24,570 Results Found

This study established a real-time measurement system to monitor the melt quality in an injection molding process using a pressure sensor installed on the nozzle and a strain gauge installed on the tie bar. Based on the sensing curves from these two...

In the manufacturing of parts, the machining process is a critical factor for ensuring product quality. Process condition monitoring is essential for this process. Traditional monitoring approaches that usually use static thresholds are inefficient a...

A configurable process Change Mining approach can detect changes from a collection of event logs and provide details on the unexpected behavior of all process variants of a configurable process. The strength of Change Mining lies in its ability to se...

Within the scope of this article, the problem of the formalization of physical processes in adaptive training complexes is considered on the example of virtual objects burning. Despite a fairly complete study of this process, the existing mathematica...

The injection-molding process is a non-linear process, and the product quality and long-term production stability are affected by several factors. To stabilize the product quality effected by these factors, this research establishes a standard proces...

In the context of Industry 4.0, Artificial Intelligence (AI) methods are used to maximize the efficiency and flexibility of production processes. The adaptive management of such semantic processes can optimize energy and resource efficiency while pro...

Submesoscale processes, characterized by strong vertical velocities that generate sea surface temperature (SST) fronts as well as O(1) Rossby number (Ro), are critical to ocean mixing and biogeochemical transport, yet their observation is hampered by...

The operation of CNC machining centers, despite their technological progress, can still be affected by undesirable events associated with the technological parameters of their operation. The minimization of these risks can be achieved via their adapt...

Injection molding is a highly nonlinear procedure that is easily influenced by various external factors, thereby affecting the stability of the product’s quality. High-speed injection molding is required for production due to the rapid cooling...

Injection molding is a popular process for the mass production of polymer products, but due to the characteristics of the injection process, there are many factors that will affect the product quality during the long fabrication processes. In this st...

Stochastic variations of the operation conditions and the resultant variations of the aerodynamic performance in Low-Pressure Turbine (LPT) can often be found. This paper studies the aerodynamic performance impact of the uncertain variations of flow...

Integrated process planning and scheduling (IPPS) is an intricate and vital issue in smart manufacturing, requiring the coordinated optimization of both process plans and production schedules under multiple resource and precedence constraints. This p...

The application of deoiling hydrocyclone systems as the downstream of three-phase gravity separator (TPGS) systems is one of the most commonly deployed produced water treatment processes in offshore oil and gas production. Due to the compact system&r...

The research on seafloor massive sulfide (SMS) started relatively late, and the results on its breaking process are few. However, the breaking process contains evaluation indexes of safe, efficient and low-disturbance mining, so it is necessary to st...

Kinematic calibration plays a pivotal role in enhancing the absolute positioning accuracy of industrial robots, with parameter identification and error compensation constituting its core components. While the conventional parameter identification met...

To address the challenges of complex harmonic characteristics, multi-source coupling, and strong time variability in aggregated loads downstream of high-voltage substations, this paper proposes an Adaptive Multi-Task Gaussian Process Regression (AMT-...

Introduction: Industry 4 [...]

The adaptability of an in-progress business process is an essential requirement for any business process management system in dynamic business process environments. Over the last two decades, the artifact-centric approach for business process managem...

A new requirement for the manufacturing companies in Industry 4.0 is to be flexible with respect to changes in demands, requiring them to react rapidly and efficiently on the production capacities. Together with the trend to use Service-Oriented Arch...

In the past decade, Unmanned Aerial Vehicles (UAVs) have garnered significant attention across diverse applications, including surveillance, cargo shipping, and agricultural spraying. Despite their widespread deployment, concerns about maintaining st...

We investigated the conceptual processing of nouns referring to objects characterized by a highly typical color and orientation. We used a go/no-go task in which we asked participants to categorize each noun as referring or not to natural entities (e...

With the continuous complexity and frequent changes in business application scenarios, companies urgently need to establish a flexible business process management mechanism that includes dynamic rules, in which dynamic adaptation methods of business...

This article presents a comparative study on the development and application of two distinct adaptive control algorithms for biomass specific growth rate control in fed-batch biotechnological processes. A typical fed-batch process using Escherichia c...

This paper explores how climate change adaptation concerns were integrated into the Swedish forestry debate and policy process during the period of 1990–2012, and draws lessons on barriers and opportunities identified in this process. Using a framewo...

The ultrafast laser processing of three-dimensional structures characterized by highly spatially resolved features is more efficiently realized by implementing adaptive optics. Adaptive optics allow for the correction of optical aberrations, introduc...

Learning environments ensure successful implementation of the learning process but not always the effective design of the e-learning objects (ELOs) and moreover, search and adaptation. A technological solution for the design of the learning objects,...

