Risk Management via Digital Dashboards in Statistics Data Centers

2020 ◽  
Vol 13 (1) ◽  
pp. 27-45
Author(s):  
Atif Amin ◽  
Raul Valverde ◽  
Malleswara Talla
Keyword(s):  
Risk Management ◽  
Real Time ◽  
Data Center ◽  
Cost Effective ◽  
Risk Level ◽  
Total Risk ◽  
Counter Measures ◽  
Effective Manner ◽  
Risk Managers

Every system, when connected to a network, is susceptible to threat of being hacked. It is important to protect all systems of an organization in real-time in a cost-effective manner. This article presents a well-designed and integrated database for risk management data using a dashboard interface in real-time risk that makes it easy for risk managers to reach a understanding the level of threats to be able to apply right controls to mitigate them. In this article, a case study of a data center for a statistical management institute is presented that proposes the calculation of total risk at the organization level by using the proposed risk database. A digital dashboard is also designed for presenting the risk level results so that decision makers can apply counter measures. The risk level on a dashboard viewer makes it easy for decision maker to understand the overall risk level at the statistics data center and assists in the creation of a tool to follow-up risk management since the time a threat hits until the time of its mitigation.

scholarly journals A Framework for Risk Assessment in Collaborative Networks to Promote Sustainable Systems in Innovation Ecosystems

2020 ◽  
Vol 12 (15) ◽  
pp. 6218
Author(s):  
Ricardo Santos ◽  
António Abreu ◽  
Ana Dias ◽  
João M.F. Calado ◽  
Vitor Anes ◽  
...  
Keyword(s):  
Risk Management ◽  
Open Innovation ◽  
System Development ◽  
Human Perception ◽  
Systems Development ◽  
Collaborative Networks ◽  
System Component ◽  
Risk Level ◽  
Sustainable Systems

Nowadays—and due to an increasingly competitive world—organizations need to collaborate in an open innovation context to be efficient and effective by achieving high levels of innovation with their products and services. However, the existing resources—as well as the innovation achieved from the diversity of partners involved—brings challenges to the management; in particularly with risk management. To fulfill such needs, risk management frameworks have been created to support managers, on preventing threats with systems development, although without properly account the influence of each system component, on the entire system, as well as the subjectivity within human perception. To account for these issues, a framework supported by fuzzy logic is presented in this work, to evaluate the risk level on system development in open innovation environment. The approach robustness is assessed by using a case study, where the challenges and benefits found are discussed.

Real-Time Process Quality Monitoring Using Wireless Sensor-Embedded Rotary Tools for Fastening Operations

2007 ◽  
Author(s):  
Deepak T. Mohan ◽  
Jeffrey Birt ◽  
Can Saygin ◽  
Jaganathan Sarangapani
Keyword(s):  
Real Time ◽  
Lead Time ◽  
Value Added ◽  
Cost Effective ◽  
Base Station ◽  
Embedded Sensors ◽  
Optical Encoder ◽  
Effective Manner ◽  
Rotary Type

Fastening operations are extensively used in the aerospace industry and constitute for more than a quarter of the total cost. Inspection of fasteners is another factor that adds cost and complexity to the overall process. Inspection is usually carried out on a sampling-basis as a stand-alone process after the fastening process is completed. Lack of capability to inspect all fasteners in a cost effective manner and the need to remove non-value added activities, such as inspection by itself, in order to reduce the manufacturing lead time have been the motivation behind this study. This paper presents a novel diagnostics scheme based on Mahalanobis-Taguchi System (MTS) for monitoring the quality of rotary-type fastening operations in real-time. This approach encompasses (1) integrating a torque sensor, a pressure sensor, and an optical encoder on a hand-held rotary-type fastening tool; (2) obtaining process parameters via the embedded sensors and generating process signatures in real-time; and (3) detecting anomalies on the tool using a wireless mote that communicates the decision with a base station. The anomalies investigated in this study are the grip length variations as under grip and normal grip, and presence of re-used fasteners. The proposed scheme has been implemented on prototype rotary tool for bolt-nut type of fasteners and tested under a variety of experimental settings. The experimental results have shown that the proposed approach is successful, with an accuracy of over 95% in detecting grip lengths of fasteners in real-time during the process.

scholarly journals Regional transportation development for development at fertilizer plants in North Sumatra (case study)

2018 ◽  
Vol 236 ◽  
pp. 02012
Author(s):  
Ikhsan Siregar ◽  
Mangara M. Tambunan
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Risk Mitigation ◽  
Risk Level ◽  
Urea Fertilizer ◽  
Analysis And Evaluation ◽  
Mitigation Action ◽  
Transportation Development ◽  
North Sumatra

