Analysis of the type II robotic mixed-model assembly line balancing problem (original) (raw)
Related papers
Stability radii of optimal assembly line balances with a fixed workstation set
International Journal of Production Economics, 2016
For an assembly line, it is required to minimize the line's cycle time for processing a partially ordered set of the assembly operations on a linearly ordered set of the workstations. The operation set is partitioned into two subsets, manual and automated. The durations of the manual operations are variable and those of the automated operations are fixed. We conduct a stability analysis for this problem. First, we derive a sufficient and necessary condition for the optimal line balance to have an infinitely large stability radius. Second, we derive formulas and an algorithm for calculating the stability radii for the optimal line balances. Third, we report computational results for the stability analysis of the benchmark instances. Finally, we outline managerial implications of the stability results for choosing most stable line balances, which save their optimality in spite of the variations of the operation durations, and for identifying the right time for the re-balancing of the assembly line.
The buffer allocation problem (BAP) and the assembly line balancing problem (ALBP) are amongst the most studied problems in the literature on production systems. However they have been so far approached separately, although they are closely interrelated. This paper for the first time considers these two problems simultaneously. An innovative approach, consisting in coupling the most recent advances of simulation techniques with a genetic algorithm approach, is presented to solve a very complex problem: the Mixed Model Assembly Line Balancing Problem (MALBP) with stochastic task times, parallel workstations, and buffers between workstations. An opportune chromosomal representation allows the solutions space to be explored very efficiently, varying simultaneously task assignments and buffer capacities among workstations. A parametric simulator has been used to calculate the objective function of each individual, evaluating at the same time the effect of task assignment and buffer allocation decisions on the line throughput. The results of extensive experimentation demonstrate that using buffers can improve line efficiency. Even when considering a cost per unit buffer space, it is often possible to find solutions that provide higher throughput than for the case without buffers, and at the same time have a lower design cost. Web-site: www.impianti.dii.unipg.it/tiacci -3 -provides single-model, paced line with fixed cycle time and deterministic task times. The SALBP can be classified with respect to the objective type: in 'type-1' problem one tries to minimize the number of stations for a given cycle time, while in 'type-2' problem one tries to minimize the cycle time for a given number of workstations. So usually the two basic objectives (performances and costs) of the problem are treated in a separate way, that is fixing one of the two as a constraint, and trying to optimize the other one. If both, number of stations and the cycle time, can be altered, the problem is of 'type E', i.e. the line efficiency E can be used to determine the quality of a balance. It is possible to maximize the line efficiency by simultaneously minimizing the cycle time and the number of workstations, for example through a unique objective function by applying objective-specific weighting factors. Real problems are much more complicated than the SALBP, and research has recently evolved towards formulating and solving generalized problems (namely Generalized Assembly Line Balancing Problem, GALBP) with different additional characteristics, such as cost functions, equipment selection, paralleling, stochastic task times and others. For a comprehensive classification of the possible features of the GALBP see and . The Mixed-model Assembly Line Balancing Problem (MALBP) can be seen as a particular case of the GALBP. Here a set of similar models, that are variations of the same base product and only differ in specific customizable product attributes, can be assembled simultaneously. Set-up times between models can be reduced sufficiently enough to be ignored . Studies published in the last years utilize different approaches to solve it, such as:
Balancing mixed-model assembly lines to reduce work overload
IIE Transactions, 2001
We propose a new line balancing approach for mixed-model assembly lines with an emphasis on how the assignment of tasks to stations aects the ability to construct daily sequences of jobs (customer orders) that provide stable workloads (in a minute-tominute sense) on the assembly line, while also achieving reasonable workload balance among the stations. The issue of short-term workload stability has received little attention in the assembly line balancing literature. Such stability allows assembly workers to complete their tasks without being rushed and thereby contributes to product quality. We propose a new objective for assembly line balancing that helps to achieve better short-term workload stability and develop a heuristic solution procedure based on ®ltered beam search for this new objective. Computational results show that for small problems (which can be solved optimally), this approach provides near optimal solutions, and for larger problems, it provides signi®cantly better results than traditional assembly line balancing methods. 0740-817X Ó 2001``IIE''
IJERT-Minimizing Number of Stations and Cycle Time for Mixed Model Assembly Line
International Journal of Engineering Research and Technology (IJERT), 2014
https://www.ijert.org/minimizing-number-of-stations-and-cycle-time-for-mixed-model-assembly-line https://www.ijert.org/research/minimizing-number-of-stations-and-cycle-time-for-mixed-model-assembly-line-IJERTV3IS081039.pdf Assembly Line Balancing is one of the widely used basic principles in production system. The problem of Assembly Line Balancing is distribution of activities among the workstations so that there will be maximum utilization of human resources and facilities without disturbing the work sequence. The specified objective for the work is to minimize number of stations and cycle time, subject to precedence constraints. In this work, the single model assembly line problem or equivalent model of multi model assembly line problem are solved for minimum number of stations and minimum cycle time. The work carried has the objective to minimize cycle time and the work stations. For deriving the minimize number of stations and cycle time the method is divided into two stages.1) Optimize the number of work stations. 2) Optimize the cycle time. The problem is chosen based on the presence of complexity and the number of models that are assembled on the line. This is a seat fabrication and assembly and has 28 activities for 04 different models.
