Parallel Workstations Research Articles

Modeling and Optimization of Parallel Disassembly Line Balancing Problem With Parallel Workstations

To reasonably arrange disassembly facilities and plan enterprise space, we propose a parallel disassembly line balancing problem (PW-PDLBP) with parallel workstations. Additionally, a mixed-integer non-linear programming (MINLP) model that minimizes the line length, number of workstations, idle time balancing index, and energy consumption is established based on the problem characteristics and is solved using the GUROBI optimizer. Furthermore, a multi-objective enhanced differential evolution algorithm (MEDE) is developed to obtain high-quality disassembly schemes for PW-PDLBP. The correctness of encoding and decoding and the solving performance of MEDE are verified by comparing with the MINLP model and four existing algorithms. Then, an instance consisting of two different types of end-of-life TVs is optimized. Finally, the effectiveness of PW-PDLBP in improving enterprise space utilization is validated by comparing it with the parallel line layout without parallel workstations.

Design model for assembly lines including fractional tasks and parallel workstations

In recent years, the use of robots and cobots allow to increase productivity and quality of products. Due to the higher investment, the robustness and efficiency of flow lines are crucial to reduce the throughput loss. The solution of installing buffers between stations increases costs and factory space. To improve the efficiency and robustness of assembly lines, the literature proposed some variants to the simple assembly line balancing problem. The introduction of fractional tasks and parallel workstations are two promising models proposed in recent works to reduce throughput loss caused by short failures. The potential of the two approaches has been studied individually, but no work has evaluated the integration of fractional and parallel tasks can further improve the efficiency of the production lines. This paper proposes a matheurstic method to design assembly lines integrating fractional tasks and parallel workstations. The approach proposed aims to reduce the computational complexity of the design of the assembly lines and provides a series of design alternatives. The simulation model tests the robustness of the design alternatives against short failures. The numerical results highlight how the proposed model improves the performance and the robustness of the assembly line when unforeseen events such as failures occur. The integration of fractional tasks and parallel tasks can improve the robustness against short failures. This benefit is relevant for robotic assembly lines, and the increasing use of cobots that are mainly used in the automotive, electronics sector, and metal machinery industries.

A Review on Assembly Line Balancing by Different Approaches

One of the oldest and most common production methods is the assembly line. The assembly line balancing issue is used to quickly build large numbers of a consistent product and is concerned with reducing the number of workstations, decreasing cycle time, increasing workload homogeneity, and increasing work cohesion. Assembly lines were initially created for the mass manufacture of standardized goods at a low cost. A production unit's assembly line consists of a number of employees and equipment. An assembly line is used in a manufacturing facility to produce components. During processing, the product travels along this line. For a flexible production system, assembly lines have changed over time from simple lines with a single model to mixed lines with numerous models, lines with parallel workstations, and U-shaped lines. Planning assembly lines for a system's primary goals includes balancing the assembly line according to the intended production volume each shift and reducing the number of workstations. Various assembly line balance issues (ALBP) have been researched and described in this study. Researchers can greatly benefit from the creation of a mathematical model to address the assembly line balance and scheduling issues.

Distributed assembly permutation flow-shop scheduling problem with non-identical factories and considering budget constraints

PurposeThis paper aims to address a distributed assembly permutation flow-shop scheduling problem (DAPFSP) considering budget constraints and factory eligibility. The first stage of the considered production system is composed of several non-identical factories with different technology levels and so the factories' performance is different in terms of processing time and cost. The second stage is an assembly stage wherein there are some parallel work stations to assemble the ready parts into the products. The objective function is to minimize the maximum completion time of products (makespan).Design/methodology/approachFirst, the problem is formulated as mixed-integer linear programing (MIP) model. In view of the nondeterministic polynomial (NP)-hard nature, three approximate algorithms are adopted based on variable neighborhood search (VNS) and the Johnsons' rule to solve the problem on the practical scales. The proposed algorithms are applied to solve some test instances in different sizes.FindingsComparison result to mathematical model validates the performance accuracy and efficiency of three proposed methods. In addition, the result demonstrated that the proposed two-level self-adaptive variable neighborhood search (TLSAVNS) algorithm outperforms the other two proposed methods. Moreover, the proposed model highlighted the effects of budget constraints and factory eligibility on the makespan. Supplementary analysis was presented by adjusting different amounts of the budget for controlling the makespan and total expected costs. The proposed solution approach can provide proper alternatives for managers to make a trade-off in different various situations.Originality/valueThe problem of distributed assembly permutation flow-shop scheduling is traditionally studied considering identical factories. However, processing factories as an important element in the supply chain use different technology levels in the real world. The current paper is the first study that investigates that problem under non-identical factories condition. In addition, the impact of different technology levels is investigated in terms of operational costs, quality levels and processing times.

Enhancing the labor division in the balancing of apparel assembly lines with parallel workstation through an improved ant colony algorithm

In order to overcome the inefficiency of labor division and management confusion in garment manufacturing assembly lines when introducing parallel workstations, an improved ant colony optimization (IACO) algorithm with multi-pheromones is proposed in this paper, which provides a new strategy to improve the match degree of operators and tasks in garment assembly line with parallel workstations. In proposed IACO, the first pheromone is set for ant to improve the efficiency of lines efficiency by balancing the workload allocation among workstations, and the second pheromone determines whether to create parallel workstations by valuing the complexity distribution of tasks. Existing real data of a garment manufacturing factory is used to verify the effective of IACO and the result shows that IACO contributes to a smooth work flow, and simultaneously reduce the efficiency loss of labor divisions (ELLD). Moreover, experiments are conduct to explore the trade-off relation between labor division and line arrangement efficiency when introducing parallel workstations. And based on the relation, strategies to create parallel workstations in the assembly line is provided for garment factories with different staff qualities for different apparel products.

New models and algorithms to solve integrated problems of production planning and control taking into account worker skills in flexible manufacturing systems

The paradigm of the cyber-physical manufacturing system is playing an increasingly important role in the development of production systems and management of manufacturing processes. This paper presents an optimization model for solving an integrated problem of production planning and manufacturing control. The goal is to create detailed production plans for a complex manufacturing system and to control the skilled manual workers. The detailed optimization model of the problem and the developed approach and algorithms are described in detail. To consider the impact of human workers performing the manufacturing primary operations, we elaborated an extended simulation-based procedure and new multi-criteria control algorithms that can manage varying availability constraints of parallel workstations, worker-dependent processing times, different product types and process plans. The effectiveness of the proposed algorithms is demonstrated by numerical results based on a case study.

Assembly line balancing with parallel workstations

ABSTRACT The simple assembly line balancing problem (SALBP) considers work division among different workstations of a serially arranged assembly process to maximise its efficiency under workload (cumulative) and technological (precedence) constraints. In this work, we consider a variant of the SALBP which allows parallel workstations. To study the effect of parallel stations, we propose a new problem (the parallel station assembly line balancing problem or PSALBP) in which the objective is to minimise the number of parallel stations required to obtain the maximum theoretical efficiency of the assembly process. We study the complexity of the problem and identify a polynomially solvable case. This result is then used as a building block for the development of a heuristic solution procedure. Finally, we carry out a computational experiment to identify the characteristics of assembly lines that may benefit from station paralleling and to evaluate the performance of the proposed heuristic.

Simultaneous Balancing and Scheduling of Order in a Supply Chain: A Goal Programming Approach

To sustain in this fiercely competitive era of industrial globalization, the manufacturers around the world are increasingly adopt a Supply Chain (SC) structures where the multiple production facilities are collaborating together to satisfy the demand. For such kind of SC network, to gratify the customer demand on time, it is an utmost need to ensures the balance and schedule the jobs within production facilities. But, due to the variation in their objectives, i.e. the balancing aims to increase the efficiency irrespective to the completion time and scheduling intend to decrease the make span regardless to the efficiency, it is often difficult to derive the optimal decisions simultaneously. Moreover, the realistic need for incorporating the parallel workstations and the zoning constraints paced by the extra-long task and technical restriction complicate this SC problem further. Even though, the goal programming model can be adopted in this regards as it has the capabilities of optimizing the conflicting objectives. However, till now such a model addressing the issues of station paralleling along with the simultaneous Balancing and Scheduling are rarely available in literature. Hence, in this work, by integrating the issue of resource paralleling, a goal programming model is offered to balance and schedule the jobs in supply chain simultaneously.

Improvement of Operational Performance through Value Stream Mapping and Yamazumi Chart: A case of Bangladeshi RMG Industry

To secure a competitive position in the global market, the Ready Made Garment (RMG) sector in Bangladesh has been facing various challenges including the improvement of industrial operational performance. Among the various operational issues, balancing the cycle time along the production line is felt to be a common and effective way for enhanced performance. There are numerous exact and approximate methods which have already been proposed and are available in literature for repetitive batch production. Unfortunately such approaches are rarely applied in the real RMG shop floor presumably due to the enormous efforts needed to align with the frequent changes of product lines. Compared to the exact and approximate methods, adoption of lean tools like VSM and Yamazumi chart is highly acclaimed for their simpler and wider applicability with superior capability in addressing and solving the balancing problems. So for balancing purposes of the RMG shop floor an attempt is made to frame and apply an integrated model combining the VSM and Yamazumi chart as presented in this article. Depending on the theoretical framework, operational performance of an RMG shop floor is evaluated upon balancing the cycle time. In doing so, firstly a current state map (CSM) and the corresponding Yamazumi chart are plotted to comprehend the existing operational procedure and analyse the workstation cycle time with respect to the takt time. Using the Yamazumi chart, the workstations are reorganized to reduce or eliminate the non-value added activities, to introduce parallel workstations, and to merge workstations so that a balanced production line is attained. Performance is then assessed by means of Overall Effectiveness of Equipment (OEE), Capacity Utilization and Efficiency. The results as obtained through testing a real life case study of RMG industry, ensure the effectiveness of the integrated system of VSM and Yamazumi chart to identify the wastes, restore the line balance and improve operational performance.

Parallel two-sided assembly line balancing with tools and tasks sharing

Purpose Parallel two-sided assembly lines are usually designed to produce large-sized products such as trucks and buses. In parallel two-sided assembly lines, both left and right sides of the line are used for manufacturing one or more products on two or more assembly lines located parallel to each other. The purpose of this paper is to develop a new mathematical model for the parallel two-sided assembly line balancing problem that helps to evaluate and validate the balancing operations of the machines such as removal of tools and fixtures and reallocating the operators. Design/methodology/approach The proposed approach is explained with the help of an example problem. In all, 22 test problems are formed using the benchmark problems P9, P12, P16 and P24. The results obtained are compared among approaches of the task(s) shared, tool(s) shared and both tool(s) and task(s) shared for effect on efficiency as the performance measure. The solution presented here follows the exact solution procedure that is solved by Lingo 16 solver. Findings Based on the experiments, line efficiency decreases when only tools are shared and increases when only tasks are shared. Results indicate that by sharing tasks and tools together, better line efficiency is obtained with less cost of tools and fixtures. Practical implications According to the industrial aspect, the result of the study can be beneficial for assembly of the products, where tools and tasks are shared between parallel workstations of two or more parallel lines. Originality/value According to the author’s best knowledge, this paper is the first to address the tools and tasks sharing between any pair of parallel workstations.

A review on mixed assembly line balancing, sequencing and scheduling in an industry

Assembly line in a production unit is a line of workers and machines. In a manufacturing unit the production of components are done on assembly line. The product moves along this line while it is being processed. The assembly lines changed with time from single models straight lines to the mixed, multi -model lines in a flexible manufacturing system and also lines with parallel work stations, U-shaped lines. The main objective of assembly line design for a system is balancing the assembly line according to the desired production volume per shift and minimizing the number of workstations. In this paper, different assembly line balancing problems (ALBP) have been reviewed and discussed. For solving the assembly line balancing and sequencing problems, the development of mathematical model may be quite helpful for the researchers.

Mixed-model U-shaped assembly lines: Balancing and comparing with straight lines with buffers and parallel workstations

In the paper a genetic algorithm approach is proposed to balance asynchronous mixed-model U-shaped lines with stochastic task times. U-shaped lines have become popular in recent years for their ability to outperform straight assembly lines in terms of line efficiency. The great majority of studies in the literature deal with paced synchronous U-shaped lines. Asynchronous lines can be more efficient than synchronous lines, but are more difficult to study, due to blocking and starvation phenomena caused by the variability of completion times: this makes it difficult to calculate the effective throughput. This variability, that in straight lines comes from the stochastic nature of task times and from the changing of models entering the line, is even higher in U-shaped lines, where an operator can work at two different models in the same cycle at the two sides of the line. For this reason, the genetic algorithm proposed is coupled to a parametric simulator for the evaluation of the objective function, which contains the simulated throughput. Two alternative chromosomal representations are tested on an ample set of instances from the literature. The best solutions are also compared with the best solutions known in the literature, on the same instances, for straight lines with buffers and parallel workstations. From the comparison it turns out that U-shaped lines are generally more efficient with respect to straight lines with buffers. This is because crossover work centers naturally act similarly to unitary buffers, providing two places in which two loads can be placed simultaneously. The superiority of U-shaped lines holds true as long as it is possible to take full advantage of the employment of crossover work centers. For particular types of instances, depending on the distribution of task times, this possibility decreases, so that straight lines with parallel workstations and buffers are preferable.

Multi-objective optimization algorithms for mixed model assembly line balancing problem with parallel workstations

AbstractThis paper deals with mixed model assembly line (MMAL) balancing problem of type-I. In MMALs several products are made on an assembly line while the similarity of these products is so high. As a result, it is possible to assemble several types of products simultaneously without any additional setup times. The problem has some particular features such as parallel workstations and precedence constraints in dynamic periods in which each period also effects on its next period. The research intends to reduce the number of workstations and maximize the workload smoothness between workstations. Dynamic periods are used to determine all variables in different periods to achieve efficient solutions. A non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO) are used to solve the problem. The proposed model is validated with GAMS software for small size problem and the performance of the foregoing algorithms is compared with each other based on some compariso...

Design of a Footwear Assembly Line Using Simulation-based ALNS

Competitive advantages of footwear manufacturing companies today lie in the ability to improve the efficiency and effectiveness of resource utilization through constantly eliminating wastes. This paper presents an innovative approach to designing a footwear assembly line with uncertain task times and parallel workstations. The measure defined to characterize the performance of the assembly line is Pair/Person/Hour (PPH). Two operational parameters, namely buffer size and the number of resources are taken into account. The objective is to maximize the performance measure of the assembly line by determining an optimized setting of the operational parameters and optimal task assignment. The solution approach utilizes Discrete Event Simulation (DES) to model the performance measure under consideration of process constraints and variability. An Adaptive Large Neighborhood Search (ALNS) heuristic is next developed and integrated into the simulation model to search for problem domain. A case study of an industrial footwear manufacturing factory is conducted to demonstrate the effectiveness of the proposed approach.

Optimization of Cycle Time in an Assembly Line Balancing Problem

Assembly line is a sequential work flow production systems which are still typical in the mass production of standard products. In mixed model assembly line system, it can produce the production sequentially by mixing more than one product on the same line. Different range of products are produced on the same line are quiet similar to the main productThis paper proposes an approach to the mixed model assembly line balancing problem (MALBP) with parallel workstations. Different methods are developed to solve assembly line balancing problems. The existing methods to solve assembly line balancing problem cannot be applied to combinatorial type problems. When we use heuristics methods for a combinatorial type problem which has more number of work elements, it may not give an optimal solution and become tedious. So this paper is aimed to propose a method to solve such type of complex line balancing problems.

컴퓨터 시뮬레이션을 이용한 병렬 대기행렬 시스템의 최적 서버 배치 방안

A queueing system with 2 parallel workstations is common in the field. Typically, the workstations have different features in terms of the inter arrival times of customers and the service times for the customers. Computer simulation study on the optimal server allocation for parallel heterogeneous queueing systems with fixed number of identical servers is presented in this paper. The queueing system is optimized with respect to minimizing the weighted system time of the customers served by 2 parallel workstations. The system time formula for the M/M/c systems in Kendall’s notation is known. Thus, we first compute the optimal allocation for parallel M/M/c systems, comparing the results with those from the computer simulation experiments, and have the same results. The CETI rule is devised through optimizing M/M/c cases, which allocates the servers based on Close or Equal Traffic Intensities between workstations. Traffic intensity is defined as the arrival rate divided by the service rate times the number of servers. The CETI rule is shown to work for M/G/c, G/M/c queueing systems by numerous computer simulation experiments, even if the rule cannot be proven analytically. However, the CETI rule is shown not to work for some of G/G/c systems.

Sensitivity-analysis based method in single-robot cells cost-effective design and optimization

Robot-centered cells play increasingly important roles in corporate automation and repetitive processing to improve productivity and quality. How to provide an optimal robotic cell design either from cost-effectiveness or from productivity enhancement is a highlighted objective, especially in 3C industry of communication, computer and consumer electronics where the cost is always sensitive. Although, in the past years, several optimizing solutions have been achieved, the robotic cell optimization is still an open question both in industry and academia, due to the diversities of cell patterns determined by some main factors as single/dual gripper, simple/parallel workstation, and so on. This work targets the optimization design of a single-robot cell from cost-effective viewpoint, by means of the sensitivity analysis, performed in terms of the processing time, the traveling time and the gripper configuration. It provides an indication on the relationship between the cell productivity and the main factors. By comparing the resulting increase in revenue with the additional equipment costs, it intuitively provides the optimal solution by considering the gripper type, and whether or how many parallel workstations are needed. A demonstration to enhance the productivity of a single-robotic cell from real-life engineering scenario is performed with an encouraging result. The paper considers the design of an economically efficient robotic cell, parallel workstations at each production stage, gripper type of the robot, and the layout, which affects the travel time of the robot.This proposed method is successfully employed in the real-life engineering cases by ABB engineers. Its effectiveness are fully demonstrated by these established engineering scenarios.

Simultaneous balancing and buffer allocation decisions for the design of mixed-model assembly lines with parallel workstations and stochastic task times

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.

A priority rule-based constructive heuristic and an improvement method for balancing assembly lines with parallel multi-manned workstations

Assembly lines of big-size products such as buses, trucks and helicopters are very different from the lines studied in the literature. These products’ manufacturing processes have a lot of tasks most of which have long task times. Since traditional assembly line models including only one worker in each station (i.e. simple assembly lines) or at most two workers (two-sided assembly lines) may not be suitable for manufacturing these type of products, they need much larger shop floor for a number of stations and long product flow times. In this study, an assembly line balancing problem (ALBP) with parallel multi-manned stations is considered. Following the problem definition, a mixed integer programming formulation is developed. A detailed study of priority rules for simple ALBPs is also presented, and a new efficient constructive heuristic algorithm based on priority rules is proposed. In order to improve solutions found by the constructive heuristic, a genetic algorithm-based solution procedure is also presented. Benchmark instances in the literature are solved by using the proposed mathematical programming formulation. It has been seen that only some of the small-size instances can be solved optimally by this way. So the efficiency of the proposed heuristic method is verified in small-size instances whose optimal solutions are found. For medium- and big-size instances, heuristics’ results and CPU times are demonstrated. A comparative evaluation with a branch and bound algorithm that can be found in the literature is also carried out, and results are presented.

Coupling a genetic algorithm approach and a discrete event simulator to design mixed-model un-paced assembly lines with parallel workstations and stochastic task times

In the paper, an innovative approach to deal with the Mixed Model Assembly Line Balancing Problem (MALBP) with stochastic task times and parallel workstations is presented. At the current stage of research, advances in solving realistic and complex assembly line balancing problem, as the one analyzed, are often limited by the poor capability to effectively evaluate the line throughput. Although algorithms are potentially able to consider many features of realistic problems and to effectively explore the solution space, a lack of precision in their objective function evaluation (which usually includes a performance parameter, as the throughput) limits in fact their capability to find good solutions. Traditionally, algorithms use indirect measures of throughput (such as workload smoothness), that are easy to calculate, but whose correlation with the throughput is often poor, especially when the complexity of the problem increases. Algorithms are thus substantially driven towards wrong objectives. The aim of this paper is to show how a decisive step forward can be done in this filed by coupling the most recent advances of simulation techniques with a genetic algorithm approach. A parametric simulator, developed under the event/object oriented paradigm, has been embedded in a genetic algorithm for the evaluation of the objective function, which contains the simulated throughput. The results of an ample simulation study, in which the proposed approach has been compared with other two traditional approaches from the literature, demonstrate that significant improvements are obtainable.