Supply chain activity has an opportunity for the occurrence of risk. Therefore, risk management is needed in the handling of risk with the aim to minimize the risk level and impact of those risks. PT. XYZ of PT Pupuk Indonesia (Persero) engaged in the fertilizer industry. The main product produced is urea fertilizer. In the production process, the factory is supported by adequate production facilities and international standard technology. Currently, PT XYZ does not yet have risk management which explicitly discusses the proposed risk management along with the handling strategies required by the company. By looking at the current condition of the company, in order to achieve the goals to be achieved the company needs a good supply chain planning such as by identifying the risks that exist in the supply chain and preventive measures. Performed risk analysis and evaluation of potential supply chain companies using HOR (House Of Risk) tools. After the research there were 42 risk events and 42 risk agents. With the 80/20 pareto approach, 9 risk agents are planned for mitigation action. There are 11 recommended risk mitigation actions recommended to the company in the hope of addressing the risk of urea fertilizer supply chain.

scholarly journals Methicillin-resistant Staphylococcus aureus genotyping using a small set of polymorphisms

2006 ◽  
Vol 55 (1) ◽  
pp. 43-51 ◽  
Author(s):  
Alex J. Stephens ◽  
Flavia Huygens ◽  
John Inman-Bamber ◽  
Erin P. Price ◽  
Graeme R. Nimmo ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Population Structure ◽  
Real Time ◽  
Real Time Pcr ◽  
Cost Effective ◽  
Resolving Power ◽  
Nucleotide Polymorphisms ◽  
Methicillin Resistant ◽  
Effective Manner ◽  
Mrsa Strains

The aim of this study was to identify a set of genetic polymorphisms that efficiently divides methicillin-resistant Staphylococcus aureus (MRSA) strains into groups consistent with the population structure. The rationale was that such polymorphisms could underpin rapid real-time PCR or low-density array-based methods for monitoring MRSA dissemination in a cost-effective manner. Previously, the authors devised a computerized method for identifying sets of single nucleotide polymorphisms (SNPs) with high resolving power that are defined by multilocus sequence typing (MLST) databases, and also developed a real-time PCR method for interrogating a seven-member SNP set for genotyping S. aureus. Here, it is shown that these seven SNPs efficiently resolve the major MRSA lineages and define 27 genotypes. The SNP-based genotypes are consistent with the MRSA population structure as defined by eburst analysis. The capacity of binary markers to improve resolution was tested using 107 diverse MRSA isolates of Australian origin that encompass nine SNP-based genotypes. The addition of the virulence-associated genes cna, pvl and bbp/sdrE, and the integrated plasmids pT181, pI258 and pUB110, resolved the nine SNP-based genotypes into 21 combinatorial genotypes. Subtyping of the SCCmec locus revealed new SCCmec types and increased the number of combinatorial genotypes to 24. It was concluded that these polymorphisms provide a facile means of assigning MRSA isolates into well-recognized lineages.

An Advanced Vibration Based Real-Time Machine Health and Process Monitoring System

2006 ◽  
Author(s):  
Chandra Jalluri ◽  
Prashanth Magadi ◽  
Mohan Viswanathan ◽  
Richard Furness ◽  
Werner Kluft ◽  
...  
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Process Monitoring ◽  
Cost Effective ◽  
Cnc Machining ◽  
Numerical Control ◽  
Automotive Manufacturing ◽  
Manufacturing Plants ◽  
Effective Manner ◽  
Machine Health

The ever-increasing emphasis on product quality with increased productivity has been driving the automotive manufacturing industry to find new ways to produce high quality products without increasing production time and manufacturing costs. In addition, automotive manufacturing plants are implementing flexible manufacturing strategies with computer numerical control (CNC) machining centers to address excess capacity, shifting consumer trends and future volume uncertainty of products. Over time, plants have used several preventative and predictive maintenance methods to address machine reliability. Such systems include, but are not limited to, scheduling machine down times at regular intervals to check/replace bearings and other spindle/slide components before they can have an adverse affect on part quality. However, most of these methods and traditional systems are not cost effective and cause significant machine down-times, safety concerns and labor overheads and do not reliably monitor other process issues, such as, clamping, incoming stock variations and thermal phenomena. This paper describes an advanced real-time vibration based machine health and process monitoring system that has been developed to address the above issues. The system, called Condition Indicator Analysis Box for CNC (CIAB™-CNC), is easily configurable, and provides real-time data and historical trends of machines, processes and tooling, enabling manufacturing plants to make accurate predictions regarding future production runs. The system also aids in the optimization of preventative maintenance tasks in a cost effective manner. The developed system monitors machine spindle and slide for unbalance, misalignment, damaged/spalled bearings, mechanical looseness, and ball screw issues. Additionally, it performs in-process monitoring during machining as well as non-machining by individual tool and/or feature to detect tool breakages, quality issues and other gross process or machine anomalies. Innovative statistical trending algorithms enable the system to automatically adapt to valid process/parameter changes and significantly reduce the chances of false alarms and warnings. The developed system provides manufacturing plants with a tool to analyze machine tools and their associated components in an effort to gather information they can use effectively to make decisions regarding flexible machines, processes and tooling.

