Control level simulation of an automatic storage and retrieval system in the automotive industry

Ko, Min Soo; Park, Sang C; Chang, Moon Jong

doi:10.1177/1063293x12474830

Cited by 7 publications

(2 citation statements)

References 15 publications

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“…Li et al (2009) emphasized the availability of real-time data to achieve a more sophisticated analysis for the control and scheduling of complex manufacturing systems. Ko et al (2013) proposed control-level simulation of an automatic storage and retrieval system in the automotive industry. In their research, the system for machine-level simulation was developed on the basis of communication with a programmable logic controller (PLC), which contains low-level data such as sensor signals, interlock signals, and sensor sequences.…”

Section: Introductionmentioning

confidence: 99%

A dynamic processing methodology of manufacturing data for the automated throughput analysis in cyber-physical production environment

Kang

Lee

Noh

2019

Concurrent Engineering

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Various studies have been conducted on cyber-physical production systems (CPPS), a core technology for the implementation of smart manufacturing. However, existing studies are mostly conceptual or at an early stage, such as the proposal of a reference architecture. To achieve the practical implementation of CPPS, a systematic methodology for the collection, processing, and application of the data for CPPS is required. This is because CPPS can be successfully implemented only when processing criteria and application methods for the diverse data that change in real time because of the nature of a manufacturing shop floor are presented. Various technologies and systems have been developed for collecting raw data from a shop floor, but they are mainly focused on the automation of manufacturing. Thus, more detailed and systematic research is required for more efficient application of such technologies using a cyber model, which is the core of CPPS. For this purpose, in this article, a logic-based systematic methodology that can generate a throughput analysis model from the real-time data of a shop floor in a CPPS environment was proposed. Furthermore, logics that perform the Mapping, Scaling, and Calibration of the data of the shop floor into the machine, process, and factory levels were developed and their application to throughput analysis was described through a case study. The results of this study are expected to facilitate the practical implementation of CPPS and contribute to the successful implementation of smart manufacturing and the resultant revival of the manufacturing industry.

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Section: Introductionmentioning

confidence: 99%

A dynamic processing methodology of manufacturing data for the automated throughput analysis in cyber-physical production environment

Kang

Lee

Noh

2019

Concurrent Engineering

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“…We logically divided the entire manufacturing enterprise information management system into three layers involving design management, management control, and process control, as shown in Figure 1. Many researchers focused on the design management layer and made a lot of achievements such as product conceptual design information modeling (Víctor et al, 2013), collaborative product innovation network (Song et al, 2012), technology platform and product platform development (Levandowski, 2012), and control level simulation of an automatic storage and retrieval system (Ko, 2013). On the management control layer, a workshop production management platform based on collaborative manufacturing execution system (c-MES) is responsible for all aspects involved in the workshop execution process.…”

Section: Introductionmentioning

confidence: 99%

A collaborative manufacturing execution system oriented to discrete manufacturing enterprises

Wang

Liu

Yizheng³

et al. 2016

Concurrent Engineering

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The study aims to present architecture and technology solution for collaborative manufacturing execution system oriented to discrete manufacturing enterprises. Under the networked manufacturing environment, the enterprises are facing challenges including the increasing manufacturing process complexity, the shorter product delivery, the higher customer satisfaction requirements, and so on. To deal with these challenges, the manufacturing enterprises must implement information management, while collaborative manufacturing execution system is one of the key technologies to realize informationization. Thus, in this study, the authors analyze production characteristics, typical production flow, and collaborative management requirements of multi-workshop production in the discrete manufacturing enterprise and propose an architecture of collaborative manufacturing execution system oriented to discrete manufacturing enterprises. The main functions of this system and key technologies to realize the system is also analyzed. Finally, a prototype system is developed and a case study is executed in Henan Pingyuan Optics Electronics Co., LTD in OPTO-Electronic Group to demonstrate the implementation and potentials of the system.

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An agile operations management system for green factory

Noh

Cho³

2014

Int. J. of Precis. Eng. and Manuf.-Green Tech.

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The globalization of suppliers and personalization of customers require new manufacturing strategy for environmental issues, region's special regulation and energy besides manufacturing factors from manufacturers. In this study, green factory is defined as a manufacturing floor that reduces waste elements such as extra work, energy, time and cost through quickly responding to external uncontrollable changes like a regulation, due date and supply. Therefore, the green factory should respond by establishing and implementing strategies for controlling their production volumes, changing their dispatch rules, adjusting their work schedules, increasing and decreasing the number of their machines and workers based on their own internal data and capacities, and other measures. To achieve such objective, manufacturing companies should realize a manufacturing intelligence that can visualize their shop-floor data, and detect and solve problems at the business planning level. In this study, an agile operations management (AOM) system that can quickly respond to field problems was developed for manufacturing intelligence. The AOM system refers to a system that collects internal data, monitors such data in real time, immediately detects problems, if any, and provides solutions to the detected issues within the shortest time.

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Control level simulation of an automatic storage and retrieval system in the automotive industry

Cited by 7 publications

References 15 publications

A dynamic processing methodology of manufacturing data for the automated throughput analysis in cyber-physical production environment

A dynamic processing methodology of manufacturing data for the automated throughput analysis in cyber-physical production environment

A collaborative manufacturing execution system oriented to discrete manufacturing enterprises

An agile operations management system for green factory

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