An intelligent risk management model for achieving smart manufacturing on Internet of Things

To adapt to the ever-changing environment, Internet of Things (IoT) has emerged for supporting manufacturing plants to better manage the quality of products. Since the application of IoT is relatively new to the manufacturing industry, increasing attention has been paid on how to manage the planning and implementation process so as to achieve smart manufacturing. However, IoT applications in each manufacturing plant are varied due to different specifications, such as the product types, product nature, plant layout, production flow, machine and equipment settings. Hence, it is essential to perform risk analysis to ensure that any possible situation and uncertainty is being considered before the implementation process. Risk management plays an important role since disruption can cause significant financial and reputational loss, especially for electronics products, which are environmental-sensitive. In this study, an electronic manufacturing risk management model (EM-RMM) is designed to assess the risk faced by manufacturing plants for IoT applications. By identifying the risks faced by manufacturing plants for IoT applications, the likelihood and consequences of the risks are analyzed by using fuzzy analytical hierarchy process (FAHP) to calculate the weighting of the risks. Through a case study in a plant which manufactures environmental-sensitive electronics products, the results provide a systematic procedure for risk assessment in IoT implementation, with the aim of achieving smart manufacturing