Binary integer formulation for mixed-model assembly line balancing problem
Computers & industrial engineering, 1998
Assembly line balancing problem 453 (a) (b) (c) Fig. 1. Precedence diagrams of (a) model 1, (b) model 2 and (c) combined. matrix with an abth entry of 1 if the processing of task b requires the completion of task a. (Dtnerwjse, ine entry'jszero. 7Ъеpreceòencematrix dì ine ...
Mixed model assembly line balancing problem under uncertainty
… , 2009. CIE 2009. …, 2009
A common assumption in the literature on mixed model assembly line balancing problem is that the task duration is known and deterministic but may differ among various models. In this paper, we present a robust optimization formulation for dealing with task duration uncertainty in a mixed model assembly line balancing problem (RMALB-P) in which task duration can vary in a specific range. RMALB-P is aim to minimize the sum of costs of the stations and the task duplication. Task duplication means that a task which is common to multiple tasks can be assigned to different stations for different models. Finally, RMALB-P is solved optimally and implemented in mixed model assembly lines of IRAN KHODRO Company. The results are compared with the previous existing balance to show the effects of the data uncertainties on the performance of assembly line outputs. The results indicate that the robust balancing approach can be a relatively more reliable method for balancing the mixed model assembly lines.
Stability radius of the optimal assembly line balance with fixed cycle time
We address the simple assembly line balancing problem: Minimize the number of stations m for processing n partially ordered operations V={1, 2, ..., n} within the given cycle time c. The processing time ti is given for each operation iV but cannot be changed only for the operations from the subset of automated and semi-automated operations Ṽ \ V . If Ṽ \ V i , then operation time ti is strictly positive real number, which is fixed during the life cycle of the assembly line. Subset Ṽ of set V includes manual operations, for which it is hard or even impossible to fix processing time for the whole life cycle of the assembly line. We assume that if Ṽ j
A comparison of formulations for the simple assembly line balancing problem
2011
Abstract: Assembly line balancing is a well-known problem in operations research. It consists in finding an assignment of tasks to some arrangement of stations where the tasks are executed. Typical objective functions require to minimize the cycle time for a given number of stations or the number of stations for a given cycle time.
Robust balancing of straight assembly lines with interval task times [star]
This paper addresses the balancing problem for straight assembly lines where task times are not known exactly but given by intervals of their possible values. The objective is to assign the tasks to workstations minimizing the number of workstations while respecting precedence and cycle time constraints. An adaptable robust optimization model is proposed to hedge against the worst-case scenario for task times. To find the optimal solution(s), a breadth first search procedure is developed and evaluated on benchmark instances. The results obtained are analyzed and some practical recommendations are given.
Stability analysis of an optimal balance for an assembly line with fixed cycle time
European Journal of Operational Research, 2006
We address the simple assembly line balancing problem: minimize the number of stations m for processing n partially ordered operations V = {1, 2, . . ., n} within the cycle time c. The processing time t i of operation i 2 V and cycle time c are given. However, during the life cycle of the assembly line the values t i are definitely fixed only for the subset of automated operations V n e V . Another subset e V V includes manual operations, for which it is impossible to fix the exact processing times during the whole life cycle of the assembly line. If j 2 e V , then operation time t j can be different for different cycles of production process. For the optimal line balance b of a paced assembly line with vector t = (t 1 , t 2 , . . ., t n ) of the operation times, we investigate stability of its optimality with respect to possible variations of the processing times t j of the manual operations j 2 e V . In particular, we derive necessary and sufficient conditions when optimality of the line balance b is stable with respect to sufficiently small variations of the operation times t j , j 2 e V . We show how to calculate the maximal value of independent variations of the processing times of all the manual operations, which definitely keep the feasibility and optimality of the line balance b.