Smart manufacturing enabled by continuous monitoring and control of polymer characteristics

2020 ◽  
pp. 257-308
Author(s):  
Michael F. Drenski ◽  
Alex W. Reed ◽  
Aide Wu ◽  
Wayne F. Reed
Keyword(s):  
Continuous Monitoring ◽  
Smart Manufacturing ◽  
Monitoring And Control ◽  
And Control

Asset Integrity Management – Natural Gas Slug Catcher Facility

2014 ◽  
Author(s):  
D.. Williams ◽  
A.. Boodoosingh
Keyword(s):  
Natural Gas ◽  
Continuous Monitoring ◽  
Integrated Approach ◽  
Process Control System ◽  
Monitoring And Control ◽  
Operational Strategies ◽  
Maintenance System ◽  
Integrity Management ◽  
And Control ◽  
Management Report

Abstract Reliable operations of the Natural Gas {Slug catcher} Facility are heavily dependent on flawless operations and also the maintenance system implemented. The maintenance system is driven by the Asset Integrity Management System (AIMS), which incorporates corrosion control, equipment maintenance, pipeline operations and vessel inspection. This system is also supported by continuous monitoring and control using a Process Control System for the natural gas facility. This paper presents an integrated approach to operations of the Slug catcher facility based on AIMS and operational strategies, which are implemented to ensure efficient and effective operations. Additionally, recommendations for further improvement are documented based on a recent Asset Integrity Management Report.

scholarly journals Towards smart biomanufacturing: a perspective on recent developments in industrial measurement and monitoring technologies for bio-based production processes

2020 ◽  
Vol 47 (11) ◽  
pp. 947-964 ◽  
Author(s):  
Carina L. Gargalo ◽  
Isuru Udugama ◽  
Katrin Pontius ◽  
Pau C. Lopez ◽  
Rasmus F. Nielsen ◽  
...  
Keyword(s):  
Industrial Revolution ◽  
Control Strategies ◽  
Smart Manufacturing ◽  
Monitoring And Control ◽  
Large Sets ◽  
Production Processes ◽  
Recent Developments ◽  
Monitoring Technologies ◽  
And Control ◽  
Industrial Measurement

AbstractThe biomanufacturing industry has now the opportunity to upgrade its production processes to be in harmony with the latest industrial revolution. Technology creates capabilities that enable smart manufacturing while still complying with unfolding regulations. However, many biomanufacturing companies, especially in the biopharma sector, still have a long way to go to fully benefit from smart manufacturing as they first need to transition their current operations to an information-driven future. One of the most significant obstacles towards the implementation of smart biomanufacturing is the collection of large sets of relevant data. Therefore, in this work, we both summarize the advances that have been made to date with regards to the monitoring and control of bioprocesses, and highlight some of the key technologies that have the potential to contribute to gathering big data. Empowering the current biomanufacturing industry to transition to Industry 4.0 operations allows for improved productivity through information-driven automation, not only by developing infrastructure, but also by introducing more advanced monitoring and control strategies.

scholarly journals Classification of Actigraphy Records from Bipolar Disorder Patients Using Slope Entropy: A Feasibility Study

Entropy ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. 1243
Author(s):  
David Cuesta-Frau ◽  
Jakub Schneider ◽  
Eduard Bakštein ◽  
Pavel Vostatek ◽  
Filip Spaniel ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Continuous Monitoring ◽  
Monitoring And Control ◽  
Term Evolution ◽  
Entropy Measures ◽  
High Prevalence ◽  
Technological Developments ◽  
And Control

Bipolar Disorder (BD) is an illness with high prevalence and a huge social and economic impact. It is recurrent, with a long-term evolution in most cases. Early treatment and continuous monitoring have proven to be very effective in mitigating the causes and consequences of BD. However, no tools are currently available for a massive and semi-automatic BD patient monitoring and control. Taking advantage of recent technological developments in the field of wearables, this paper studies the feasibility of a BD episodes classification analysis while using entropy measures, an approach successfully applied in a myriad of other physiological frameworks. This is a very difficult task, since actigraphy records are highly non-stationary and corrupted with artifacts (no activity). The method devised uses a preprocessing stage to extract epochs of activity, and then applies a quantification measure, Slope Entropy, recently proposed, which outperforms the most common entropy measures used in biomedical time series. The results confirm the feasibility of the approach proposed, since the three states that are involved in BD, depression, mania, and remission, can be significantly distinguished.

