Parallel Assembly Lines Research Articles

Balancing parallel assembly lines with human-robot collaboration: problem definition, mathematical model and tabu search approach

Human-robot collaboration (HRC), as an emerging production mode, has garnered significant attention in the context of the growing smart manufacturing. This study aims to investigate the application of human-robot collaboration in parallel assembly lines and explore its potential for improving productivity, resource utilisation and flexibility. To the best of our knowledge, this is one of the first attempts to consider the combination of parallel assembly line balancing problem (PALBP) and human-robot collaboration. In this study, the parallel assembly line balancing problem with human-robot collaboration (PALBP-HRC) is introduced and characterised. The collaboration mode allows human workers and robots to execute tasks both in parallel and in collaboration. A mixed-integer programming model (MIP) that minimises the cycle time is formulated and a lower bound is proposed. Due to the NP-hardness, we develop an adapted tabu search (TS) algorithm specifically tailored for problem characterisation. Experimental results indicate that the proposed TS algorithm achieves competing performance compared to the MIP and other algorithms, including genetic algorithm (GA) and simulated annealing (SA) algorithm. The comparison between PALBP and PALBP-HRC demonstrates that the integration of human-robot collaboration to parallel assembly line can achieve significant improvements in efficiency and flexibility.

Heuristic and metaheuristic procedures for the Parallel Assembly Lines Balancing Problem with multi-line workstations and buffer sizing

This paper addresses the parallel assembly lines balancing problem (PALBP) with multi-line workstations, lines with different cycle times and buffer sizing. When a PALB system works with lines with different cycle times, the lines with multi-line workstations have to produce in batches; thus, the use of buffers may be needed. For the first time in the literature, this study jointly solved the PALBP and the buffer sizing problem (PALBP-B). Due to the multi-objective nature of the problem (minimising the number of workstations and the total buffer size in the multi-line workstations), several multi-objective heuristics and metaheuristics are proposed to solve the PALBP-B. Finally, an extensive computational experiment is carried out to analyse all the procedures presented.

An adaptive large neighborhood search algorithm for parallel assembly lines scheduling problem with complex fixture constraints

In recent years, the value chain facilitates the transition of competition among enterprises from a single link to a comprehensive one, thereby driving intelligent upgrades within manufacturing enterprises. The intelligent upgrading also imposes new constraints on the traditional assembly line production mode. Inspired by the real production practices of company L, a global intelligent terminal manufacturing enterprise headquartered in China, this study addresses the parallel heterogeneous assembly line scheduling problem with fixture constraints (HALSFC). To tackle this challenging problem, we propose a mixed integer linear programming (MILP) model that aims to maximize the number of completed work orders within a specified time. To our best knowledge, this study is among the first attempts to address the HALSFC problem with setups and related work orders. Due to the NP-hardness of the problem, we propose an improved adaptive large neighborhood search algorithm (IALNS) for solving HALSFC. We evaluate both model functionalities and algorithm effectiveness using instances generated based on the real production data of company L. Extensive experimental results demonstrate the effectiveness and efficiency of IALNS compared to MILP, Tabu search algorithm (TS) and genetic algorithm (GA), especially for medium- and large-scale instances. Additionally, the sensitivity analysis of the quality inspection time, the related work orders proportion and the minimum cooling time of fixtures is also conducted.

Modeling and balancing of parallel U-shaped assembly line based on improved genetic algorithms

Aiming at the improvement of the efficiency of the assembly line in the intelligent manufacturing field, a parallel U-shaped assembly line balancing problem (PUALBP) appears. In this paper, a mathematical model of the PUALBP-I is established, and an improved genetic algorithm (IGA) is innovatively designed based on the allocation strategy. Combined with 56 classic examples, the IGA is used to solve the mathematical models of SUAL and PUAL respectively, and the balance results and the balance effect evaluation indicators are obtained. The comparison with Parallel U-line Heuristic (PUH) shows that the results of PUAL are better than SUAL, and verifies that the IGA is effective. The results demonstrate that the IGA in calculating large-scale problems is superior to the small-scale problems, which provides a useful reference for solving PUALBP.

