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1 – 10 of 383Mohammad Kamal Uddin, Marian Cavia Soto and Jose L. Martinez Lastra
Design, balancing, and sequencing are the key issues associated with assembly lines (ALs). The purpose of this paper is to identify AL design issues and to develop an integrated…
Abstract
Purpose
Design, balancing, and sequencing are the key issues associated with assembly lines (ALs). The purpose of this paper is to identify AL design issues and to develop an integrated methodology for mixed‐model assembly line balancing (MMALB) and sequencing. Primarily, mixed‐model lines are utilized for high‐variety, low‐volume job shop or batch production. Variation of a generic product is important for the manufacturers as the demand is mostly customer driven in the present global market.
Design/methodology/approach
Different AL design norms, performance indexes, and AL workstation indexes have been identified in the initial stage of this work. As the paper progresses, it has focused towards an integrated approach for MMALB and sequencing addressed for small‐ and medium‐scale assembly plants. A small‐scale practical problem has been justified with this integrated methodology implemented by MATLAB.
Findings
ALs execution in the production floor require many important factors to be considered. Different line orientations, production approaches, line characteristics, performance and workstation indexes, problem definitions, balancing and product sequencing in accordance with the objective functions are needed to be taken into account by the line designer.
Originality/value
This paper has highlighted the important AL design characteristics and also provided an integrated approach for balancing mixed‐model assembly lines (MMALs) combined with sequencing heuristic. The findings of this paper can be helpful for the designers while designing an AL. The integrated approach for balancing and sequencing of MMALs can be used as a functional tool for assembly‐based contemporary industries.
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Muhamad Magffierah Razali, Nur Hairunnisa Kamarudin, Mohd Fadzil Faisae Ab. Rashid and Ahmad Nasser Mohd Rose
This paper aims to review and discuss four aspects of mixed-model assembly line balancing (MMALB) problem mainly on the optimization angle. MMALB is a non-deterministic…
Abstract
Purpose
This paper aims to review and discuss four aspects of mixed-model assembly line balancing (MMALB) problem mainly on the optimization angle. MMALB is a non-deterministic polynomial-time hard problem which requires an effective algorithm for solution. This problem has attracted a number of research fields: manufacturing, mathematics and computer science.
Design/methodology/approach
This paper review 59 published research works on MMALB from indexed journal. The review includes MMALB problem varieties, optimization algorithm, objective function and constraints in the problem.
Findings
Based on research trend, this topic is still growing with the highest publication number observed in 2016 and 2017. The review indicated that the future research direction should focus on human factors and sustainable issues in the problem modeling. As the assembly cost becomes crucial, resource utilization in the assembly line should also be considered. Apart from that, the growth of new optimization algorithms is predicted to influence the MMALB optimization, which currently relies on well-established algorithms.
Originality/value
The originality of this paper is on the research trend in MMALB. It provides the future direction for the researchers in this field.
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Abdolreza Roshani and Farnaz Ghazi Nezami
This paper aims to study a generalized type of mixed-model assembly line with multi-manned workstations where multiple workers simultaneously perform different tasks on the same…
Abstract
Purpose
This paper aims to study a generalized type of mixed-model assembly line with multi-manned workstations where multiple workers simultaneously perform different tasks on the same product. This special kind of assembly line is usually utilized to assemble different models of large products, such as buses and trucks, on the same production line.
Design/methodology/approach
To solve the mixed-model multi-manned assembly line balancing problem optimally, a new mixed-integer-programming (MIP) model is presented. The proposed MIP model is nondeterministic polynomial-time (NP)-hard, and as a result, a simulated annealing (SA) algorithm is developed to find the optimal or near-optimal solution in a small amount of computation time.
Findings
The performance of the proposed algorithm is examined for several test problems in terms of solution quality and running time. The experimental results show that the proposed algorithm has a satisfactory performance from computational time efficiency and solution accuracy.
Originality/value
This research is the very first study that minimizes the number of workers and workstations simultaneously, with a higher priority set for the number of workers, in a mixed-model multi-manned assembly line setting using a novel MIP model and an SA algorithm.
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The purpose of this paper is to introduce robust optimization approaches to balance mixed model assembly lines with uncertain task times and daily model mix changes.
Abstract
Purpose
The purpose of this paper is to introduce robust optimization approaches to balance mixed model assembly lines with uncertain task times and daily model mix changes.
Design/methodology/approach
Scenario planning approach is used to represent the input data uncertainty in the decision model. Two kinds of robust criteria are provided: one is min‐max related; and the other is α‐worst scenario based. Corresponding optimization models are formulated, respectively. A genetic algorithm‐based robust optimization framework is designed. Comprehensive computational experiments are done to study the effect of these robust approaches.
Findings
With min‐max related robust criteria, the solutions can provide an optimal worst‐case hedge against uncertainties without a significant sacrifice in the long‐run performance; α‐worst scenario‐based criteria can generate flexible robust solutions: through rationally tuning the value of α, the decision maker can obtain a balance between robustness and conservatism of an assembly line task elements assignment.
Research limitations/implications
This paper is an attempt to robust mixed model assembly line balancing. Some more efficient and effective robust approaches – including robust criteria and optimization algorithms – may be designed in the future.
Practical implications
In an assembly line with significant uncertainty, the robust approaches proposed in this paper can hedge against the risk of poor system performance in bad scenarios.
Originality/value
Using robust optimization approaches to balance mixed model assembly line.
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Dongwook Kim, Dug Hee Moon and Ilkyeong Moon
The purpose of this paper is to present the process of balancing a mixed-model assembly line by incorporating unskilled temporary workers who enhance productivity. The authors…
Abstract
Purpose
The purpose of this paper is to present the process of balancing a mixed-model assembly line by incorporating unskilled temporary workers who enhance productivity. The authors develop three models to minimize the sum of the workstation costs and the labor costs of skilled and unskilled temporary workers, cycle time and potential work overloads.
Design/methodology/approach
This paper deals with the problem of designing an integrated mixed-model assembly line with the assignment of skilled and unskilled temporary workers. Three mathematical models are developed using integer linear programming and mixed integer linear programming. In addition, a hybrid genetic algorithm that minimizes total operation costs is developed.
Findings
Computational experiments demonstrate the superiority of the hybrid genetic algorithm over the mathematical model and reveal managerial insights. The experiments show the trade-off between the labor costs of unskilled temporary workers and the operation costs of workstations.
Originality/value
The developed models are based on practical features of a real-world problem, including simultaneous assignments of workers and precedence restrictions for tasks. Special genetic operators and heuristic algorithms are used to ensure the feasibility of solutions and make the hybrid genetic algorithm efficient. Through a case study, the authors demonstrated the validity of employing unskilled temporary workers in an assembly line.
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T.K. Bhattacharjee and S. Sahu
This paper briefly reviews the assembly line balancing techniques developed over the last 30 years. It attempts to establish the direction of research, to identify unexplored…
Abstract
This paper briefly reviews the assembly line balancing techniques developed over the last 30 years. It attempts to establish the direction of research, to identify unexplored areas with potential for study and recommends future courses of action.
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David Little and Andrew Hemmings
Today's market environment is characterized by an increasing demand for greater product variety. This has inevitably led to decreased product life cycle and forced volume…
Abstract
Today's market environment is characterized by an increasing demand for greater product variety. This has inevitably led to decreased product life cycle and forced volume manufacturers to consider switching from the mass production of a limited range of products to lower volume production of a wider range. This trend is observable in moves towards lean production within the car industry.
The purpose of this paper is to cut down energy consumption and eliminate production waste on mixed-model assembly lines. Therefore, a supermarket integrated dynamic cyclic…
Abstract
Purpose
The purpose of this paper is to cut down energy consumption and eliminate production waste on mixed-model assembly lines. Therefore, a supermarket integrated dynamic cyclic kitting system with the application of electric vehicles (EVs) is introduced. The system resorts to just-in-time (JIT) and segmented sub-line assignment strategies, with the objectives of minimizing line-side inventory and energy consumption.
Design/methodology/approach
Hybrid opposition-based learning and variable neighborhood search (HOVMQPSO), a multi-objective meta-heuristics algorithm based on quantum particle swarm optimization is proposed, which hybridizes opposition-based learning methodology as well as a variable neighborhood search mechanism. Such algorithm extends the search space and is capable of obtaining more high-quality solutions.
Findings
Computational experiments demonstrated the outstanding performance of HOVQMPSO in solving the proposed part-feeding problem over the two benchmark algorithms non-dominated sorting genetic algorithm-II and quantum-behaved multi-objective particle swarm optimization. Additionally, using modified real-life assembly data, case studies are carried out, which imply HOVQMPSO of having good stability and great competitiveness in scheduling problems.
Research limitations/implications
The feeding problem is based on static settings in a stable manufacturing system with determined material requirements, without considering the occurrence of uncertain incidents. Current study contributes to assembly line feeding with EV assignment and could be modified to allow cooperation between EVs.
Originality/value
The dynamic cyclic kitting problem with sub-line assignment applying EVs and supermarkets is solved by an innovative HOVMQPSO, providing both novel part-feeding strategy and effective intelligent algorithm for industrial engineering.
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This paper presents an analysis of the problem of Assembly Facility Assignment in a Mixed Model Assembly Line. Poisson arrivals and exponential service time distribution have been…
Abstract
This paper presents an analysis of the problem of Assembly Facility Assignment in a Mixed Model Assembly Line. Poisson arrivals and exponential service time distribution have been assumed. On the basis of the analysis presented it is possible to choose a particular facility on economic considerations, further, optimum service rate for such facilities has also been evaluated.
Confirmations are applied in kit preparation for mixed-model assembly to promote quality, but research that explains the impact on time efficiency has been lacking. The purpose of…
Abstract
Purpose
Confirmations are applied in kit preparation for mixed-model assembly to promote quality, but research that explains the impact on time efficiency has been lacking. The purpose of this paper is to determine the extent to which the type of confirmation method relates to time-efficient kit preparation when order batching is applied.
Design/methodology/approach
An industrially relevant laboratory experiment is applied, simulating kit preparation with order batching for mixed-model assembly. The time efficiency is studied as associated with four confirmation methods – barcode ring scanner, button presses, voice commands and RFID-reading wristbands – when applied as pick-from and place-to confirmation. Furthermore, the paper also considers the quality outcome.
Findings
Efficiency is promoted by methods that minimise interrupting the picker’s motions when performing pick-from confirmations and with methods that allow each hand to place components and perform place-to confirmations simultaneously – here represented by button presses and RFID-reading wristbands. Moreover, combining various methods for the tasks of pick-from or place-to confirmation can benefit efficiency.
Research limitations/implications
Pickers at an early stage of the learning curve (one shift of training) were considered.
Practical implications
The findings promote the customised applications of picking information systems in industry.
Social implications
Combining various methods for the tasks of pick-from and place-to confirmation can provide more fitting applications that better align with the picker’s preferences.
Originality/value
Combinations of various methods when applied as either pick-from or place-to confirmation, or both, are studied.
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