimization objectives. Another difference between assembly and disassembly is that disassembly involves additional precedence relations among tasks due to processing alternatives or physical restrictions. In this study, we define and solve the profit-oriented partial disassembly-line balancing problem. We first characterize different types of precedence relations in disassembly and propose a new representation scheme that encompasses all these types. We then develop the first mixed integer programming formulation for the partial disassembly-line balancing problem, which simultaneously determines (1) the parts whose demand is to be fulfilled to generate revenue, (2) the tasks that will release the selected parts under task and station costs, (3) the number of stations that will be opened, (4) the cycle time, and (5) the balance of the disassembly line, i.e. the feasible assignment of selected tasks to stations such that various types of precedence relations are satisfied. We propose a lower and upper-bounding scheme based on linear programming relaxation of the formulation. Computational results show that our approach provides near optimal solutions for small problems and is capable of solving larger problems with up to 320 disassembly tasks in reasonable time

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

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Program Komputasi Ranked Positional Weight Untuk Keseimbangan Lintasan Perakitan

Assembly line balancing (ALBP) is a problem that often occurs in industrial engineering as part of the NP-hard combinatorial optimization problem. Which means no one can guarantee the optimal solution in solving the problems. ALBP used to solve balance optimization problem with a series of elements that are assigned to work in a particular station by the restrictions that have been set. Input needed to obtain optimal results include work element, cycle time, process time for each work element and number of predecessors. These data are needed in large number for the implementation in the real world and is not recommended to do calculations manually because it required long time. This paper implements one of line balancing algorithm i.e. Ranked Positional Weight (RPW) designed using Java programming language. The program can read a maximum of 50 work elements and a maximum of 3 predecessors for each element executed with 3 different times. The results will be the optimum number of work stations, work elements assigned to each station and line balance efficiency for each different cycle time