IRJET- Search Improvement using Digital Thread in Data Analytics
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This document discusses the use of digital thread in data analytics to improve search and provide end-to-end visibility across product lifecycles. Digital thread is a communication system that connects manufacturing process elements and provides a complete view of each element throughout the lifecycle. It allows sharing of information across organizations and suppliers. Digital thread brings quality gains by managing large amounts of data and complex supply chains. It helps enterprises quickly redesign products and meet timelines while maintaining visibility of each component's journey. The document proposes using a Neo4j graph database hosted on AWS cloud to implement a digital thread that links product data. This would provide security, performance, and analytics benefits across the overall manufacturing process.
![International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 05 Issue: 12 | Dec 2018 www.irjet.net p-ISSN: 2395-0072
© 2018, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 745
Search Improvement using Digital Thread in Data Analytics
Sagar Latake1, Mohini Jayashette2, Priti Khadtare3, Trupti Biradar4
1,2,3Student, Bachelor of Engineering, Dept. Of Computer Engineering, ISB&M School of Technology, Pune
Maharashtra, India
4Asst. Professor Dept. Of Computer Engineering, ISB&M School of Technology, Pune, Maharashtra, India
---------------------------------------------------------------------***----------------------------------------------------------------------
Abstract - Digital Thread is nothing but a communication
system which connect the elements present in the
manufacturing processesand providesthecompleteviewof an
element throughout the overall manufacturing lifecycle.
Between organizations, especially with complex products, it’s
fairly evident that communication is important. In complex
products, if we’re looking for an efficient design process, that
means sharing information in some way that will allow
suppliers from different levels of the organizations supply
chain to have input on design of the product. The stream
which starts from the creation of any product concepts and
continues to get data throughout the overallproductlifecycle.
It is the process in which the required changes will be done
and it will ultimately influences the future of manufacturing
by using digital thread. Digital Thread can bring quality gains
for those manufacturers in organizationwhoneedstomanage
huge amounts of data and manage complex and complicated
supply chains. Even in a complex discrete environment of the
organization, where data volumes are low, manufacturing
enterprises have to be able for redesign quickly and meet
required timelines. The Digital Thread helps enterprises to
maintain a clear view of every component’s journey from
receiving source through to the final product and beyond to
tracking and records for quality standards and product
lifecycle management.
Key Words: DigitalThread, Neo4jGraph Database,Cloud,
Data Analytics.
1. INTRODUCTION
1.1 Digital Thread
Digital Thread is nothing but a data-driven architecture
that links information generated from the overall product
lifecycle together. Digital thread is getting more and quality
as it is a communicationsystemfordesigning,manufacturing
and used in operational processes for designing, building
and maintaining the engineering product in an organization
more efficiently. There is a scientific formulation describes
where digital thread is used for complete design decisions
may be absent.
Full traceabilityacrossa full lifecycleisthesynonym
for the digital thread. Digital thread is developed for
achieving the product lifecycle’s digital measurement from
the way will be back to the capabilities of model based
system engineering, where the concepts forthevehicle were
originally explored for taking complex designs” in[2].
1.2 Neo4j
Neo4j is an open-source graph database based on Java
with high performance, high reliability and high
extensibility. A graph database isa data managementsystem
with the Create, Delete, Update, and Read(CRUD)operations
which exposes the graph data model, the ability to deal with
relationships are the most distinctive properties of graph
database when comparing with other traditional or NoSQL
databases. Neo4j is the most magnificant graph database
currently all Durability(ACID). Differing from traditional
RDBS, the kernel of Neo4j is a fast topological engine, which
focus on the processing of huge amount of data and complex
links between data. Asshownin,theinformationmodelingof
Neo4j mainly contains three structure units, i.e., nodes,
relationships and properties. There can be multiple
relationships between two differentnodesand relationships
have directions. Nodes and relationships can contain
variable properties in[3].
1.3 Data Analytics
With the increase in universal data volume, the
technology of big data and its analytical processes are
generally used to provide the description about massive
datasets. Compared with other traditional datasets and its
processes, big data includes semi structured and
unstructured data which needs more real time analysis. Big
data also gets details about new prospects for determining
new values, It also supports us for understanding of hidden
values deeply and it will also experiences newly created
challenges, For instance, how to exceptionally organize and
manipulate such big datasets. The volume of information
from various sources is growing large, it also providesabout
some challenging issues demanding rapid resolutions. Big
data visualization process is another vital process which
takes an important place in big data analytics problems.
Because through data visualization only the final report of
data analytics will be visualized in [4].
1.4 Cloud(AWS)
Cloud Computing is a recently emerged model which is
becoming popular among almost all enterprises. It involves
the concept of on demand services which means using the
cloud resources on demand and we can scale the resources
as per demand. Cloud computing provides various benefits
and it is a cost effective model in[5]. It is the approaching IT
industry murmured words- the users move their](https://image.slidesharecdn.com/irjet-v5i12136-181231111953/85/IRJET-Search-Improvement-using-Digital-Thread-in-Data-Analytics-1-320.jpg)
![International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 05 Issue: 12 | Dec 2018 www.irjet.net p-ISSN: 2395-0072
© 2018, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 746
applications and data to the remote cloud so that they can
have a simple and pervasive way of accessing.
