Cleanroom Fan Energy Reduction—Airflow Control Retrofit Based on Continuous, Real-time Particle Sensing

Abstract Cleanrooms are utilized in electronics, semiconductor, aerospace, pharmaceutical, automotive, optical, medical device, and food processing facilities where air cleanliness is required to prevent defects in high-tech or high-value products. Compared to general commercial space, cleanrooms typically use 5 to 50 times the energy for the same area. One key reason is the high volume of conditioned and filtered air required to make the room air cleaner, which is measured in room-average particle concentration. The technology in this study uses real-time continuous particle sensors as feedback signals to automatically adjust fan speed. The system can modulate fan speed and provide the correct amount of airflow into the cleanroom to prevent over-supply and save energy. In typical manufacturing cleanrooms, the unoccupied state (evenings and weekends) is approximately two times longer than the occupied state (operational work hours), and particle generation (from personnel, equipment, and process) is much lower during the unoccupied state. Limited components and parts are required to apply the technology in this study into the design of a new cleanroom or to integrate the technology into existing cleanroom fan systems.

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Overview of Forming and Formability Issues for High Volume Aluminium Car Body Panels

Materials Science Forum ◽

10.4028/www.scientific.net/msf.519-521.795 ◽

2006 ◽

Vol 519-521 ◽

pp. 795-802 ◽

Cited By ~ 7

Author(s):

Dominique Daniel ◽

Gilles Guiglionda ◽

Pierre Litalien ◽

Ravi Shahani

Keyword(s):

New Technologies ◽

High Volume ◽

Production Lines ◽

Particle Generation ◽

Car Body ◽

Conventional Technology ◽

Sheet Products ◽

Cost Efficient ◽

Aluminum Panels ◽

Fine Tune

Cost-efficient designs of aluminum autobody structures consist mainly of stampings using conventional technology. Progress in metallurgy and forming processes has enabled aluminum body panels to achieve significant market share, particularly for hoods. Fast bake hardening alloys with better hemming performance were developed for improved outer panel sheet products. Specific guidelines for handling and press working were established to form aluminum panels using similar schedules and production lines as steel parts. Stamping productivity was improved by optimization of the trimming process to reduce sliver/particle generation and resulting end-of-line manual rework. Both hemming formability and trimming quality not only depend on tooling setup but also on microstructural features, which govern intrinsic alloy ductility. Targets for the next high volume aluminum car body applications, such as roof panels and doors, require higher strength and/or better formability. The challenges of complex stampings can be met with optimized alloys and lubricants, with improved numerical simulation to fine-tune stamping process parameters, and with the introduction of new technologies. Warm forming was examined as a potential breakthrough technology for high volume stamping of complex geometries.

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Evaluation on Combustion Properties of Nanoparticle as Fuel Additive

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.335-336.1516 ◽

2011 ◽

Vol 335-336 ◽

pp. 1516-1519 ◽

Cited By ~ 3

Author(s):

Yong Qiang Ren ◽

Zhi Ning Huang ◽

Yan Fu

Keyword(s):

Liquid Paraffin ◽

Fuel Additive ◽

Average Particle ◽

X Ray ◽

Paraffin Oil ◽

Transmission Electron ◽

Combustion Properties ◽

Fuel Oils ◽

Save Energy ◽

Similar Crystal Structure

To improve combustion properties of fuel oils, save energy and reduce pollution, the metal nanoparticles modified by fatty acids have been prepared. The dispersion capacities of these modified nanoparticles in liquid paraffin oil were examined, and were characterized by X-ray powder diffraction (XRD), transmission electron microscopy (TEM), Fourier transform infrared spectrum (FTIR) . The results show they possess similar crystal structure as organic shell, and average particle diameters, which are in agreement with their excellent oil-solubilities. Moreover, the properties of the modified nanoparticles additives in boiler fuel were evaluated by means of oxygen bomb relative method as regards energy saving and residual products lowering. The results show that the efficiency of combustion and decrement of residual products for fuels were improved to different degree. Therefore, notable economic and social benefits are brought.

