Earticle

Port storage area optimization is resulted from the space allocation requirements of a seaport. Inventory analysis, covered in the scope of operation research topics, is frequently used in the port management such as determining the capacity of the storage areas. In the scope of port planning, the feasible storage area will yield an economic configuration with minimal investment. To achieve this, there must be none or minimum idle container slots in the storage area. In this study, a model based on the inventory analysis considering the minimization of the port expenses was implemented for the İzmir port in Turkey and the optimum future storage area of İzmir port was estimated for the coming years by forecasting the container traffic using Artificial Neural Networks considering the Turkey’s economic growth. The study indicated that there is a requirement of a storage area capacity for the coming years. It was found that, the capacity requirement for an optimal storage area management for the seaport was around 10000 containers for 2014, 11000 for 2018 and 12000 for 2023.

The key to improve the container terminal efficiency is the integrated optimization of the quay crane (QC) and the yard truck (YT) scheduling, which is normally settled separately and considered in a certain condition in classical literatures. To improve the operation efficiency and simulate the practical operation, a PSO-based integrated QC-YT scheduling optimization model with uncertain factors is established in this research, considering two uncertain factors of YT travel speed and unit time of QC loading/discharging operation that affect the operating efficiency of the terminal greatly. The goal is the minimal operated time of QCs with the coordination of YTs. To solve this difficult combinatorial problem, the PSO algorithm is developed. PSO is evaluated for combinatorial problems with uncertain factors, which represents a new application of PSO. Numerical experiments show that the model of this research gives systemic simulation for the scheduling process with uncertain factors. And the results are better than model without uncertainties in terms of the accuracy and stability.

본 논문은 자동화 컨테이너 터미널의 장치장에서 장치 위치 결정 전략을 다목적 진화 알고리즘(MOEA: Multi-Objective Evolutionary Algorithm)을 이용해 최적화하는 방안을 제안한다. 장치장의 해측과 육측 생산성은 서로 상충하기 때문에, 이 둘을 동시에 최대화하는 것은 불가능하다. 대신 본 논문에서는 MOEA를 이용해 파레토 최적해 집합(Pareto optimal set)을 구하였다. 초기 실험 결과 장치장의 컨테이너 점유율이 높은 어려운 문제의 경우, MOEA의 집단이 지역 해에 쉽게 빠지는 것을 확인하였다. 이에 본 논문에서는 난이도가 다른 두 개의 문제를 동시에 최적화함으로써 집단의 다양성을 유지하는 방안을 제안하였으며, 실험 결과 제안 방안이 단일 문제만 해결하는 방안에 비해 동일한 비용으로 더 좋은 전략을 얻을 수 있음을 확인하였다.

This paper proposes a method of optimizing a stacking strategy for an automated container terminal using multi-objective evolutionary algorithms (MOEAs). Since the yard productivities of seaside and landside are conflicting objectives to be optimized, it is impossible to maximize them simultaneously. Therefore, we derive a Pareto optimal set instead of a single best solution using an MOEA. Preliminary experiments showed that the population is frequently stuck in local optima because of the difficulty of the given problem depending on the yard occupancy rate. To cope with this problem, we propose another method of simultaneously optimizing two problems with different difficulties so that diverse solutions can be preserved in the population. Experimental results showed the proposed method can derive better stacking policies than the compared method solving a single problem given the same computational costs.

This paper has focused on the middle term process planning around quays based on the prefixed long-term plan of the product mixed ships. Recently, the order rate of high add-value ships in domestic shipyards has been sharply increased and the spending time at quays is accordingly on an increasing trend. For proper and practical process planning related to quays, it has to be closely connected with a long-term plan and product calendar, erection network and result of ship allocation around quays. Moreover, it is also required to include the integrated consideration of the whole process of a yard, each ship, and each team respectively. The most distinguishing feature of this study is that it would run on the ship allocation simulator and GIS framework in order not to be limited to the specific one yard and the readers can figure out the optimization formulation containing the work load leveling and a different approach from PERT/CPM. The proposed approach reflected all requirements from the department of process planning and management in a shipyard, and the analysis of the results has explained its performance of the optimization result with the examples of total 43 ships under construction from 2008 to 2013.