This article presents a mathematical model of cyclical economic processes, formulated as the sum of a deterministic polynomial function and a cyclic random process that simultaneously captures trend, stochasticity, cyclicity, and rhythm variability....

The milk pasteurization process is nonlinear in nature, and for this reason, the application of linear control algorithms does not guarantee the obtainment of the required performance in every condition. The problem is here addressed by proposing an...

Efficient matching of incoming events of data streams to persistent queries is fundamental to event stream processing systems in wireless sensor networks. These applications require dealing with high volume and continuous data streams with fast proce...

The discriminability and transferability of models are two important factors for the success of domain adaptation methods. Recently, some domain adaptation methods have improved models by adding a discriminant information extraction module. However,...

This paper presents a novel class of self-organizing sensing agents that adaptively learn an anisotropic, spatio-temporal Gaussian process using noisy measurements and move in order to improve the quality of the estimated covariance function. This ap...

Fetal electrocardiography is among the most promising methods of modern electronic fetal monitoring. However, before they can be fully deployed in the clinical practice as a gold standard, the challenges associated with the signal quality must be sol...

Visual quality inspection of part surfaces is a crucial step in industrial production. Image edge detection is a common technique for assessing the surface conditions of parts. However, current methods have limitations, including poor noise filtering...

Syntactic adaptation effects have been demonstrated for an expanding list of structure types, but the mechanism underlying this effect is still being explored. In the current work on filler-gap dependency processing, we examined whether exposing part...

Predictive maintenance (PM) algorithms are widely applied for detecting operational anomalies on industrial processes to schedule for a maintenance intervention before a possible breakdown; however, much less focus has been devoted to the use of such...

This article presents the development and application of a distinct adaptive control algorithm that is based on fuzzy logic and was used to control the specific growth rate (SGR) in a fed-batch biotechnological process. The developed control algorith...

Factories of the future are foreseen to evolve into smart factories with autonomous and adaptive manufacturing processes. However, the increasing complexity of the network of manufacturing processes is expected to complicate the rapid detection of pr...

Graphics processing units and video cards have seen a surge of usage in domains other than graphics computers, due to advances in hardware and software technologies; however, little uptake has been in the domain of systems engineering and real time c...

The remaining useful life (RUL) prediction is important for improving the safety, supportability, maintainability, and reliability of modern industrial equipment. The traditional data-driven rolling bearing RUL prediction methods require a substantia...

Globally, the architecture, engineering, construction, and operations (AECO) industry faces rapid urbanization and environmental urgency. However, developing economies often lack the strategic capacity to utilize BIM for sustainable development. This...

While the province of British Columbia (BC), Canada, provides guidelines for flood risk management, it is local governments’ responsibility to delineate their own flood vulnerability, assess their risk, and integrate these with planning policies to i...

Adaptive laboratory evolution (ALE) is a valuable complementary tool for modern strain development. Insights from ALE experiments enable the improvement of microbial cell factories regarding the growth rate and substrate utilization, among others. Mo...

Space-time adaptive processing (STAP) approaches based on sparse Bayesian learning (SBL) have attracted much attention for the benefit of reducing the training samples requirement and accurately recovering sparse signals. However, it has the problem...

Lithium-ion batteries (LiBs) are the most important part of electric vehicle (EV) systems. Because there are two different degradation rates during LiB degradation, there are many two-phase models for LiBs. However, most of these methods do not consi...

Space-time adaptive processing (STAP) techniques have been motivated as a key enabling technology for advanced airborne radar applications. In this paper, a slow-time code design is considered for the STAP technique in airborne radar, and the princip...

The article presents a new space-time adaptive processing (STAP) method for target detection in a heterogeneous and non-stationary environment. In study it was proven that it is possible to estimate the clutter covariance matrix (CCM) in STAP by usin...

This paper proposes two modified space time adaptive processing (STAP) methods based on piecewise sub-apertures and data constraints for non-stationary interference cancellation in synthetic aperture radar (SAR) applications. In these methods, the en...

To tackle the challenge of enhancing moving target detection performance in environments characterized by small sample sizes and non-uniformity, methods rooted in sparse signal reconstruction have been incorporated into Space-Time Adaptive Processing...

Exponentially weighted moving average (EWMA) and Shewhart control charts are commonly utilized to detect the small to moderate and large shifts in the process mean, respectively. This article introduces a novel Bayesian AEWMA control chart that emplo...

This paper provides the modeling, implementation, and simulation of fractional-order processes associated with the production of the enriched 13C isotope due to chemical exchange processes between carbamate and CO2. To demonstrate and simulate the pr...