Managing inventory in customizable multi-echelon assembly systems

We consider a general assembly system that produces variations on a single product. Customers can choose to customize any aspect of the product which corresponds to one or more stages of the assembly system. We assume that demand for the original product and the demand for any customization at any stage are all random with known probability distributions. We model this problem as a multi-echelon inventory management problem. This problem has not been studied before. Allowing for customization at any stage in an assembly system makes this problem significantly more complex than similar problems considered in the past. To solve this problem, we ‘split' the assembly line into two parallel assembly lines which we call uncommitted and committed lines. We show that the usual method of reducing the assembly system to a series is not possible in general. We develop a heuristic policy which can be used to then reduce the system into a series system. We also present numerical calculations which highlight the efficacy of the heuristic policy.

Improved ant colony algorithm for the mixed-model parallel two-sided assembly lines balancing problem

ABSTRACT In response to the increasing demand for individualized products in the ‘small-lot, multi-variety’ market, there is an urgent need to enhance the efficiency and intelligence level of assembly lines. To address this, a novel solution method for the mixed-model parallel two-sided assembly lines balancing problem (MMPTSALBP) is proposed. The first step is to define the type and layout of the parallel two-sided assembly lines. Next, a mathematical model is constructed with the objective of minimizing the number of workstations required for the MMPTSALBP, proposing an improved ant colony algorithm that utilizes double string representation for the initial solution encoding method and a double pheromone matrix update to solve the model. Its efficiency is tested on benchmark datasets according to some performance measures and classifications. A study validates its effectiveness on 25 classical arithmetic cases by comparison with the solutions of an heuristic algorithm and an artificial fish swarm algorithm that had been reported to perform well.

A NEW MATHEMATICAL MODEL FOR PARALLEL ASSEMBLY LINE BALANCING PROBLEM WITH ERGONOMIC CONSTRAINTS: ERGOPALBP

Parallel assembly line (PAL) systems are one of the most preferred assembly line (AL) types for high volume and mass production in real-life applications. In the PALs, a parallel assembly line balancing problem (PALBP) is basically solved according to certain priority relations and task processing times. However, academic research generally does not take into account the ergonomic strains exposed by workers at stations. It would be a more accurate approach to consider ergonomic aspects in real-life PALBPs. In this study, the ergonomic-constrained PALBP (ergoPALBP) is discussed. Accordingly, the classical PALBP mathematical model is modified by adding ergonomic constraints. The mathematical model proposed for ergoPALBP has been implemented in a PAL system as a real-life application. Both ergonomic risk factors and total station operation times obtained with mathematical models used for classical PALBP and proposed for ergoPALBP were compared. According to the results obtained, the mathematical model proposed for the ergoPALBP shows a successful performance.

Heuristic and metaheuristic procedures for the buffer sizing problem in parallel assembly lines balancing problem with multi-line workstations and different cycle times

In the parallel assembly lines balancing problem (PALBP) there is the possibility that the operators can perform the tasks assigned to their multi-line workstation on two adjacent lines. As a result, the line efficiency can be increased. In a PALB system, the assembly lines can work with the same or different cycle times. In the latter case, the lines may produce in batches, and thus the use of buffers (existence and sizing) in multi-line workstations is needed. Exact procedures have been proposed to solve the buffer sizing problem (BSP) in a multi-line workstation, but only small-size instances can be solved in a viable computational time. The BSP is an unresolved problem for real-size instances. This paper presents the first non-exact procedures to solve real-size instances of the BSP in a multi-line workstation for a given set of tasks. The problem is detailed and described in the paper, and several heuristics and metaheuristic procedures are developed to solve it. Finally, several computational experiments are carried out to evaluate the procedures presented.