2. LITERATURE SURVEY
2.1 Information about Digital Thread
In product overall lifecycle digital twinsare extendedby
the digital thread for enclosing all flows during the
manufacturability, serviceability, engineering, design,
identification and performance . It is the thread which will
run in all organization and a condition with which the
product or service interacts in [7]. The right information at
the right places and at the right time.Dependinguponhowit
is used and by whom it is used the data will be transferred
into the information and then thisinformationistransferred
into the intelligence. With the crossing of the physical and
digital world the data which transferredintotheintelligence
is transferred into the actions. The main challengeisthatthe
information ordata accessandunderstandingwhichpresent
at the right place and the right time so that it is can be used
as part of new value added products,sothatitcanhelpmake
better informed decisions of particular complex design
decision in[8].
2.2 Use of Digital Thread in Data Analytics
Data analytics (DA) is the process of examiningdatasets
in order to draw conclusions about the informationtheycan
contain, increasingly with the specialized systems and
software. In commercial industries to enable the
organization to become more informative for taking
informative decisions and various data analytics techniques
are used in [9]. The product is the lifeline of an enterprise of
organization. While it is developed, launched and deployed
in service, it generates complex and large amount of data. A
connected enterprise must be geared towards tapping this
continuous stream of data throughout the value chain to
extract actionable, real time insights that are usedfor newer
and more efficient outcomes, which are lending the
organization a competitive edge. Yet, the majority of
businesses lack the agility to adapt to the connected world
due to various challenges that only a digital thread can
address in [10].
3. APPLICATIONS OF DIGITAL THREAD
3.1 Data Flows From Shop Floor(Administrative
Decisions) To The Top Floor(System Wide
Visibility)
Manufacturing is generally characterized by the
hierarchical nature. In the automation pyramid the control
loops which are local are supervised by the MC, PLC and
industrial PC(IPC) where actuators and sensors are the
inputs.
3.2 In Production Automation – Fewer Tradeoffs
between Cost, Quality And Speed
Manufacturing growth of productivity has become
slower in worldwide according to the data from the ILC
program from the conference board.
3.3InPredictiveMaintenance–MachineDowntime
Visibility and Reduction
Predictive Maintenance is nothing but the application of
predictive analytical algorithms against the real time
observed data to proactively identify the potential concerns
before they arise and to make guided recommendations to
address the issues.
4. ADVANTAGES OF DIGITAL THREAD
4.1 For Velocity
Even in a complex discreteenvironment,wherevolumes
become low, manufacturing enterprises have to change
quickly and meet demanding or required timelines.
4.2 For Change Management
The various layers of change by usingdimensionscanbe
measured by the digital thread.
4.3 More Benefits of the Adopting of DigitalThread
Adaptation of the DT(Digital Thread) is the first step
towards building the Model Based Enterprise for the Smart
Factory Revolution.
5. CONCLUSION
In our paper we are implemented the digital thread. In
our project we had created the graph database from
structured data and hosted this graph database on the cloud
and gave the security level by level as well.
ACKNOWLEDGEMENT
We would like to express our deepest appreciation to all
those who provided us the possibilitytocompletethispaper.
A special thanks we give to our project guide Prof. Sagar
Latake and our HOD of computer department Dr. Pallavi Jha
whose contribution in suggestions and encouragement and
helped us to coordinate in our project mainly in writing this
paper.
REFERENCES
[1] Engineering Design with Digital Thread written By
Victor Singh* and Karen E. Willcox Massachusetts
Institute of Technology, Cambridge, MA, 02139.
[2] What Are the Digital Threads and Digital
Twins?https://www.adandp.media/articles/what-are-
digital-twins-and-digital-threads.](https://image.slidesharecdn.com/irjet-v5i12136-181231111953/85/IRJET-Search-Improvement-using-Digital-Thread-in-Data-Analytics-2-320.jpg)
![International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 05 Issue: 12 | Dec 2018 www.irjet.net p-ISSN: 2395-0072
© 2018, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 747
[3] 2014 International Conference on Power System
Technology (POWERCON 2014) Chengdu, 20-22 Oct.
2014
[4] INTERNATIONAL CONFERENCE ON INFORMATION,
COMMUNICATION & EMBEDDED SYSTEMS (ICICES
2017) 978-1-5090-6135-8/17/$31.00 ©2017 IEEE A
Survey Paper on Big Data Analytics By M.D. Anto
Praveena1 Dr. B. Bharathi2 1Research Scholar,
Sathyabama University, Chennai, Tamilnadu, India.
