To better cope with the Internet usage shift from host-centric end-to-end communication to receiver-driven content retrieval, innovative information-centric networking (ICN) architectures have been proposed. With explosive increase in global network traffic, energy efficiency issue ICN is a growing concern. A number of approaches proposed address energy-efficiency ICN. However, several significant research challenges remain be addressed before its widespread deployment, including shutdown,...

Recently, a series of innovative information-centric networking (ICN) architectures have been designed to better address the shift from host-centric end-to-end communication requester-driven content retrieval. With explosive increase mobile data traffic, mobility issue in ICN is growing concern and number approaches proposed deal with problem ICN. Despite potential advantages wireless environments, several significant research challenges remain be addressed before its widespread deployment,...

Unexpected disruptive events in manufacturing systems always interrupt normal production conditions and cause loss. A resilient system should be designed with the capability to suffer minimum loss during disruptions, settle itself steady state quickly after each disruption. In this paper, we define (PL), throughput settling time (TST), total underproduction (TUT) as three metrics measure resilience, use these measures assist design of multi-stage reconfigurable systems. Numerical case...

Manufacturing has adopted technologies such as automation, robotics, industrial Internet of Things (IoT), and big data analytics to improve productivity, efficiency, capabilities in the production environment. Modern manufacturing workers not only need be adept at traditional but also ought trained advanced data-rich computer-automated technologies. This study analyzes science (DSA) skills gap today's workforce identify critical technical domain knowledge required for intelligent...

With the rapid development of artificial intelligence (AI) in recent years, fault diagnostics for industrial applications have leaped toward partially or fully automatic provided by capability analyzing massive condition monitoring data from sensors and actuators. Generally, AI-based can achieve high accuracy when failure types appear training dataset testing are same. These diagnostic methods could be invalidated dealing with unprecedented faults because pretrained classifier tends to...

Abstract In recent years, driven by Industry 4.0 wave, academic research has focused on the science, engineering, and enabling technologies for intelligent cyber manufacturing. Using a network science data mining-based Keyword Co-occurrence Network (KCN) methodology, this work analyzes trends in topics manufacturing literature over past two decades to inform researchers, educators, industry leaders of knowledge It studies evolution methods Internet Things (IoT), cloud computing, The KCN...

A research study was conducted (1) to examine the practices employed by US manufacturers achieve productivity goals and (2) understand what level of intelligent maintenance technologies strategies are being incorporated into these practices. This found that effectiveness choice strategy were strongly correlated size manufacturing enterprise; there large differences in adoption advanced diagnostics prognostics between small medium-sized enterprises (SMEs). Despite their greater technologies,...

The goals of this paper are to 1) examine the current practices diagnostics, prognostics, and maintenance employed by United States (U.S.) manufacturers achieve productivity quality targets 2) understand present level technologies strategies that being incorporated into these practices. A study is performed contrast impact various industry-specific factors on effectiveness profitability implementation prognostics health management technologies, using both surveys case studies a sample U.S....

This paper studies optimal policy for modular product reassembly within a remanufacturing setting where firm receives returns with variable quality and reassembles products of multiple classes to customer orders. High-quality modules are allowed substitute low-quality during provide the system flexibility such that shortage in lower can be smoothed out by higher module inventories. We formulate problem as Markov decision process characterize structure control policy. In particular, we show...

In this paper, we investigate hidden opportunities for performing proper maintenance tasks during production time without causing losses. One of the on a machine is when starved or blocked due to occurrence random failures its upstream downstream machines. Such failure-induced starvation blockage defined as passive opportunity window (PMOW), and predicted bottleneck machines in manufacturing systems with different configurations. The effectiveness PMOW prediction algorithm validated through...

Abstract Roll-to-Roll (R2R) systems, featuring motorized or idle rollers, are crucial for high-volume, continuous production of flexible substrates. A significant challenge in R2R printing processes is maintaining tight alignment tolerances multi-layer printed electronics. This alignment, known as registration, complicated by the deformability substrates and complex roller dynamics, leading to registration errors (RE) caused variations substrate tensions speeds. Despite using real-time...

Multi-Agent Reinforcement Learning (MARL) presents a promising approach for addressing the complexity of Traffic Signal Control (TSC) in urban environments. However, existing platforms MARL-based TSC research face challenges such as slow simulation speeds and convoluted, difficult-to-maintain codebases. To address these limitations, we introduce PyTSC, robust flexible environment that facilitates training evaluation MARL algorithms TSC. PyTSC integrates multiple simulators, SUMO CityFlow,...