Improving the manufacturing process of kitchen furniture with a sustainable perspective

The concept of sustainability concerns the ability to satisfy current needs without compromising the possibility for future generations to satisfy their own needs. Over the years this concept turned out to be an essential theme for many industries because of a spread and heightened sensitivity towards environmental protection and social responsibility. Nevertheless, every firm still needs to guarantee the economic viability of its actions and retain its competitive advantage over competitors to remain in the market. This idea corresponds to the triple bottom line approach, according to which the business performance should be monitored from three perspectives, namely economic, environmental, and social. From one side sustainability means the integration of multiple practices, whereas on the other side, the current globalized and competitive economy requires enterprises to combine sustainability with practices of Industry 4.0 to contribute to Circular Economy objectives. The aim is to make choices that improve all three aspects. This work proposes an approach able to involve all three pillars of sustainability and the forefront tools to evaluate them. The case study presents the improvement of the manufacturing process for kitchen furniture. The aim was to create a smart working environment able to increase productivity and mitigate ergonomic risks ensuring a reduced environmental impact. Four parallel manual assembly lines were replaced with one semi-automated line, in which some specific workstations can adapt the product position to the operator's anthropometric measures. The re-design of the workplace allowed both the reduction of out-of-quality pieces and the enhancement of worker well-being. The main results show the achieved optimization for each pillar.

Parallel assembly lines worker assignment and balancing problem: A mathematical model and an artificial bee colony algorithm

In today’s competitive world, assembly lines are one of the most important industrial manufacturing systems, which can accommodate the massive increase in customer demands and product range, for the production industry. One possible way to increase the capacity and efficiency of assembly lines is to design a parallel assembly line system, consisting of two or more assembly lines placed next to each other. In the literature, the assembly lines are usually balanced according to tasks with fixed processing times without considering worker–task compatibility. In real-life applications, however, since the processing time of each task may vary according to the capability of each worker, the assignment of tasks to stations in the assembly line depends on the skills of the worker assigned to the related station. Considering the worker and task assignments together for each assembly line will provide a more realistic perspective. This paper, to the best of our knowledge, is the first study that considers the minimization of joint cycle time for the worker assignment and assembly line balancing problem in parallel assembly lines (PALWABP-II). Accordingly, a binary linear mathematical programming (BLP) model is developed and an artificial bee colony (ABC)-based solution approach is proposed for medium and large-sized problems. A new set of test problems is presented to the literature for a computational experiment. In addition, a summary of the literature is presented. An example problem is solved using the BLP model. In order to evaluate the effectiveness of the proposed model and approach, they are compared with the classical particle swarm optimization (PSO) algorithm and ten different priority rules. The computational results on test problems prove the effectiveness of the proposed ABC algorithm for the PALWABP-II.

An Integrated Method for Solving the Two-Sided Assembly Line Balancing Problems

The problems of parallel two-sided assembly lines balancing (TALB) are nonpolynomial (NP-hard) problems that belong to the field of combinatorial optimization. In most cases, these problems can be resolved with algorithms. To this end, this research adopts colored Petri nets (CPN) and a minimal spanning tree (MST) to address the type I problems for two-sided assembly line balancing problem (TALBP). This research proposes a three-step method. In the first step, a reachability tree chart is built to show potential tasks order assignment. In the second step, the color firing mechanism is employed to determine if the colored conditions are satisfied. The final step uses a MST and a least-time prioritized rule to select the proper tasks for assignment efficiently. These steps will be performed repetitively until all the tasks are properly assigned. Since the whole assignment process is based on graphical and paradigm methods, it can be adopted to lessen the burdens of complex calculations. The end of the research will present the comparison results between the examples from the literature and the method proposed in this research. As indicated by the research findings, employing CPN and an MST for TALBPs (type-I) can obtain even favorable and consistent results over legacy methods, and further optimize workstation design and enhance balance efficiency.

Multi-objective optimization of cycle time and energy consumption in parallel robotic assembly lines using a discrete firefly algorithm

PurposeAssembly lines are one of the places where energy consumption is intensive in manufacturing enterprises. The use of robots in assembly lines not only increases productivity but also increases energy consumption and carbon emissions. The purpose of this paper is to minimize the cycle time and total energy consumption simultaneously in parallel robotic assembly lines (PRAL).Design/methodology/approachDue to the NP-hardness of the problem, A Pareto hybrid discrete firefly algorithm based on probability attraction (PHDFA-PA) is developed. The algorithm parameters are optimized using the Taguchi method. To evaluate the results of the algorithm, a multi-objective programming model and a restarted simulated annealing (RSA) algorithm are used.FindingsAccording to the comparative study, the PHDFA-PA has a competitive performance with the RSA. Thus, it is possible to achieve a sustainable PRAL through the proposed method by addressing the cycle time and total energy consumption simultaneously.Originality/valueTo the best knowledge of the authors, this is the first study addressing energy consumption in PRAL. The proposed method for PRAL is efficient in solving the multi-objective balancing problem.

