Real-time capacity requirement planning for make-to-order manufacturing with variable time-window orders

A distributed data stream processing system handles real-time, changeable and sudden streaming data load. Its elastic resource allocation has become a fundamental and challenging problem with a fixed strategy that will result in waste of resources or a reduction in QoS (quality of service). Spark Streaming as an emerging system has been developed to process real time stream data analytics by using micro-batch approach. In this paper, first, we propose an improved SVR (support vector regression) based stream data load prediction scheme. Then, we design a spark-based maximum sustainable throughput of time window (MSTW) performance model to find the optimized number of virtual machines. Finally, we present a resource scaling algorithm TWRES (time window resource elasticity scaling algorithm) with MSTW constraint and streaming data load prediction. The evaluation results show that TWRES could improve resource utilization and mitigate SLA (service level agreement) violation.

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Dynamic Measurement of Spatial Attitude at Bottom Rotating Drillstring: Simulation, Experimental, and Field Test

Journal of Energy Resources Technology ◽

10.1115/1.4031742 ◽

2015 ◽

Vol 138 (2) ◽

Cited By ~ 2

Author(s):

Qilong Xue ◽

Ruihe Wang ◽

Baolin Liu ◽

Leilei Huang

Keyword(s):

Real Time ◽

Measurement Errors ◽

Time Window ◽

Measurement Data ◽

Movement Patterns ◽

Dynamic Measurement ◽

Drilling Process ◽

Stick Slip ◽

Actual Measurement ◽

Gas Drilling

In the oil and gas drilling engineering, measurement-while-drilling (MWD) system is usually used to provide real-time monitoring of the position and orientation of the bottom hole. Particularly in the rotary steerable drilling technology and application, it is a challenge to measure the spatial attitude of the bottom drillstring accurately in real time while the drillstring is rotating. A set of “strap-down” measurement system was developed in this paper. The triaxial accelerometer and triaxial fluxgate were installed near the bit, and real-time inclination and azimuth can be measured while the drillstring is rotating. Furthermore, the mathematical model of the continuous measurement was established during drilling. The real-time signals of the accelerometer and the fluxgate sensors are processed and analyzed in a time window, and the movement patterns of the drilling bit will be observed, such as stationary, uniform rotation, and stick–slip. Different signal processing methods will be used for different movement patterns. Additionally, a scientific approach was put forward to improve the solver accuracy benefit from the use of stick–slip vibration phenomenon. We also developed the Kalman filter (KF) to improve the solver accuracy. The actual measurement data through drilling process verify that the algorithm proposed in this paper is reliable and effective and the dynamic measurement errors of inclination and azimuth are effectively reduced.

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A single‐shot autocorrelator for the ultraviolet with a variable time window

Review of Scientific Instruments ◽

10.1063/1.1141207 ◽

1990 ◽

Vol 61 (3) ◽

pp. 998-1003 ◽

Cited By ~ 14

Author(s):

S. Szatmári ◽

F. P. Schäfer ◽

J. Jethwa

Keyword(s):

Time Window ◽

Single Shot ◽

Variable Time

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Analyzing EEG of Quasi-Brain-Death Based on Dynamic Sample Entropy Measures

Computational and Mathematical Methods in Medicine ◽

10.1155/2013/618743 ◽

2013 ◽

Vol 2013 ◽

pp. 1-6 ◽

Cited By ~ 4

Author(s):

Li Ni ◽

Jianting Cao ◽

Rubin Wang

Keyword(s):

Brain Death ◽

Real Time ◽

Time Window ◽

Approximate Entropy ◽

Sample Entropy ◽

Well Performance ◽

Entropy Measures ◽

Brain Death Determination ◽

Death Determination ◽

The Brain

To give a more definite criterion using electroencephalograph (EEG) approach on brain death determination is vital for both reducing the risks and preventing medical misdiagnosis. This paper presents several novel adaptive computable entropy methods based on approximate entropy (ApEn) and sample entropy (SampEn) to monitor the varying symptoms of patients and to determine the brain death. The proposed method is a dynamic extension of the standard ApEn and SampEn by introducing a shifted time window. The main advantages of the developed dynamic approximate entropy (DApEn) and dynamic sample entropy (DSampEn) are for real-time computation and practical use. Results from the analysis of 35 patients (63 recordings) show that the proposed methods can illustrate effectiveness and well performance in evaluating the brain consciousness states.

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Real-Time IoT-Based Production Planning and Control of Industrial Robots in an Automated Cyber-Physical Production System Under Dynamic Conditions: Lessons Learned from a Make-to-Order Usage Case

Computer Aided Systems Theory – EUROCAST 2019 - Lecture Notes in Computer Science ◽

10.1007/978-3-030-45096-0_59 ◽

2020 ◽

pp. 485-492

Author(s):

Joachim Berlak ◽

Julia Berg ◽

Michael Stangl ◽

Luciano Baumgart

Keyword(s):

Real Time ◽

Production Planning ◽

Production System ◽

Lessons Learned ◽

Industrial Robots ◽

Production Planning And Control ◽

Dynamic Conditions ◽

Planning And Control ◽

Make To Order ◽

And Control

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Right-time vs real-time pro-active construction safety and health system architecture

Construction Innovation ◽

10.1108/ci-10-2015-0049 ◽

2016 ◽

Vol 16 (3) ◽

pp. 253-280 ◽

Cited By ~ 15

Author(s):

Jochen Teizer

Keyword(s):

Supply Chain ◽

Real Time ◽

Occupational Safety ◽

Time Window ◽

Data Gathering ◽

Critical Time ◽

Construction Safety ◽

Content Type ◽

Safety And Health ◽

High Concern

Purpose The purpose of this paper is to investigate the critical time window for pro-active construction accident prevention and response. Large to small organisations throughout the entire construction supply chain continue to be challenged to adequately prevent accidents. Construction worker injuries and fatalities represent significant waste of resources. Although the five C’s (culture, competency, communication, controls and contractors) have been focusing on compliance, good practices and best-in-class strategies, even industry leaders have only marginal improvements in recorded safety statistics for many years. Design/methodology/approach Right-time vs real-time construction safety and health identifies three major focus areas to aid in the development of a strategic, as opposed to tactical, response. Occupational safety and health by design, real-time safety and health monitoring and alerts and education, training and feedback leveraging state-of-the-art technology provide meaningful predictive, quantitative and qualitative measures to identify, correlate and eliminate hazards before workers get injured or incidents cause collateral damage. Findings The current state and development of existing innovative initiatives in the occupational construction safety and health domain are identified. A framework for right-time vs real-time construction safety and health presents the specific focus on automated safety and health data gathering, analysis and reporting to achieve better safety performance. The developed roadmap for right-time vs real-time safety and health is finally tested in selected application scenarios of high concern in the construction industry. Originality/value A strategic roadmap to eliminate hazards and accidents through right-time vs real-time automation is presented that has practical as well as social implications on conducting a rigorous safety culture and climate in a construction business and its entire supply chain.

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