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Top1. Introduction
An assembly line comprises a series of workstations where a set of assembly tasks is executed repeatedly. When demand increases and some favorable ergonomics conditions are required, a lean manual assembly line may not satisfy a specific takt time and some tasks need to be automated to form a semi-automatic assembly line, gaining benefits from both humans and robots. Improving productivity and working conditions may not be the only reasons to automate; reducing a high labor cost is also added to the need for transformation. Lacking skilled labor due to demographic transition, the salary and training costs of human operators have increased. How to transform a manual line to a semi-automatic line? Conventionally, the objective when designing an assembly line is to raise the line efficiency by minimizing the operating costs and/or maximizing the throughput. However, factors related to workers that determine the quality and productivity of an assembly line are rarely mentioned (Le & Van Huynh, 2018). There are several works studied how to improve quality and productivity of robots by using a knowledge-based system. Wang L., Tian Y., Sawaragi T., & Horiguchi Y. (2010) studied how to acquire and transfer tacit knowledge to other robots and workers. Al-Moadhen A. A., Packianather M., Setchi R., & Qiu R. (2016) used a semantic knowledge to increase intelligence in robot task planning generation. However, these works focused on full automation and did not involve transforming a manual assembly line to semi-automation so criteria in a task allocation were not discussed.
This paper uses a case study from a project involving collaboration between DENSO International Asia and Sirindhorn International Institute of Technology to demonstrate a proposed methodology to transform a lean manual assembly line to a semi-automatic assembly line for a Lego-car production line in a design phase. The assembly line has been used to teach undergraduate and graduate students to design and improve a lean manufacturing process. To discuss human-robot task allocation in semi-automation process design in Introduction, Literature review, and Methodology, readers should be informed about the current setup of manual assembly line such as physical requirements in manual assembly tasks and a sequence and types of operations. This information should strengthen problem background for the readers. Thus, it is necessary to introduce Lego parts, a setup and a performance of a current assembly line using three manual operators before semi-automation transformation. One Lego car has six small and light-weight parts consisting of one base, one front, two frames, four tires, one roof, and one rear. The Bill of Material (BOM) and the dimensions of a Lego car are illustrated in Figure 1. Employing Japanese lean manufacturing practice to reduce muda (wastes) in the process, the Lego-car assembly line is first designed to satisfy 17 seconds of takt time using three manual operators. The sequence of work elements with the processing time assigned to operator 1, 2 and 3 is displayed in Figure 2. It has a high line balancing ratio of 96.43%. Only four units of standard work in process (WIP) is used in the design to simultaneously keep a continuous flow or one-piece flow and minimize an inventory. From this current manual assembly line, a proposed method is then utilized to transform a manual assembly line to a semi-automatic one using a human-robot task allocation methodology which is the key to this study.