This paper has focused on the middle term process planning around quays based on the prefixed long-term plan of the product mixedships. Recently, the order rate of high add-value ships in domestic shipyards has been sharply increased and the spending time atquays is accordingly on an increasing trend. For proper and practical process planning related to quays, it has to be closely connectedwith a long-term plan and product calendar, erection network and result of ship allocation around quays. Moreover, it is also requiredto include the integrated consideration of the whole process of a yard, each ship, and each team respectively. The most distinguishingfeature of this study is that it would run on the ship allocation simulator and GIS framework in order not to be limited to the specific oneyard and the readers can figure out the optimization formulation containing the work load leveling and a different approach fromPERT/CPM. The proposed approach reflected all requirements from the department of process planning and management in a shipyard,and the analysis of the results has explained its performance of the optimization result with the examples of total 43 ships underconstruction from 2008 to 2013.

3D 프린팅 기술은 다양한 산업분야에서 개념모델 및 기능성 시제품을 제작하는데 많이 응용되고 있지만, 3D 프린팅 소재 및 제작된 제품 신뢰성 등의 여러 가지 이유로 상용화 제품으로 적용되는 데 한계가 존재한다. 본 논문에서는 3D 프린팅 기술을 이용한 산업적 응용분야 중 하나로 발전소 저탄장에 사용되는 풀 코드 스위치 모듈의 부품들 중 잦은 돌발 상황으로 인해 파손이 자주 발생하는 허브 구동부와 레버 고정부 부품들에 대해 현장에서 작업자들이 단기 대체부품으로 적용이 가능하도록 하는 부품 최적 설계 및 FDM 방식 3D 프린팅 제조공정기술에 대한 연구결과를 제시하였다. 3D 프린팅 기술의 경우 소재 적용에 있어서 한계가 존재하므로, 본 논문에서는 구조 최적화 설계를 통해 구조 안정성을 확보하는 방안에 대해 연구를 수행하였다. 허브 구동부 부품에 대해 내부 구조 형상 및 구조 설계 변수 최적화를 수행하여 좌측구동모드에서는 안전계수가 153.67% 증가한 1.243을 확보할 수 있었으며, 우측구동모드에서는 404.96% 증가한 3.156을 확보할 수 있었다. 레버 고정부 부품의 경우, 반복적인 스위칭 구동에 의한 굽힘 모멘트로 인해 발생하는 파손을 최소화하기 위해 구조 최적화 설계를 수행하여 26% 증가한 구조 안전계수(7.52)를 확보할 수 있었다. 본 연구를 통해 3D 프린팅 기술을 단기 대체부품 제조공정에 적용함에 있어서 소재 최적화를 통한 설계보다는 3D 프린팅 공정의 적층특성을 활용한 구조적 최적화 설계기법 이 더욱 유연한 결과를 도출할 수 있음을 확인할 수 있었다.

Recently, 3D printing technology has been applied to make a concept model and working mockup of an industrial application. On the other hand, this technology has limited applications in industrial products due to the materials and reliability of the 3D printed product. In this study, the components of a full cord switch module are proposed as a case of a 3D printed component that can be used as a substitute for a short period. These are hub-driven and lever lockup components that have the structural characteristics of breaking down frequently in the emergency operating status. To ensure the structural strength for a substitute period, research of structure optimization was performed because 3D printing technology has a limitation in the materials used. After optimizing the structure variables of the hub-driven component, reasonable results can be drawn in that the safety factors of the left and right switching mode are 1.243 (${\Delta}153.67%$) and 3.156 (${\Delta}404.96%$). The lever lockup component has a structural weak point that can break down easily on the lockup-part because of a cantilever shape and bending moment. The rib structure was applied to decrease the deflection. In addition, optimization of the structural variables was performed, showing a safety factor of 7.52(${\Delta}26%$).