In an automotive plant, an automated storage and retrieval system (ASRS) synchronizes material handling flows from a part production line to an auto-assembly line. The part production line transfers parts on small-/large-sized pallets. The products on pallets are temporarily stored on the ASRS, and the ASRS retrieves the products upon request from the auto-assembly line. Each ASRS aisle is equipped with narrow-/wide-width racks for two pallet sizes. An ASRS aisle with narrow-/wide-width racks improves both storage space utilization and crane utilization while requiring delicate ASRS aisle design, i.e., the locations of the narrow-/wide-width racks in an ASRS aisle, and proper operation policies affect the ASRS performance over demand fluctuations. We focus on operation policies involving a common storage zone using wide-width racks for two pallet sizes and a storage-retrieval job-change for a crane based on assembly-line batch size. We model a discrete-event simulation model and conduct extensive experiments to evaluate operation policies. The simulation results address the best ASRS aisle design and suggest the most effective operation policies for the aisle design.

The purpose of this study is to analyze the adequacy of production capacity of the assembly process system of mobile bath vehicle’s top box panel and process design through a simulation analysis. Towards this end, the layout of the facility designed with pre-verification job using a simulation modeling and an experiment, and facility, logistics process, and personnel input method were made into a simulation model, and the design system’s adequacy was evaluated through an experiment. To produce 120 mobile bath vehicles annually, it was analyzed that 14 general workers and seven skilled workers were adequate through the experiment. It was also identified that three painting process lines carried out through outsourcing were adequate. Production lead time was 201.7 hours on average and it was 230 hours maximum. To meet customer delivery service level of 95% within the deadline when establishing a customer order and vehicle delivery plan, it was analyzed that more than 215 hours of lead time is needed minimum. If the process cycle time is reduced to 85% upon system stabilization and skillfulness improvement, it was analyzed that annual output of 147 vehicles can be achieved without additional production line expansion.

The application of the theoretical model to real assembly lines has been one of the biggest challenges for researchers and industrial engineers. There should be some realistic approach to achieve the conflicting objectives on real systems. Therefore, in this paper, a model is developed to synchronize a real system (A discrete event simulation model) with a theoretical model (An optimization model). This synchronization will enable the realistic optimization of systems. A job assignment model of the assembly line is formulated for the evaluation of proposed realistic optimization to achieve multiple conflicting objectives. The objectives, fluctuation in cycle time, throughput, labor cost, energy cost, teamwork and deviation in the skill level of operators have been modeled mathematically. To solve the formulated mathematical model, a multi-objective simulation integrated hybrid genetic algorithm (MO-SHGA) is proposed. In MO-SHGA each individual in each population acts as an input scenario of simulation. Also, it is very difficult to assign weights to the objective function in the traditional multi-objective GA because of pareto fronts. Therefore, we have proposed a probabilistic based linearization and multi-objective to single objective conversion method at population evolution phase. The performance of MO-SHGA is evaluated with the standard multi-objective genetic algorithm (MO-GA) with both deterministic and stochastic data settings. A case study of the goalkeeping gloves assembly line is also presented as a numerical example which is solved using MO-SHGA and MO-GA. The proposed research is useful for the development of synchronized human based assembly lines for real time monitoring, optimization, and control.

본 연구에서는 해양플랜트 산업의 가치사슬 및 수명주기 연구를 통해 해양 자원개발 비즈니스의 포괄적인 형상을 파악하였고 해양프로젝트 검증 목적의 시뮬레이션을 위해 조립 및 인간공학 시뮬레이션에 대한 연구를 수행하였다. 구체적으로는 조립 시뮬레이션의 경우 드릴쉽을 대상으로 탑재공정에 대한 조립 시뮬레이션을 통해 공정에 대한 유효성 검증을 수행할 수 있었고, 인간공학 시뮬레이션의 경우 FPSO 플랫폼을 대상으로 작업자 시뮬레이션을 통해 작업환경에서의 문제점을 사전에 도출할 수 있었다.

CONWIP is robust and efficient for various type of operating system, such as series, parallel, and assembly systems. Especially, assembly system would be controlled couple of modified CONWIP system. In the following paper, we developed Critical Path CONWIP system that gives signal to sub-line from a station of critical path then, compared with m-conwip, discrete-card-buffer CONWIP. 2 representative asymmetric assembly system models are used to compare each control system. As a result, critical path CONWIP holds less whole work-in-process with similar output. It can decrease total cost and WIP for high holding cost assembly system

The assembly tolerance design methods have applied linear or nonlinear programming methods and used simulation method and search algorithms to optimize the tolerance allocation of each part in an assembly. However, those methods are only considered to the relationship between tolerance and manufacturing cost, which do not consider a quality loss cost for each part tolerance. In this paper, the integrated simulation model used genetic algorithm and the Monte-Carlo simulation method was developed for the allocation of the optimal tolerance considering the manufacturing cost and quality loss cost.