Balancing U-shaped assembly lines by considering worker performance

Assembly lines are flow-oriented mass production systems where the productive units or stations perform the operations. An assembly line consists of a sequence of m stations through which the product units proceed. Each station performs a subset of the n operations necessary for manufacturing the products. Assembly lines have been used for faster, cheaper, more quality and more production in industrial systems. Therefore, assembly line balancing is a very important production planning activity for the production systems. The design of an assembly line requires tasks to be grouped into stations such that the precedence relations among the tasks are satisfied and some performance measures are optimized. This problem is known as Assembly Line Balancing Problem (ALBP). Generally, in ALBP studies, there are a lot of assumptions for simplifying the solution of the problem. As a result of several simplifying assumptions, this problem was called Simple Assembly Line Balancing Problem (SALBP) (Baybars, 1986). Traditionally assembly lines are arranged in a straight line. However, the implementation of Lean Manufacturing and Just in Time Production (JIT) systems entail U-shaped assembly line (Chiang, 2006). The associated line balancing problem is called UALBP, which was introduced by Miltenburg and Wijngaard (1994). Compared to traditional straight lines and parallel lines, U-shaped assembly lines have lots of advantages in terms of performance of workers and production system. Especially, by means of U-shaped layout, improved balancing of assembly lines can be achieved (Scholl and Klein, 1999). This is due to the fact that precedence constraints of the U-shaped lines are more relaxed than those of the straight lines, such that, a task can share a station with any of its predecessors and/or any of its successors (Scholl and Klein, 1999). This provides solution of the problem with a better line efficiency and lower line imbalance. The implementation of Lean Manufacturing systems entail U-shaped assembly lines, since one-piece flow can be implemented by this type of facility layout (Satoğlu et al., 2010). Due to high capital requirements when installing or redesigning a line, its configuration planning is of great relevance for practitioners. Cheng et al., (2000) proposed the following factors that enhanced the wider acceptance of U-shaped lines: • U-shaped line is preferred to a straight line because of its volume flexibility. By increasing or decreasing the number of operators on the line, a company can adjust the production rate as required. This level of volume flexibility is harder to obtain with a straight line. Besides, since walking distance is shorter in a U-shaped than on a straight line, it is easier for an operator to oversee several workstations. • Another advantage of U-shaped line is that the number of workstations required is never more than that required by a straight line (Scholl and Klein, 1999). There are more possibilities for grouping tasks into workstations on a U-line. Moreover, a U-line eliminates the need for special material-handling equipment such as conveyors and other special material-handling operators that are necessary in straight line. Instead, production operators move products from machine to machine. • Moreover, U-shaped lines offer organizational and social advantages. The operators are expected to become multi-skilled and they are able to manage several tasks, which provides job-enrichment. This prevents the daily activities of the operators from becoming routine. Since the operators can see the end product, they are motivated to achieve a higher quality level (Scholl and Klein, 1999). Moreover, a better visibility, communication and teamwork can be achieved by means of the U-shaped lines. This facilitates a sense of belonging, and increases responsibility and ownership compared to a straight line. For solving the UALBP, Miltenburg and Wijngaard (1994) employed a dynamic programming formulation to solve small problems with up to 11 tasks and proposed a heuristic to solve larger problems. Urban (1998) presented an integer linear programming formulation to solve small to medium sized U-line balancing problems with up to 45 tasks by using standart mathematical programming software CPLEX. Scholl and Klein (1999) developed a branch and bound procedure called ULINO to solve problems with up to 297 tasks. Becker and Scholl (2006) extended the problem by integrating practical and relevant aspects, like parallel lines or processing alternatives. In spite of these efforts, there is a wide gap between the academic discussion and practical applications (Boysen et al., 2007). An important issue in U-shaped assembly line balancing problem is the consideration of human factors. Since U-shaped lines are concerned with manual assembly operations, human factor plays a major role in production systems. However, there is a limited literature on human factors in line balancing. These are; • Ergonomic aspects such as physical effort of operators and the risks that they face (Choi, 2009; Otto and Scholl, 2011; Xu et al., 2012), • Learning effect (Costa and Miralles, 2009; Toksari et al., 2008; 2010), • Fatigue (Digiesi et al., 2009) and • Workers' skills (Miralles et al., 2007, 2008; Wong et al., 2006). Worker performance must be considered in line balancing, because as a worker becomes more experienced in performing a specific task, in other words his/her cumulative production quantity increases, his/her task time per one piece of product decreases in a non-linear sense. Therefore, task times are not independent from workers' performance. Another fact is, that every worker cannot perform every task at the same processing time. In addition, every worker cannot be able to perform every task in producton systems. These facts can significantly cause actual task times differ from the preassumed standard times. However, most researchers assumed that the time of task is independent from workers performance. In this study, a Nonlinear Integer Programming Model that intends to assign tasks to the operators of a U-shaped assembly line is developed. Thus, the worker performance that is a significant human factor was reflected to the U-shaped Assembly Line Balancing Problem (UALBP). This is a unique aspect of this study. To the best of the author's knowledge, there is no past study that considers simultaneously both minimization number of workstation and optimization of worker assignment while balancing the single model U-shaped assembly lines. The thesis is organized as follows: First, assembly lines and line balancing problem are explained. Then, a detailed literature research is conducted. The proposed mathematical model is explained in section 4 and computational experiments are conducted in section 5. The study is completed with a conclusion, suggestions and further research.