Smart Manufacturing: State-of-the-Art Review in Context of Conventional and Modern Manufacturing Process Modeling, Monitoring and Control

2018 ◽  
Author(s):  
Parikshit Mehta ◽  
Prahalada Rao ◽  
Zhenhua (David) Wu ◽  
Vukica Jovanović ◽  
Olga Wodo ◽  
...  
Keyword(s):  
Process Modeling ◽  
Manufacturing Process ◽  
Industry 4.0 ◽  
Data Science ◽  
State Of The Art ◽  
Smart Manufacturing ◽  
Future Research ◽  
High Tech ◽  
Monitoring And Control ◽  
And Control

With the advances in automation technologies, data science, process modeling and process control, industries worldwide are at the precipice of what is described as the fourth industrial revolution (Industry 4.0). This term was coined in 2011 by the German federal government to define their strategy related to high tech industry [1], specifically multidisciplinary sciences involving physics-based process modeling, data science and machine learning, cyber-physical systems, and cloud computing coming together to drive operational excellence and support sustainable manufacturing. The boundaries between Information Technologies (I.T.) and Operation Technologies (O.T.) are quickly dissolving and the opportunities for taking lab-scale manufacturing science research to plant and enterprise wide deployment are better than ever before. There are still questions to be answered, such as those related to the future of manufacturing research and those related to meeting such demands with a highly skilled workforce. Furthermore, in this new environment it is important to understand how process modeling, monitoring, and control technologies will be transformed. The aim of the paper is to provide state-of-the-art review of Smart Manufacturing and Industry 4.0 within scope of process monitoring, modeling and control. This will be accomplished by giving comprehensive background review and discussing application of smart manufacturing framework to conventional (machining) and advanced (additive) manufacturing process case studies. By focusing on process modeling, monitoring, analytics, and control within the larger vision of Industry 4.0, this paper will provide a directed look at the efforts in these areas, and identify future research directions that would accelerate the pace of implementation in advanced manufacturing industry.

scholarly journals Internet of things for industrial monitoring and control applications

2018 ◽  
Vol 7 (2.21) ◽  
pp. 280 ◽  
Author(s):  
R A. Karthika ◽  
Shaik Rahamtula ◽  
Yalavarthi Anusha
Keyword(s):  
Continuous Monitoring ◽  
Control Algorithms ◽  
Raspberry Pi ◽  
Monitoring And Control ◽  
Credit Score ◽  
Score Card ◽  
Industrial Monitoring ◽  
Processing Control ◽  
And Control ◽  
E Mail

Smart enterprise is an observing, controlling and investigating carrier which incorporates wireless transmission generation and electronic sensor innovation. It permits the client to get the overall scope of services, the opportunity for continuous monitoring and automated controlling of industrial environment.  This paper was advanced to provide internet based totally smoke and temperature and security tracking. This device is allowed to track the facts every time & everywhere from the source of the internet whenever we login into internet. This paper also concludes that person can set restriction for above parameters & if these parameters cross beyond that cost, it's going to activate the devices. As a part of its alarm gadget, it'll play the recorded sounds: “intruder” or “smoke detected” when there may be a detection. The credit score card size Raspberry Pi (RPI) with Open source pc vision (OpenCV) software program handles the photo processing, control algorithms for the alarms and sends captured snap shots to consumer’s e mail through wireless. In this project Raspberry Pi3B+ is used.  

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