Fog Computing for Distributed Family Learning in Cyber-Manufacturing Modeling

Distributed data filtering and modeling for fog and networked manufacturing

“…has significantly improved manufacturing productivity and flexibility, ensured product quality, and reduced the manufacturing cost. Fog Computing extends the Cloud Computing paradigm close to the "Edge" of the manufacturing network [1], i.e., near the manufacturing equipment, processes and data [2], thus improving the performance of runtime metrics, such as time latency of the computation services and the communication bandwidth utilization [3]. In this paper, Fog is defined as low-cost computation devices, including Edge and other devices between Edge and Cloud [4].…”

Bayesian Sparse Regression for Mixed Multi-Responses with Application to Runtime Metrics Prediction in Fog Manufacturing

“…The concept of Fog manufacturing is defined on integrating a Fog computing network with interconnected manufacturing processes, facilitates, and systems. With local computation units (i.e., Fog units) close to the manufacturing processes, the Cloud-based centralized computation architecture can be evolved to a Cloud-Fog collaborative computation to provide higher responsiveness and significantly lower time latency (Wu et al 2017;Zhang et al 2019). There is a trade-off between the local computing efficiency on a Fog unit and the global collaborative efficiency of the centralized Cloud.…”

“…These metrics include the CPU utilization (i.e., continuous response), temperature of the CPU (i.e., continuous response), the number of computation tasks executed within a certain time period (i.e., counting response), and whether the memory utilization exceeds certain thresholds (i.e., binary response). Prediction and uncertainty quantification of these metrics are essential to support the computation in the Fog manufacturing, advancing analytics and optimization for high responsiveness and reliability (Wu et al 2017;Zhang et al 2019). Based on the runtime performance metrics of these Fog nodes, the Fog computing can dynamically assign computation tasks to different Fog nodes (Chen et al 2018).…”

“…Design of experiments for the analysis of runtime performance metrics (summarized fromZhang et al (2019) with authors' permission).…”

Challenges of modeling and analysis in cybermanufacturing: a review from a machine learning and computation perspective

“…This will allow the workforce to focus more on the insight-needed and situation-dependent tasks, such as business planning and new process/product development, rather than the basic and repetitive tasks (Chen and Jin 2017). In this direction, the concept of computation services in manufacturing has been proposed , to describe a situation where manufacturing data is automatically collected and processed in ubiquitous computation units, such as the Cloud and the Fog nodes Zhang et al 2019). The goal is to provide real-time or online computation results and meet on-demand computation requests from manufacturing processes, systems, and users for decision-making.…”