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Research on the Efficient Application of Silica Fume in High-Tech Cement-Based Materials

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.374-377.1537 ◽

2011 ◽

Vol 374-377 ◽

pp. 1537-1540

Author(s):

Dong Lin ◽

Zi Yun Wen

Keyword(s):

Compressive Strength ◽

Silica Fume ◽

Packing Density ◽

Particle Diameter ◽

High Tech ◽

Average Particle ◽

Average Particle Diameter ◽

Cement Based Materials ◽

Pre Treatment

The comparison experiments are carried out at different silica fume dosage between the silica fume with pre-treatment and the silica fume without pre-treatment. The results show that the pre-treatment of silica fume improved the strength greatly and the silica fume dosage corresponding to the strength peak somewhat moved forward from 0.20 for the cement-based materials with pre-treatment of silica fume to 0.21 for the cement-based materials without pre-treatment of silica fume. The particles distribution experiment results indicate that after the pre-treatment of silica fume, the average particle diameter of silica fume reduced from 2.865μｍto 0.151μｍ. Based on Aim-Goff model, it is concluded that the increase in the compressive strength and flextural strength of cement-based materials with pre-treatment of silica fume, are attributed to the dispersion of silica fume agglomeration and the increase in the packing density of the cement-based materials.

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Service Discovery Framework for Distributed Embedded Real-Time Systems

Advances in Systems Analysis, Software Engineering, and High Performance Computing - Handbook of Research on Emerging Advancements and Technologies in Software Engineering ◽

10.4018/978-1-4666-6026-7.ch007 ◽

2014 ◽

pp. 126-147 ◽

Cited By ~ 1

Author(s):

Furkh Zeshan ◽

Radziah Mohamad ◽

Mohammad Nazir Ahmad

Keyword(s):

Web Services ◽

Real Time ◽

Context Awareness ◽

Service Discovery ◽

Low Cost ◽

High Volume ◽

Heterogeneous Environments ◽

Real Time Systems ◽

Loosely Coupled ◽

Time Systems

Embedded systems are supporting the trend of moving away from centralised, high-cost products towards low-cost and high-volume products; yet, the non-functional constraints and the device heterogeneity can lead to system complexity. In this regard, Service-Oriented Architecture (SOA) is the best methodology for developing a loosely coupled, dynamic, flexible, distributed, and cost-effective application. SOA relies heavily on services, and the Semantic Web, as the advanced form of the Web, handles the application complexity and heterogeneity with the help of ontology. With an ever-increasing number of similar Web services in UDDI, a functional description of Web services is not sufficient for the discovery process. It is also difficult to rank the similar services based on their functionality. Therefore, the Quality of Service (QoS) description of Web services plays an important role in ranking services within many similar functional services. Context-awareness has been widely studied in embedded and real-time systems and can also play an important role in service ranking as an additional set of criteria. In addition, it can enhance human-computer interaction with the help of ontologies in distributed and heterogeneous environments. In order to address the issues involved in ranking similar services based on the QoS and context-awareness, the authors propose a service discovery framework for distributed embedded real-time systems in this chapter. The proposed framework considers user priorities, QoS, and the context-awareness to enable the user to select the best service among many functional similar services.

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Data-driven decision support under concept drift in streamed big data

Complex & Intelligent Systems ◽

10.1007/s40747-019-00124-4 ◽

2019 ◽

Vol 6 (1) ◽

pp. 157-163 ◽

Cited By ~ 2

Author(s):

Jie Lu ◽

Anjin Liu ◽

Yiliao Song ◽

Guangquan Zhang

Keyword(s):

Decision Making ◽

Big Data ◽

Real Time ◽

Concept Drift ◽

High Volume ◽

Streaming Data ◽

Data Driven ◽

Research Directions ◽

Decision Outcomes ◽

Past Data

Abstract Data-driven decision-making ($$\mathrm {D^3}$$D3M) is often confronted by the problem of uncertainty or unknown dynamics in streaming data. To provide real-time accurate decision solutions, the systems have to promptly address changes in data distribution in streaming data—a phenomenon known as concept drift. Past data patterns may not be relevant to new data when a data stream experiences significant drift, thus to continue using models based on past data will lead to poor prediction and poor decision outcomes. This position paper discusses the basic framework and prevailing techniques in streaming type big data and concept drift for $$\mathrm {D^3}$$D3M. The study first establishes a technical framework for real-time $$\mathrm {D^3}$$D3M under concept drift and details the characteristics of high-volume streaming data. The main methodologies and approaches for detecting concept drift and supporting $$\mathrm {D^3}$$D3M are highlighted and presented. Lastly, further research directions, related methods and procedures for using streaming data to support decision-making in concept drift environments are identified. We hope the observations in this paper could support researchers and professionals to better understand the fundamentals and research directions of $$\mathrm {D^3}$$D3M in streamed big data environments.

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