scholarly journals Jellytoring: Real-Time Jellyfish Monitoring Based on Deep Learning Object Detection

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1708 ◽  
Author(s):  
Miguel Martin-Abadal ◽  
Ana Ruiz-Frau ◽  
Hilmar Hinz ◽  
Yolanda Gonzalez-Cid
Keyword(s):  
Object Detection ◽  
Real Time ◽  
Warning System ◽  
Cost Effective ◽  
Marine Species ◽  
Global Scale ◽  
Tourism Industry ◽  
Commercial Fishing ◽  
Anthropogenic Pressures ◽  
Effective Manner

During the past decades, the composition and distribution of marine species have changed due to multiple anthropogenic pressures. Monitoring these changes in a cost-effective manner is of high relevance to assess the environmental status and evaluate the effectiveness of management measures. In particular, recent studies point to a rise of jellyfish populations on a global scale, negatively affecting diverse marine sectors like commercial fishing or the tourism industry. Past monitoring efforts using underwater video observations tended to be time-consuming and costly due to human-based data processing. In this paper, we present Jellytoring, a system to automatically detect and quantify different species of jellyfish based on a deep object detection neural network, allowing us to automatically record jellyfish presence during long periods of time. Jellytoring demonstrates outstanding performance on the jellyfish detection task, reaching an F1 score of 95.2%; and also on the jellyfish quantification task, as it correctly quantifies the number and class of jellyfish on a real-time processed video sequence up to a 93.8% of its duration. The results of this study are encouraging and provide the means towards a efficient way to monitor jellyfish, which can be used for the development of a jellyfish early-warning system, providing highly valuable information for marine biologists and contributing to the reduction of jellyfish impacts on humans.

Steel Lazy Wave Riser Configuration for Turret Moored FPSO With Disconnectable Turret in Deepwater

2015 ◽  
Author(s):  
Daniel Karunakaran ◽  
Sankar Subramanian ◽  
Rolf Baarholm
Keyword(s):  
Deep Water ◽  
Cost Effective ◽  
Attractive Alternative ◽  
Harsh Environment ◽  
Detailed Case ◽  
Effective Manner ◽  
Water Developments ◽  
Pros And Cons ◽  
Steel Catenary Risers

Recently turret-Moored FPSOs have been used in many deep water developments worldwide, with consideration of disconnectable turrets for harsh environment applications. This trend makes the interactions between FPSO and risers system more important. Further, Steel Lazy Wave Risers (SLWR), which is a compliant variant of the mostly commonly used Steel Catenary Risers (SCR), is becoming an attractive riser option. The paper provides a review of the various riser systems that can be considered for turret-moored FPSOs, and specific emphasis on Steel Lazy Wave Risers. A detailed case study of Steel Lazy Wave Risers for a typical turret moored FPSO with disconnectable turret is presented. This system is described in terms of design and functionalities, the fabrication and installation methods are presented. The case study shows clearly that SLWR are an attractive alternative to be used for FPSO with disconnectable turret and is very efficient to fabricate and install in a very cost effective manner. Pros and Cons for SLWR are discussed, with consideration of the particular challenges of turret-moored FPSOs with large floater motions, hang-off geometry constraints at turret, hang-off loads, riser interferences, risers pre-installation, and turret disconnection constraints.

scholarly journals Development of an Automatic Image Cropping and Feature Extraction System for Real-Time Warping Monitoring in 3D Printing

2021 ◽  
Author(s):  
Jiarui Xie
Keyword(s):  
Real Time ◽  
Detection System ◽  
Region Of Interest ◽  
Cost Effective ◽  
Time Warping ◽  
Time Data ◽  
Fused Filament Fabrication ◽  
System A ◽  
Effective Manner

Fused Filament Fabrication (FFF) is an additive manufacturing technology that can produce complicated structures in a simple-to-use and cost-effective manner. Although promising, the technology is prone to defects, e.g. warping, compromising the quality of the manufactured component. To avoid the adverse effects caused by warping, this thesis utilizes deep-learning algorithms to develop a warping detection system using Convolutional Neural Networks (CNN). To create such a system, a real-time data acquisition and analysis pipeline is laid out. The system is responsible for capturing a snapshot of the print layer-bylayer and simultaneously extracting the corners of the component. The extracted region-of-interest is then passed through a CNN outputting the probability of a corner being warped. If a warp is detected, a signal is sent to pause the print, thereby creating a closed-loop monitoring system. The underlying model is tested on a real-time manufacturing environment yielding a mean accuracy of 99.21%.

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