By the recent fast growth of e-commerce markets, it has been stimulated to study order picking systems to improve their efficiency in distribution centers. Many companies and researchers have been developed various types of order picking systems and pursued the corresponding optimal operation policies. However, the performances of the systems with the optimal policies often depend on the structures of the centers and the operation environments. Based on a simulation model that mimics a unique zone picking system operated by a real company in the Republic of Korea, this study compares several operation policies and finds the most appropriate order selection rule and worker assignment policy for the system. Under all scenarios considered in this study, simulation results show that it is recommendable to assign more efficient workers to the zones with heavier workload. It also shows that selecting the order with the maximum number of non-repeatedly visited zones from the order list provides the most consistent and stable performances with respect to flow time, makespan, and utilization of the system even under the scenario with the breakdown zones. On the other hand, selecting the order with the minimum ratio of penalty to the number of zones performs the worst in all scenarios considered.

Recently, due to the expansion of the logistics industry, demand for logistics automation equipment is increasing. The modern logistics industry is a high-tech industry that combines various technologies. In general, as various technologies are grafted, the complexity of the system increases, and the occurrence rate of defects and failures also increases. As such, it is time for a predictive maintenance model specialized for logistics automation equipment. In this paper, in order to secure the operational safety and reliability of the parcel loading system, a predictive maintenance platform was implemented based on the Naive Bayes-LSTM(Long Short Term Memory) model. The predictive maintenance platform presented in this paper works by collecting data and receiving data based on a RabbitMQ, loading data in an InMemory method using a Redis, and managing snapshot DB in real time. Also, in this paper, as a verification of the Naive Bayes-LSTM predictive maintenance platform, the function of measuring the time for data collection/storage/processing and determining outliers/normal values was confirmed. The predictive maintenance platform can contribute to securing reliability and safety by identifying potential failures and defects that may occur in the operation of the parcel loading system in the future.

사물인터넷(IoT) 기술을 활용한 전력 사용량 모니터링은 스마트팜 운영비 절감 기술 개발을 위한 기초자료로 필요성이 부각되고 있다. 본 연구에서는 멜론 생산 스마트팜 운영 중 실시간 전력사용량 모니터링 시스템을 설치한 예를 소개하고 이 를 이용하여 수집된 데이터를 실시간으로 활용하는 방법을 제 안한다. 전력사용량 모니터링 시스템의 실증을 위하여 멜론 스마트팜에서 3개월의 멜론 재배기간 동안 보일러, 양분분배 시스템, 자동제어기, 순환팬, 보일러제어기, 기타 IoT 관련 유 틸리티 등 스마트팜 시설에서 사용하는 개별 전원 기구들의 전력사용량 데이터를 수집하였다. 모니터링 결과를 이용하여 전기에너지 소비패턴의 예시를 분석하고, 측정 데이터를 최 적으로 활용하기 위해 필요한 고려사항을 제시하였다. 본 논 문은 전력사용량 모니터링 시스템을 새로이 구축하고자 하는 유저들에게 기술적 진입장벽을 낮추고 생성된 데이터 활용 시 시행착오를 줄이는 데 유용한 자료가 될 것으로 사료된다.

The development of technology related to the Fourth Industrial Revolution and the growth of the online market due to pandemic are continuing the growth of the logistics market for product delivery. If it is difficult to deliver the product directly to the customer during delivery, storage and delivery using the unmanned courier box are being carried out. However, existing storage boxes are not actively used due to lack of usability even though they have the advantage of storing goods and delivering non-face-to-face. In addition, existing courier boxes are not prepared for cold chain transportation. The unmanned delivery storage device with ICT cold chain technology should be developed to prepare for the transition to non-face-to-face society, to improve logistics efficiency and meet user's requirements. Also, it is necessary to consider the measures to reduce the safety problems that may occur during the use and maintenance of the automatic system.This study conducted a model-based analysis for the development of unmanned delivery storage devices with ICT cold chain technology, and conducted a study to derive the system development specifications that meet the requirements and secure safety and apply them to the development process.

