scholarly journals Closed-Loop Lifecycle Management of Service and Product in the Internet of Things: Semantic Framework for Knowledge Integration

Sensors ◽  
2016 ◽  
Vol 16 (7) ◽  
pp. 1053 ◽  
Author(s):  
Min-Jung Yoo ◽  
Clément Grozel ◽  
Dimitris Kiritsis
Author(s):  
Anthony D’Angelo ◽  
Edwin K. P. Chong

This paper establishes the baseline for incorporating the Internet of Things (IoT) into the Reliability-Risk model. The authors developed the original Reliability-Risk model as a “trade-off” tool for ranking conceptual designs as a function of reliability. We summarize the original Reliability-Risk model and algorithm and discuss the process of updating the standard Integration Definition Function Modeling (IDEF0) technique with the IoT. Inserting the updated IDEF0 into the Reliability-Risk modeling framework creates a dynamic closed-loop system. We identified a concept for using a probabilistic workflow to automate the new closed-loop system and discuss a Reliability-Risk sensitivity approach. The Reliability-Risk model ranked five conceptual packaging designs against 17 criteria for incorporation into the supply chain. The authors use a Multi-Criteria-Decision System (MCDS) to establish the rankings. The paper re-visits the original example to include data (the IoT) such as shock, temperature, and humidity obtained from various nodes in the logistics cycle. After the sensor data are incorporated, updated systems specification and reliability models resulted in a new ranking. We will discuss the results of the rankings. Current research in developing the Digital Twin and Digital Thread are lacking in the area of logistics modeling. The incorporation of Discrete Event Simulation models to simulate transportation, handling, and storage shows promise to address these shortcomings. Therefore, we will briefly discuss our approach on incorporating Discrete Event Simulation modeling into the Reliability-Risk-IoT model to create a “logistics twin.”


2020 ◽  
Vol 1684 ◽  
pp. 012020
Author(s):  
Guo-hua Qiu ◽  
Yingying Wang ◽  
Chenhui Zhou ◽  
Yajun Xia ◽  
Niansong Mei ◽  
...  

2020 ◽  
Vol 172 ◽  
pp. 105376 ◽  
Author(s):  
E. Wang ◽  
S. Attard ◽  
A. Linton ◽  
M. McGlinchey ◽  
W. Xiang ◽  
...  

2021 ◽  
Vol 6 (4) ◽  
pp. 66
Author(s):  
Lukai Tong

<p><span lang="EN-US">Nowadays, the Internet of Things is being used in various fields. Drainage is placed at the top of the priority in campus life. However, the current campus drainage system cannot meet people’s yearning for a better life, so the system needs to be optimized. The optimized drainage system is divided into four parts. Sensor part, communication part, cloud control part, water storage/drainage part, identification part. RFID and AI technology are used for identification, temperature, humidity and pressure sensors are used for perception, cloud computing technology is used for cloud control, WIFI technology is used for communication and water storage and drainage control has three modes: remote control, automatic closed-loop control and manual control. Drainage network with circular pipe network drainage system, to achieve intelligent, accurate goals.</span></p>


Author(s):  
Christos I. Papanagnou

AbstractClosed-loop supply chains are complex systems as they involve the seamless backward and forward flow of products and information. With the advent of e-commerce and online shopping, there has been a growing interest in product returns and the associated impact on inventory variance and the bullwhip effect. In this paper, a novel four-echelon closed-loop supply chain model is presented, where base-stock replenishment policies are modelled by means of a proportional controller. A stochastic state-space model is implemented, initially to capture the supply chain dynamics while the model is analysed under stationarity conditions with the aid of a covariance matrix. This allows the bullwhip effect to be expressed as a function of replenishment policies and product return rates. Next, an optimisation method is introduced to study the impact of the Internet of Things on inventory variance and the bullwhip effect. The results show that the Internet of Things can reduce costs associated with inventory fluctuations and eliminate the bullwhip effect in closed-loop supply chains.


2020 ◽  
pp. 1-12
Author(s):  
Zhang Caiqian ◽  
Zhang Xincheng

The existing stand-alone multimedia machines and online multimedia machines in the market have certain deficiencies, so they cannot meet the actual needs. Based on this, this research combines the actual needs to design and implement a multi-media system based on the Internet of Things and cloud service platform. Moreover, through in-depth research on the MQTT protocol, this study proposes a message encryption verification scheme for the MQTT protocol, which can solve the problem of low message security in the Internet of Things communication to a certain extent. In addition, through research on the fusion technology of the Internet of Things and artificial intelligence, this research designs scheme to provide a LightGBM intelligent prediction module interface, MQTT message middleware, device management system, intelligent prediction and push interface for the cloud platform. Finally, this research completes the design and implementation of the cloud platform and tests the function and performance of the built multimedia system database. The research results show that the multimedia database constructed in this paper has good performance.


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