Simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

Abstract

Growing interests from customers in customised products and increasing competitions among peers necessitate companies to configure their manufacturing systems more effectively than ever before. We propose a new assembly line system configuration for companies that need intelligent solutions to satisfy customised demands on time with existing resources. A mixed-model parallel two-sided assembly line system is introduced based on the parallel two-sided assembly line system previously proposed by Ozcan et al. (Balancing parallel two-sided assembly lines, International Journal of Production Research, 48 (16), 4767-4784, 2010). The mixed-model parallel two-sided assembly line balancing problem is illustrated with examples from the perspective of simultaneous balancing and sequencing. An agent based ant colony optimisation algorithm is proposed to solve the problem. This algorithm is the first attempt in the literature to solve an assembly line balancing problem with an agent based ant colony optimisation approach. The algorithm is illustrated with an example and its operational procedures and principles explained and discussed.Keywords: mixed-model parallel two-sided assembly lines; assembly line balancing; agent based ant colony optimisation; meta-heuristics; artificial intelligence

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

“…A set of tasks, , belonging to each product model is performed according to certain technological precedence relationships and represents the set of predecessors of task for model on line . A certain amount of processing time associated with each task needs to be processed on a series of workstations , where is a binary variable and 0 represents the left side line while 1 represents the right side line (Kucukkoc and Zhang, 2014). As in traditional lines, capacity constraints and precedence relationships need to be satisfied.…”

“…This paper aims to develop a generic solution-building approach for the mixed-model assembly line balancing problem using the framework proposed by Kucukkoc and Zhang (2014) and contributes to knowledge in several aspects. First of all, unlike the study by Kucukkoc and Zhang (2014), the problem studied in the current work does not consider the model sequencing problem. Instead, it aims to obtain a mixed-model parallel two-sided assembly line system which is compatible with any model sequence.…”

“…Although mixedmodel parallel two-sided assembly lines are encountered in producing large-sized highvolume products in industry (see for example Jack (2012) for Mercedes-Benz TM bus assembly lines at their Istanbul plant and Bloomberg (2015) for Toyota TM Caetano Portugal airport buses assembly line at their Portugal plant), this problem has not been properly dealt with by researchers. Kucukkoc and Zhang (2014) introduced the mixed-model parallel two-sided assembly line balancing and sequencing problem and proposed a solution framework to solve the problem using an agent-based approach. This paper aims to develop a generic solution-building approach for the mixed-model assembly line balancing problem using the framework proposed by Kucukkoc and Zhang (2014) and contributes to knowledge in several aspects.…”

“…Kucukkoc and Zhang (2014) introduced the mixed-model parallel two-sided assembly line balancing and sequencing problem and proposed a solution framework to solve the problem using an agent-based approach. This paper aims to develop a generic solution-building approach for the mixed-model assembly line balancing problem using the framework proposed by Kucukkoc and Zhang (2014) and contributes to knowledge in several aspects. First of all, unlike the study by Kucukkoc and Zhang (2014), the problem studied in the current work does not consider the model sequencing problem.…”

“…Mixed-model lines emerged as a consequence of increasing interest in customized products in the global market, and Thomopoulos (1967) introduced the mixed-model assembly line balancing problem. Mixed-model lines enable production of different product models on the same line in an intermixed sequence (Boysen et al, 2008;Kucukkoc and Zhang, 2014). Various heuristic, meta-heuristic, and exact solution approaches have been proposed for solving the mixed-model assembly line balancing problem; e.g., Kara et al (2007), Ozcan and Toklu (2009a), Ozcan et al (2010a), Mosadegh et al (2012), and Manavizadeh et al (2013) developed simulated annealing approaches; Ozcan et al (2011), Xu andXiao (2011), Akpinar andBayhan (2011), Hamzadayi and Yildiz (2012), and Manavizadeh et al (2012) developed genetic algorithm techniques; Simaria and Vilarinho (2009) and Yagmahan (2011) developed ant colony optimization (ACO) techniques, and Akpinar et al (2013) hybridized ACO with a genetic algorithm.…”