Multi-objective parallel adjacent U-shaped assembly line balancing collaborated by robots and normal and disabled workers

This paper emphasises the parallel adjacent U-shaped assembly line balancing problem in which the collaborative work forces in the system comprise human workers and robots. Apart from normal workers, disabled workers are also hired to enable the company to enjoy corporate tax benefits from the government. Five objectives related to the system as a whole and another three interacting entities are optimised simultaneously. A mathematical model is formulated for the first time for this type of layout. Due to the NP-hard nature of the problem, a reference point based evolutionary algorithm, namely non-dominated sorting teaching-learning-based optimisation (NSTLBO III), is proposed to solve medium- and large-sized problems. The performances of NSTLBO III are benchmarked in the sense of Pareto efficiency with two well-known multi-objective evolutionary algorithms, i.e. non-dominated sorting genetic algorithm (NSGA III) and multi-objective evolutionary algorithm based on decomposition (MOEA/D). The experimental results show that NSTLBO III surpasses its contestants significantly concerning the convergence to the true Pareto front.

A Multi-criteria Production Planning Approach for Aircraft Manufacturing Flow Lines

We consider a two-stage low-volume manufacturing system motivated by settings found in the aerospace industry. The first stage is given by parallel mixed-model assembly lines. The second stage consists of parallel paint stations. The two stages are decoupled by a finite-capacity buffer. Jobs have to be assigned to the assembly lines and must be sequenced on the lines. Afterwards, they must be assigned to paint stations and have to be sequenced at these stations. The conflicting performance measures are the total weighted tardiness (TWT) of the jobs at the second stage, whereas labor and inventory costs are considered at the first stage. We are interested in determining the set of Pareto-optimal solutions. We propose a hybrid metaheuristic based on the non-dominated sorting genetic algorithm (NSGA)-II to tackle large-sized problem instances. Results of computational experiments based on randomly generated problem instances are presented. The results demonstrate that the hybrid heuristic is able to quickly compute high-quality solutions.

Parallel Assembly Line Balancing Model with Tooling Consideration and Demand Fulfilment (ALBPTD)

In this study, we propose a model that extends the assembly line balancing problem (ALBP) to consider parallel lines with tool requirements by task and demand fulfillment (ALBPTD). We develop an integer program to minimize the system's total cost including the variable operational and fixed costs associated with workstations and tooling. The proposed model investigates the best demand distribution among lines. To assess the model's performance, test data sets from the literature are employed with different problem sizes and precedence structures. The model performs well in terms of computational time for medium sized problems.

Balancing of parallel U-shaped assembly lines with a heuristic algorithm based on bidirectional priority values

Aiming at improving assembly line efficiency and flexibility, a balancing method of parallel U-shaped assembly line system is proposed. Based on the improved product priority diagram, the bidirectional priority value formula is obtained. Then, assembly lines are partitioned into z-q partitions and workstations are defined. After that, the mathematical model of the parallel U-shaped assembly line balancing problem is established. A heuristic algorithm based on bidirectional priority values is used to solve explanatory examples and test examples. It can be seen from the results and the effect indicators of the assembly line balancing problem that the heuristic algorithm is suitable for large balancing problems. The proposed method has higher calculation accuracy and shorter calculation time. The balancing effect of the parallel U-shaped assembly line is better than that of single U-shaped assembly line, which verifies the superiority of the parallel U-type assembly line and effectiveness of the proposed method. It provides a theoretical and practical reference for parallel U-type assembly line balancing problem.

A parameter tuned hybrid algorithm for solving flow shop scheduling problems with parallel assembly stages

In this paper, we study the scheduling problem for a customized production system consisting of a flow shop production line with a parallel assembly stage that produces various products in two stages. In the first stage of the production line, parts are produced using a flow shop production line, and in the second stage, products are assembled on one of the parallel assembly lines. The objective is to minimize the time required to complete all goods (makespan) using efficient scheduling. A mathematical model is developed; however, the model is NP-hard and cannot be solved in a reasonable amount of time. To solve this NP-hard problem, we propose two well-known metaheuristics and a hybrid algorithm. To calibrate and improve the performance of our algorithms, we employ the Taguchi method. We evaluate the performance of our hybrid algorithm with the two well-known methods of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) and demonstrate that our hybrid algorithm outperforms both the GA and PSO approaches in terms of efficiency.

