|Yuen, Shun Ming
|An industrial Internet-of-Things (IIoT) system for smart manufacturing of electronics products
|Choy, K. L. (ISE)
Chen, P. C. (ISE)
|Electronic industries -- Management
Internet of things -- Industrial applications
Hong Kong Polytechnic University -- Dissertations
|Faculty of Engineering
Department of Industrial and Systems Engineering
|xiv, 171 pages : color illustrations
|Accompanying the globalization trend, the present business world is becoming more dynamic. Manufacturers always seek effective approaches to maintain good product quality, especially for environmentally sensitive electronic products. Unlike general goods, the quality of raw materials, semi-and final environmentally sensitive products can be easily affected by the external environment, i.e., the ambient temperature and relative humidity, during the electronics manufacturing process. Therefore, rigorous quality control of every process in the manufacturing plant is necessary to maintain a high quality of products. However, the entire manufacturing process is complicated and involves numerous sections, including mould rooms, processing workshops, dust-free workshops, production workshops and a number of storage facilities. Each section has its own specific requirements for environmental conditions and the staff are required to regularly check the environmental information in each section one by one, leading to a time-consuming and inefficient whole environmental control process. In addition, the reporting mechanism when conditions are out of specification is done manually at regular intervals, resulting in a certain likelihood of quality deviation. In this research study, an Industrial Internet-of-Things (IIoT) System is proposed, with the adoption of the latest Internet of Things (IoT) technologies to develop and deploy a real-time environmental monitoring scheme in electronics manufacturing. Using IoT architecture, the environmental information, i.e., ambient temperature and relative humidity, can be collected in a real-time manner through the use of IoT sensors. Based on the process parameters and the data collected from IoT technologies, quality analysis is then performed using a fuzzy association rule mining (FARM) approach. Although IoT is useful in environmental monitoring during the manufacturing process, IoT applications in each manufacturing plant vary due to different specifications, such as product types, product nature, plant layout, production flow, machine and equipment settings. Accordingly, it is essential to perform risk analysis to ensure that any possible situation and are of uncertainty are given consideration before the implementation process. By identifying the risks faced by manufacturing plants in relation to IoT applications, the likelihood and consequences of the risks are analysed by using a fuzzy analytical hierarchy process (FAHP) to calculate the weighting of the risks. In order to validate the proposed system, a case study was conducted in an electronics manufacturing company located in Shenzhen, China. This study contributes to a practical approach in managing IoT technology implementation so as to increase competitiveness in the manufacturing industry. In addition, the research output provides significant value in terms of improved visibility of environmental conditions in manufacturing sites and a systematic approach to analyse the relationship between quality deviation and ambient factors.
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