성균관대학교 · Engineering
Sang Do Noh 교수의 연구실은 제조업의 디지털 전환을 선도하는 분야에서 활동하며, 스마트 팩토리 및 디지털 트윈 기반의 개인화 생산 시스템 개발에 중점을 둡니다. 특히 공정 제어, 복원성 있는 생산 시스템(CPS, CPLS), 그리고 산업 인터넷(IoT) 기반의 효율적 제조 플랫폼 설계를 통해 제조 현장의 지속 가능성과 유연성을 제고하는 데 연구를 집중하고 있습니다. 다수의 논문에서 제시된 다층적 사이버-물리 시스템 아키텍처와 제품 수명주기 관리(PLM) 통합 솔루션은 실제 제조 환경에 적용 가능한 실용적 기반을 제공합니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
Recently, manufacturing concepts, such as personalized production and distributed manufacturing, have attracted attention owing to the ongoing revolution in industrial technology. Connected micro smart factories in factory-as-a-service system with these new manufacturing paradigms and Industrial Internet of Things (IIoT) are inefficient in terms of cost and production. To solve these problems, a digital twin, which uses a digital representation of a process, with the same configuration of manufa
Personalised production allows the supply chain (SC) to exist in various dynamic fluctuations within a make-to-order (MTO) environment. An SC for personalised production has redundant inventory and operation capacity; therefore, it requires a system that can achieve recoverability for operation resilience. Thus, a standalone cyber physical system (CPS) has limitation for SC control with MTO. To solve this problem, the CPS must be coordinated, and a systematic approach is required. This study pro
ABSTRACT In the era of the Fourth Industrial Revolution, there is a growing focus on digital twin (DT) in order to advance toward smart manufacturing. Thus, researchers have conducted numerous studies on DT and extensively developed related technologies. There are many studies that apply and analyse DT to actual manufacturing sites for the realization of a smart factory, but it is necessary to clearly consider which part of DT is applied and what function it performs in manufacturing. As such, t
Ensuring sustainability is a primary concern of the manufacturing industry. Not only does the enhancement of process and systematic efficiency secure sustainability through increased energy efficiency but it also improves the efficiency in terms of overall productivity. Dyeing and finishing industries consume massive amounts of energy and have large energy-related expenditures. The industry comprises small- and medium-sized enterprises, which have insufficient capital to pay for the energy-effic
To achieve efficient personalized production at an affordable cost, a modular manufacturing system (MMS) can be utilized. MMS enables restructuring of its configuration to accommodate product changes and is thus an efficient solution to reduce the costs involved in personalized production. A micro smart factory (MSF) is an MMS with heterogeneous production processes to enable personalized production. Similar to MMS, MSF also enables the restructuring of production configuration; additionally, it
PLM (product lifecycle management) is an innovative manufacturing paradigm which allows company's engineering contents to be developed and integrated with all business processes in the extended enterprise throughout the product lifecycle. This allows engineering decisions to be made with a full understanding of the product and its portfolio, including processes, resources, and plants. For today's manufacturing industries, support from software systems is essential for the creation, management, a
Today, megatrends such as individualization, climate change, emissions, energy, and resource scarcity, urbanization, and human well-being, impact almost every aspect of people’s lives. Transformative impacts on many sectors are inevitable, and manufacturing is not an exception. Many studies have investigated solutions that focus on diverse directions, with urban production being the focus of many research efforts and recent studies concentrating on Industry 4.0 and smart manufacturing technologi
In a re-entrant job shop (RJS), an entity can visit the same resource type multiple times; this is called re-entrancy, which occurs frequently in actual industries. Re-entrancy causes an NP-hard problem and is dominated by heuristics-based production control. The stochastic arrivals due to re-entrancy require the design of an appropriate dispatching rule. Reinforcement learning (RL) is an efficient technique for establishing robust dispatching rules; however, only a few cases that coordinate RL-
With the increasing dynamic nature of customer demand, production, product, and manufacturing design changes have become more frequent. Moreover, inadequate validation during the manufacturing design phase may result in additional issues, such as process redesign and layout reallocation, during the operation phase. Therefore, systems that can pre-validate and allow accurate and reliable analysis in the manufacturing design phase, as well as apply and optimize variations in production lines in re
The manufacturing industry has witnessed rapid changes, including unpredictable product demand, diverse customer requirements, and increased pressure to launch new products. To deal with such changes, the reconfigurable manufacturing system has been proposed as one of the advanced manufacturing systems that is close to the realisation of smart manufacturing since it is able to reconfigure its hardware, software, and system structures in a much quicker manner. Conventional simulation technologies
Generally, the generation of a simulation model is both a time- and cost-consuming task within processes for performing simulation. Therefore, reuse of the simulation model that is once generated based on a huge amount of information/data is an essential and important issue for simulation engineers. It is more difficult to exchange a reusable simulation model across heterogeneous simulation systems because these systems have different structures and modes of expressing information even if the co