본 연구는 서로 다른 철학적 관점과 지침원리에 근거한 사회적 HRM 시스템과 경제적 HRM 시스템이 구성원의 태도와 행동 및 조직의 운영역량에 미치는 영향을 분석하였다. 한국직업능력개발원에서 조사하 는 인적자본패널(HCCP)의 2007년-2017년 원자료를 이용하여 분석한 결과 첫째, 사회적 HRM 시스템은 구성원의 태도와 행동 및 조직의 운영역량에 긍정적인 효과가 있음을 확인하였으나 경제적 HRM 시스템의 조직 운영역량에 관한 효과는 확인되지 않았다. 둘째, 사회적 HRM 시스템이 태도와 행동 및 운영역량 에 미치는 효과는 경제적 HRM 시스템의 효과보다 크다는 증거를 발견하였다. 셋째, 사회적 HRM 시스템 과 경제적 HRM 시스템 간의 정합성 효과는 발견되지 않았다. 즉, 사회적 HRM 시스템 및 경제적 HRM 시스템의 수준이 일치하는 경우가 어느 한쪽의 시스템 수준이 높거나 낮은 경우보다 조직 성과에 미치는 영향이 크지 않음을 확인하였다. 넷째, 사회적 HRM 시스템 수준과 경제적 HRM 시스템 수준이 모두 낮은 경우보다 두 시스템 수준이 모두 높은 경우에 조직 성과에 미치는 긍정적 효과가 더 높음을 실증하였다. 본 연구 결과는 사회적 HRM 시스템이 구성원의 기량을 향상시키고 동기를 부여하며 새로운 직무기회를 제공하는 실무관행을 통해 구성원의 태도와 행동 및 조직의 운영역량에 긍정적인 효과가 있음을 의미한다. 반면, 구성원 간의 경쟁을 기본 원리로 삼아 인적자본을 갖춘 스타인재를 확보하고 개인적인 인센티브를 통해 동기를 부여하는 경제적 HRM 시스템만으로는 조직 성과의 향상에 한계가 분명함을 시사한다. 또한, 사회적 HRM 시스템의 실무관행 간에는 상보적인 시너지 효과를 기대할 수 있지만, 경제적 HRM 시스템 내에서는 이와 같은 시너지 창출이 어려움을 암시하고 있다. 사회적 HRM 시스템이 경제적 HRM 시스템보다 효과가 높을 뿐만 아니라 두 HRM 시스템 간의 정합성 효과는 기대하기 어렵다는 본 연구의 결과는 이론적, 실무적 관점에서 증거 기반의 HRM 시스템을 구축하려는 기업에 중요한 시사점을 제공하고 있다.

With the advent of the 4.0 era of logistics due to the Fourth Industrial Revolution, infrastructures have been built to receive the same services online and offline. Logistics services affected by logistics 4.0 and IT technology are rapidly changing. Logistics services are developing using technologies such as big data, artificial intelligence, blockchain, Internet of things, and augmented reality. The convergence of logistics services and various IT new technologies is accelerating, and the development of data management solution technology has led to the emergence of electronic cargo waybill to replace paper cargo waybill. The electronic waybill was developed to supplement paper waybill that lack economical and safety. However, the electronic waybill that appeared to complement the paper waybill are also in need of complementation in terms of efficiency and reliability. New research is needed to ensure that electronic cargo waybill gain the trust of users and are actively utilized. To solve this problem, electronic cargo waybill that combine blockchain technology are being developed. This study aims to improve the reliability, operational efficiency and safety of blockchain electronic cargo waybill. The purpose of this study is to analyze the blockchain-based electronic cargo waybill system and to derive evaluation indicators for system supplementation.

There are several methods of peak-shaving, which reduces grid power demand, electricity bought from electricity utility, through lowering “demand spike” during On-Peak period. An optimization method using linear programming is proposed, which can be used to perform peak-shaving of grid power demand for grid-connected PV+ system. Proposed peak shaving method is based on the forecast data for electricity load and photovoltaic power generation. Results from proposed method are compared with those from On-Off and Real Time methods which do not need forecast data. The results also compared to those from ideal case, an optimization method which use measured data for forecast data, that is, error-free forecast data. To see the effects of forecast error 36 error scenarios are developed, which consider error types of forecast, nMAE (normalizes Mean Absolute Error) for photovoltaic power forecast and MAPE (Mean Absolute Percentage Error) for load demand forecast. And the effects of forecast error are investigated including critical error scenarios which provide worse results compared to those of other scenarios. It is shown that proposed peak shaving method are much better than On-Off and Real Time methods under almost all the scenario of forecast error. And it is also shown that the results from our method are not so bad compared to the ideal case using error-free forecast.

In this study, based on the System Dynamics (SD) methodology, the interrelationship between the factors inherent in the operation of the New Technology Certification System (NTCS) in Korea was identified by a causal map containing a feedback loop mechanism in connection with ‘new technology development investment’, ‘commercialization of new technology’, and ‘sales by new technology’. This conceptualized causal map was applied to the simulation of the operations of the New Excellent Technology and Environmental Technology Verification System (NET&ETV) run by the Ministry of Environment among various NTCSs in Korea. A SD computer simulation model was developed to analyze and predict the operational performance of the NET&ETV in terms of key performance indices such as ‘sales by new technology’. Using this model, we predicted the future operational status the NET&ETV and found a policy leverage that greatly influences the operation of the NET&ETV. Also the sensitivity of the key indicators to changes in the external variables in the model was analyzed to find policy leverage.

Supply chain management can be defined as an information system that connects the inside and outside of a company. Its purpose is to systematically and strategically manage the flow of information, resources and services to improve the long-term performance of the entire organization, including individual companies connected to the supply chain, and the quality of service provided to customers. The ultimate goal of SCM is to create synergy through organic integration of supply and demand based on cooperation and collaboration with stakeholders in the supply chain. This study is based on the hypothesis that the company's management performance will improve as the level of SCM improves. Most of the previous studies dealt with the relationship between corporate performance and SCM in the IT area. In this study, research was conducted through human capacity with IT system. The causal relationship was demonstrated, and there was a difference in the perception of the results of this study depending on whether or not smart factories were consulted in the era of the 4th Industrial Revolution. There is a need to examine the links between management's value chain and its causal relationship.

PURPOSES: This paper presents the development and evaluation of the smart hardware-in-the-loop systems (SMART-HILS) that evaluate traffic signal operations of a new real-time traffic signal control system called SMART SIGNAL at the traffic management center (TMC) level. METHODS: The layouts of the hardware and software components of the SMART-HILS were introduced in this study and its performance was tested using real-time traffic signal operation algorithms embedded in the SMART SIGNAL control server by utilizing the VISSIM simulation model. In this study, the SMART-HILS management software was developed using .NET programming language. Fewer random seed numbers were used for the test scenarios by conducting statistical tests to address the shortcomings of a longer time due to the adoption of the simulation time as the real-time by the TMC server. RESULTS : It was determined that SMART-HILS can communicate with TMC and VISSIM for both upload and download directions within acceptable time constraints and evaluate new design algorithms for traffic signal timing. CONCLUSIONS : In practice, traffic engineers can utilize SMART-HILS for testing the traffic signal operation alternatives before their selection and implementation. This application could increase the productivity of traffic signal operation.

The concept of carsharing involves sharing a small number of reserved cars to be used individually by a larger number of people as required. This study examines the operating parameters of one-way carsharing systems in order to determine the appropriate operating conditions that minimizes the lost sales rate. Five operating parameters are tested in this study: the number of stations, the average number of vehicles per station, the rate of one-way trip, the average number of staffs per station, and the relocation policy. The performance of round-trip carsharing systems is also compared to that of one-way carsharing systems. A simulation model is developed and simulations are performed to determine the appropriate combination of operating parameter and levels. The simulation results show that the average number of vehicles per station is the most critical parameter. Other key findings obtained from this research are as follows. First, applying the appropriate relocation policy to one-way carsharing systems can allow more customers to rent vehicles than the traditional round-trip carsharing systems. Second, the appropriate relocation policy should be selected based on the average number of vehicles per station in order to minimize the lost sales rate. Third, the number of stations does not affect the lost sales rate. This study findings will provide tools to understand impact of the carsharing system parameters on the efficiency of the carsharing operations.

This study aims to provide a real-time information to the driver by effectively operating the advanced safety device attached to the freight vehicle, thereby minimizing insecure behavior of the driver such as speeding, rapid acceleration, sudden braking, And improve driving habits to prevent accidents and save energy. Advanced safety equipment is a device that warns the driver that the vehicle leaves the driving lane regardless of the intention of the driver and reduces the risk of traffic accidents by mitigating or avoiding collision by detecting a frontal collision during driving.The main contents of this report are as follows: In case of installing a warning device on a lane departing vehicle (excluding a light vehicle) and a lorry or special vehicle with a total weight exceeding 3.5 tonnes, the driver must continue to operate unless the driver releases the function.In addition, when the automatic emergency braking system is installed, the structure should be such that the braking device is operated automatically after warning the driver when the risk of collision with the running or stopped vehicle in the same direction is detected in front of the driving lane.