Production planning with parallel lines and limited batch splitting: Mathematical model and a case study in the white goods sector

This paper addresses the optimization of production planning in the white goods sector, motivated by the real case of a home appliances manufacturer. The main characteristics of this productive process are multiple parallel assembly lines with distinct unrelated speeds that vary depending on product type; a tight limit on the maximum number of split batches; multiple product types that share different types of resources; and constraints on production capacity. For the company, it is important to consider all these characteristics in an integrated manner, which results in a complex decision-making process. To provide effective support to decision-making in this context, we propose an optimization model that seeks to meet the demand in the planning horizon considering all the mentioned characteristics, while minimizing the processing times and the number of split batches. The results of computational experiments with instances based on real data provided by the company showed that the proposed approach is effective and presents good quality solutions for the case study, suggesting significant productivity gains if put into practice. They indicate improvements in production times by up to 9.43% and reductions in batch splitting by approximately 55% with respect to the current operation of the company.

Parallel Assembly Line Balancing with Resource Dependent Task Times in Manufacturing of Solar Energy Collector

Bu çalışmada, Konya’da faaliyet gösteren ve güneş enerjisi kolektörü üreten bir firmanın montaj hatlarında kaynak bağımlı görev süreleri ile paralel montaj hattı dengeleme uygulaması yapılmıştır. Öncelikle ilgili firmanın montaj hattı tanıtılmış ve kaynak bağımlı görev süreleri ile hat dengeleme yaklaşımını kullanmanın son derece uygun olduğunu göstermek amacıyla montaj hattındaki görevlerin farklı kaynak alternatifleri ile farklı sürelerde tamamlanma seçenekleri ortaya koyulmuştur. Daha sonra, karar vericiler tarafından mevcut montaj hattı ile aynı özelliklere sahip ikinci bir montaj hattının kurulmasına karar verildiği ve yeni kurulacak hattın mevcut hatta paralel bir şekilde yerleştirilerek faaliyet göstereceğinden hareketle bahsi geçen bu iki montaj hattının paralel montaj hattı dengeleme yaklaşımı ile bütünleşik olarak dengelenmesi yapılmıştır. Uygulama sonucu, bahsi geçen firmanın montaj hatlarının, karar vericiler tarafından planlanan çevrim süresi değeri için kaynak bağımlı görev süreleriyle paralel hat dengeleme yaklaşımı kullanılarak bütünleşik olarak dengelenmesinin, hatların birbirinden bağımsız dengelenmesi durumuna kıyasla aylık toplam maliyette % 5,67 oranında bir iyileştirme sağladığı belirlenmiştir. Aynı hatların beş farklı çevrim süresi değeri için dengelenmesiyle yapılan senaryo analizinde de kaynak bağımlı görev süreleriyle paralel hat dengeleme yaklaşımının bağımsız dengeleme yaklaşımına göre toplam maliyeti iyileştirme oranları ortalaması % 8,09 olarak elde edilmiştir.

EXISTENCE AND SIZING OF BUFFERS IN PARALLEL ASSEMBLY LINES WITH MULTI-LINE WORKSTATIONS AND DIFFERENT CYCLE TIMES

ABSTRACT: Parallel Assembly Lines with multi-line stations (PALBs) have been widely studied in recent years because PALBs can help improve the efficiency of a production system. However, the need of buffers has not been considered in the PALBP literature. In this study, for the first time in the literature, it is shown and demonstrated the need to consider the use of buffers in this type of line when their cycle times are different. Moreover, the buffer sizing problem in a multi-line workstation is presented and formalized. It is shown that the sequencing and scheduling of the task influences the buffer size. Finally, the designed resolution method is shown: solve a mixed integer linear programming model with a commercial software, with the objective of minimizing the size of the buffers. Keywords: Parallel assembly lines balancing, buffer sizing, task sequencing and scheduling.