Mixed-model parallel two-sided assembly line balancing problem: A flexible agent-based ant colony optimization approach

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Assembly lines are frequently used as a production method to assemble complex products. Two-sided assembly lines are utilized to assemble large-sized products (e.g., cars, buses, trucks). Locating two lines in parallel helps improve line efficiency by enabling collaboration between the line workers. This paper proposes a mixed-model parallel two-sided assembly line system that can be utilized to produce large-sized items in an inter-mixed sequence. The mixed-model parallel two-sided line balancing problem is defined and the advantages of utilizing multi-line stations across the lines are discussed. A flexible agent-based ant colony optimization algorithm is developed to solve the problem and a numerical example is given to explain the method systematically. The proposed algorithm builds flexible balancing solutions suitable for any model sequence launched. The dynamically changing workloads of workstations (based on specific product models during the production process) are also explored. A comprehensive experimental study is conducted and the results are statistically analyzed using the well-known paired sample t-test. The test results indicate that the mixed-model parallel two-sided assembly line system reduces the workforce need in comparison with separately balanced mixed-model two-sided lines. It is also shown that the proposed algorithm outperforms the tabu search algorithm and six heuristics often used in the assembly line balancing domain

On applications of ant colony optimisation techniques in solving assembly line balancing problems

PublishedArticleRecently, there is an increasing interest in applications of meta-heuristic approaches in solving various engineering problems. Meta-heuristics help both academics and practitioners to get not only feasible but also near optimal solutions where obtaining a solution for the relevant problem is not possible in a reasonable time using traditional optimisation techniques. Ant colony optimisation algorithm is inspired from the collective behaviour of ants and one of the most efficient meta-heuristics in solving combinatorial optimisation problems. One of the main application areas of ant colony optimisation algorithm is assembly line balancing problem. In this paper, we first give the running principle of ant colony optimisation algorithm and then review the applications of ant colony optimisation based algorithms on assembly line balancing problems in the literature. Strengths and weaknesses of proposed algorithms to solve various problem types in the literature have also been discussed in this research. The main aim is to lead new researches in this domain and spread the application areas of ant colony optimisation techniques in various aspects of line balancing problems. Existing researches in the literature indicate that ant colony optimisation methodology has a promising solution performance to solve line balancing problems especially when integrated with other heuristic and/or meta-heuristic methodologies

Balancing of mixed-model parallel U-shaped assembly lines considering model sequences

This is the author accepted manuscript. The final version is available from Taylor & Francis via the DOI in this record.As a consequence of increasing interests in customised products, mixed-model lines have become the most significant components of today’s manufacturing systems to meet surging consumer demand. Also, U-shaped assembly lines have been shown as the intelligent way of producing homogeneous products in large quantities by reducing the workforce need thanks to the crossover workstations. As an innovative idea, we address the mixed-model parallel U-shaped assembly line design which combines the flexibility of mixed-model lines with the efficiency of U-shaped lines and parallel lines. The multi-line stations utilised in between two adjacent lines provide extra efficiency with the opportunity of assigning tasks into workstations in different combinations. The new line configuration is defined and characterised in details and its advantages are explained. A heuristic solution approach is proposed for solving the problem. The proposed approach considers the model sequences on the lines and seeks efficient balancing solutions for their different combinations. An explanatory example is also provided to show the sophisticated structure of the studied problem and explain the running mechanism of the proposed approach. The results of the experimental tests and their statistical analysis indicated that the proposed line design requires fewer number of workstations in comparison with independently balanced mixed-model U-lines

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

Optimising the process parameters of selective laser melting for the fabrication of Ti6Al4V alloy

This is the author accepted manuscript. The final version is available from Emerald via the DOI in this recordPurpose- Surface roughness is an important evaluation index for industrial components and it strongly depends on the processing parameters for selective laser molten Ti6Al4V parts. This paper aims to obtain an optimum SLM parameter set to improve the surface roughness of Ti6Al4V samples. Design/methodology/approach- A response surface methodology (RSM) based approach is proposed to improve the surface quality of selective laser molten Ti6Al4V parts and understand the relationship between the selective laser melting (SLM) process parameters and the surface roughness. The main SLM parameters (i.e. laser power, scan speed and hatch spacing) are optimised and Ti6Al4V parts are manufactured by the SLM technology with no post processes. Findings- Optimum process parameters were obtained using the RSM method to minimise the roughness of the top and vertical side surfaces. Obtained parameter sets were evaluated based on their productivity and surface quality performance. The validation tests have been performed and the results verified the effectivity of the proposed technique. It was also shown that the top and vertical sides must be handled together to obtain better top surface quality. Practical implications- The obtained optimum SLM parameter set can be used in the manufacturing of Ti6Al4V components with high surface roughness requirement. Originality/value- RSM is used to analyse and determine the optimal combination of SLM parameters with the aim of improving the surface roughness quality of Ti6Al4V components, for the first time in the literature. Also, this is the first study which aims to simultaneously optimise the surface quality of top and vertical sides of titanium alloys.This research was supported by the National High Technology Research and Development Program of China (863 Program: 2015AA042501)

A dynamic order acceptance and scheduling approach for additive manufacturing on-demand production

This is the final version. Available on open access from Springer Verlag via the DOI in this recordAdditive manufacturing (AM), also known as 3D printing, has been called a disruptive technology as it enables the direct production of physical objects from digital designs and allows private and industrial users to design and produce their own goods enhancing the idea of the rise of the “prosumer”. It has been predicted that, by 2030, a significant number of small and medium enterprises will share industry-specific AM production resources to achieve higher machine utilization. The decision-making on the order acceptance and scheduling (OAS) in AM production, particularly with powder bed fusion (PBF) systems, will play a crucial role in dealing with on-demand production orders. This paper introduces the dynamic OAS problem in on-demand production with PBF systems and aims to provide an approach for manufacturers to make decisions simultaneously on the acceptance and scheduling of dynamic incoming orders to maximize the average profit-per-unit-time during the whole makespan. This problem is strongly NP hard and extremely complicated where multiple interactional subproblems, including bin packing, batch processing, dynamic scheduling, and decision-making, need to be taken into account simultaneously. Therefore, a strategy-based metaheuristic decision-making approach is proposed to solve the problem and the performance of different strategy sets is investigated through a comprehensive experimental study. The experimental results indicated that it is practicable to obtain promising profitability with the proposed metaheuristic approach by applying a properly designed decision-making strategy.National High Technology Research and Development Program of Chin

An Improved Ant Colony Optimisation Algorithm for Type-I Parallel Two-Sided Assembly Line Balancing Problem

Publishedn/aThe first author wishes to thank the Balikesir University and University of Exeter for their financial supports

Data for: MILP models to minimise makespan in additive manufacturing machine scheduling problems

Test data used for the computational experiments of the following paper:MILP models to minimise makespan in additive manufacturing machine scheduling problems Ibrahim KucukkocComputers & Operations Research (under review

U-shaped disassembly line balancing problem: Mixed-integer programming models and artificial bee colony algorithm

The detailed results of the paper entitled "U-shaped disassembly line balancing problem: Mixed-integer programming models and artificial bee colony algorithm&quot

Data for: MILP models to minimise makespan in additive manufacturing machine scheduling problems

Test data used for the computational experiments of the following paper:MILP models to minimise makespan in additive manufacturing machine scheduling problems Ibrahim KucukkocComputers & Operations Research (under review)THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV