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

The application of robotic U-shaped line layouts is becoming more important for manufacturing companies. Compared to straight assembly line layouts, U-shaped assembly lines result in cost savings, easier material handling and higher production rates. The reason for this is that U-shaped lines improve visibility and skill sharing between operators, increase production quality, reduce work in process inventory and facilitate problem-solving of appearing production failures which is shown in several researches. Key companies such as Toyota and Boeing are using U-shaped assembly lines to benefit from the advantages of U-shaped line layouts. However, few breakdowns are common. Breakdowns reduce the throughput rate and product quality and therefore strategies are needed which can ensure the targeted throughput and product quality of companies during breakdowns. In this thesis a breakdown strategy IS designed for a robotic U-shaped line which uses versatile backup robots on backup stations to cover the failures of workstation robots. Versatile backup robots are only considered in one prior study for a straight line layout and, in that study, the backup robots demonstrated a better performance than other breakdown strategies used for straight lines. The concept of backup stations with versatile robots is adapted to the robotic U-shaped line layout to identify whether backup robots can be an efficient breakdown strategy for robotic U-shaped lines. This adaptation is the placement of the backup stations between the arms of the U-shaped line layout. An automotive body shop assembly line configuration is selected for the U-shaped line layout. Ten workstations are used in the line configuration. Four positions exist for the placement of backup stations. Each combination of workstations and placement positions have been analyzed to find the most efficient backup strategy for line configuration designed. The analysis starts with the one backup station, then considers two backup stations and finally three backup stations on the four possible placement options. The best option of the one, two and three backup stations are compared with four backup stations and the current breakdown strategies which are the usage of manual repair stations only and the workload reallocation of broken robots by working robots downstream the line. The criteria for the performance comparison are the cycle time and product quality which are generated for a 5%, 10% and 15%-line breakdown. For the generation of the criteria, a genetic algorithm is used which is modified from a straight line layout to the robotic U-shaped line backup

ABSTRACTThe solution to the assembly line balancing with the hierarchical worker assignment problem (ALBHWP) provides the optimal allocation of workers and tasks to the stations that minimise the total worker cost. In the ALBHWP, tasks differ in terms of the qualification requirements of workers, and the qualification levels of workers are hierarchical. In the hierarchical workforce structure, a lower qualified worker can be replaced by higher qualified ones with higher costs, while the vice versa is not applicable. This problem has only been studied for straight assembly lines so far. In this paper, we introduce the ALBHWP for U-shaped assembly lines. We developed integer and constraint programming models for solving the ALBHWP and compared their effectiveness using an extensive set of benchmark instances. We solved the ALBHWP for straight and U-shaped assembly lines comparatively. Constraint programming models have been statistically proven to provide better quality solutions faster than integer programming models. Besides, the CP model outperforms the only available metaheuristic in the literature for the S-ALBHWP in almost all problem sizes. Another observation is that a U-shaped line design is more cost-effective than a straight line design, but solving the ALBHWP for U-shaped lines is more difficult regarding computational complexity.

Event and object oriented simulation to fast evaluate operational objectives of mixed model assembly lines problems

The basic assumption of assembly line balancing is that every task's time is fixed. However, in practice, different processing alternatives may be available to process a task with different times. The problem in this case is to assign tasks and resources to work stations that minimise total cost and so-called resource dependent assembly line balancing (RDALB) in the literature. This study proposes a new integer programming formulation for RDALB. This formulation is then modified to develop a formulation for RDULB problem in U-shaped assembly lines. To the best knowledge of the authors, this study is the first RDULB study and the developed formulation is the first RDULB formulation. The proposed formulations are illustrated and validated using several examples. An experimental analysis is also conducted to examine the percent improvement in total cost when the line layout is switched into the U-shaped from the straight line shape. Experimental results show that an improvement in total operating cost is obtained when the straight line is switched into the U-shaped line configuration. Results also show that percentage improvement in total operating cost is significantly greater for problem instances having a large number of tasks and having greater values for the strength of the precedence relationships among tasks.

Balancing of parallel U-shaped assembly lines

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

A survey on problems and methods in generalized assembly line balancing

This research focuses on simulation-based assembly line balancing by investigating three configurations in U-shaped assembly lines. The names of the three layouts are U-shaped lines, parallel U-shaped lines (PUL), and parallel adjacent U-shaped lines (PAUL). Since PUL and PAUL were proposed with limited implementations, this study adopts secondary data from a real case industry and models the selected layouts using ARENA simulation. Simulation results are utilized to compare the performances of the three layouts in terms of the number of workstations, line efficiency, and workload smoothness. Some tradeoffs are observed and discussed for the layouts and the selected KPIs. The results show that PAUL outperforms the U-shaped and PUL, but its average waiting time increases due to the least number of operators. Also, the total outputs lower as the cycle time increases. PAUL is a promising layout for improvement and implementation.

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.

The recent Industry 4.0 trend, followed by the technological advancement of collaborative robots, has urged many industries to shift towards new types of assembly lines with human-robot collaboration (HRC). This type of manufacturing line, in which human skill is supported by robot agility, demands an integrated balancing and scheduling of tasks and operators among the stations. This study attempts to deal with these joint problems in the straight and U-shaped assembly lines while considering different objectives, namely, the number of stations (Type-1), the cycle time (Type-2), and the cost of stations, operators, and robot energy consumption (Type-rw). The latter type often arises in the real world, where multiple types of humans and robots with different skills and energy levels can perform the assembly tasks collaboratively or in parallel at stations. Additionally, practical constraints, namely robot tool changes, zoning, and technological requirements, are considered in Type-rw. Accordingly, different mixed-integer linear programming (MILP) models for straight and U-shaped layouts are proposed with efficient lower and upper bounds for each objective. The computational results validate the efficiency of the proposed MILP model with bounded objectives while addressing an application case and different test problem sizes. In addition, the analysis of results shows that the U-shaped layout offers greater flexibility than the straight line, leading to more efficient solutions for JIT production, particularly in objective Type-2 followed by Type-rw and Type-1. Moreover, the U-shaped lines featuring a high HRC level can further enhance the achievement of desired objectives compared to the straight lines with no or limited HRC.

Integration of balancing and preventive maintenance in straight and U-shaped resource-dependent assembly lines: MILP model and memetic algorithm

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.

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

U-shaped lines are considered to have a number of advantages over traditional lines. COMSOAL is a recurrent procedure for assembly lines balancing, and it stands for computer method for sequencing operations for assembly lines. In this paper, an improved U-COMSOAL is proposed to solve some problems of COMSOAL, the random picking part of the COMSOAL method is substituted by a ranked positional weight method, and takes both the predecessors and successors of the tasks into the account. Finally, a comparison of between the improved method and a classical method suggested by Ö. F. Baykoç was done, which illustrate the efficiency of U-COMSOAL.

Many assembly lines in industries are now being designed as the U-shaped assembly line balancing (UALB) due to pressures of just-in-time manufacturing. Once compared to the straight assembly line balancing (SALB), it has better balancing, improved communication, fewer workstations, and more flexibility for adjustment. This paper proposes a hybrid intelligent approach to solve such the UALB problems. The TSGA method consisting of the tabu search (TS) and the genetic algorithm (GA) is used to identify solutions for the UALB problems. The multiple objectives including the workload variance, the idle time, and the line efficiency, are proposed and set as the objective function of search process. With the proposed approach, the TS can well address the number of tasks assigned for each workstation of the U-shaped line, while the GA can also assign the sequence of tasks for each workstation according to precedence constraints. The proposed approach is tested against three UALB problems from a survey of literature. Obtained results are compared with results obtained from the single-objective approach. As results, the proposed multiple-objective approach based on the TSGA method gives better solutions for all UALB problems.