[5] 2015 The Fifth International Conference on Advanced
Computing & Communication Technologies, CLOUD
COMPUTING SECURITY:AMAZON WEB SERVICE,
written by Arushi Jain M.tech Student Department of
CSE & IT ITM University Gurgaon ,India
arushijain_1992@yahoo.com
[6] Exploring the Cloud from Passive Measurements: the
Amazon AWS Case Ignacio Bermudez, StefanoTraverso,
Marco Mellia, Maurizio Munaf`oDET, Politecnico di
Torino, Italy – {lastname}@tlc.polito.it, 2013
Proceedings IEEE INFOCOM
[7] https://www.ibaset.com/blog/what-is-the-digital-
thread/
[8] https://www.tatatechnologies.com/us/72351-digital-
thread-digital-twins-predictive-twins-process-
intelligence/
[9] https://searchdatamanagement.techtarget.com/definiti
on/data-analytics/
[10] https://www.tcs.com/blogs/digital-thread-unlocking-
insights-from-product-data-stream/
[11] IEEE TRANSACTION PAPER ON BIGDATA,VOL.1,NO.1,
JANUARY-MARCH 2015](https://image.slidesharecdn.com/irjet-v5i12136-181231111953/85/IRJET-Search-Improvement-using-Digital-Thread-in-Data-Analytics-3-320.jpg)
IRJET- Search Improvement using Digital Thread in Data Analytics
- 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 12 | Dec 2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 745 Search Improvement using Digital Thread in Data Analytics Sagar Latake1, Mohini Jayashette2, Priti Khadtare3, Trupti Biradar4 1,2,3Student, Bachelor of Engineering, Dept. Of Computer Engineering, ISB&M School of Technology, Pune Maharashtra, India 4Asst. Professor Dept. Of Computer Engineering, ISB&M School of Technology, Pune, Maharashtra, India ---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - Digital Thread is nothing but a communication system which connect the elements present in the manufacturing processesand providesthecompleteviewof an element throughout the overall manufacturing lifecycle. Between organizations, especially with complex products, it’s fairly evident that communication is important. In complex products, if we’re looking for an efficient design process, that means sharing information in some way that will allow suppliers from different levels of the organizations supply chain to have input on design of the product. The stream which starts from the creation of any product concepts and continues to get data throughout the overallproductlifecycle. It is the process in which the required changes will be done and it will ultimately influences the future of manufacturing by using digital thread. Digital Thread can bring quality gains for those manufacturers in organizationwhoneedstomanage huge amounts of data and manage complex and complicated supply chains. Even in a complex discrete environment of the organization, where data volumes are low, manufacturing enterprises have to be able for redesign quickly and meet required timelines. The Digital Thread helps enterprises to maintain a clear view of every component’s journey from receiving source through to the final product and beyond to tracking and records for quality standards and product lifecycle management. Key Words: DigitalThread, Neo4jGraph Database,Cloud, Data Analytics. 1. INTRODUCTION 1.1 Digital Thread Digital Thread is nothing but a data-driven architecture that links information generated from the overall product lifecycle together. Digital thread is getting more and quality as it is a communicationsystemfordesigning,manufacturing and used in operational processes for designing, building and maintaining the engineering product in an organization more efficiently. There is a scientific formulation describes where digital thread is used for complete design decisions may be absent. Full traceabilityacrossa full lifecycleisthesynonym for the digital thread. Digital thread is developed for achieving the product lifecycle’s digital measurement from the way will be back to the capabilities of model based system engineering, where the concepts forthevehicle were originally explored for taking complex designs” in[2]. 1.2 Neo4j Neo4j is an open-source graph database based on Java with high performance, high reliability and high extensibility. A graph database isa data managementsystem with the Create, Delete, Update, and Read(CRUD)operations which exposes the graph data model, the ability to deal with relationships are the most distinctive properties of graph database when comparing with other traditional or NoSQL databases. Neo4j is the most magnificant graph database currently all Durability(ACID). Differing from traditional RDBS, the kernel of Neo4j is a fast topological engine, which focus on the processing of huge amount of data and complex links between data. Asshownin,theinformationmodelingof Neo4j mainly contains three structure units, i.e., nodes, relationships and properties. There can be multiple relationships between two differentnodesand relationships have directions. Nodes and relationships can contain variable properties in[3]. 1.3 Data Analytics With the increase in universal data volume, the technology of big data and its analytical processes are generally used to provide the description about massive datasets. Compared with other traditional datasets and its processes, big data includes semi structured and unstructured data which needs more real time analysis. Big data also gets details about new prospects for determining new values, It also supports us for understanding of hidden values deeply and it will also experiences newly created challenges, For instance, how to exceptionally organize and manipulate such big datasets. The volume of information from various sources is growing large, it also providesabout some challenging issues demanding rapid resolutions. Big data visualization process is another vital process which takes an important place in big data analytics problems. Because through data visualization only the final report of data analytics will be visualized in [4]. 1.4 Cloud(AWS) Cloud Computing is a recently emerged model which is becoming popular among almost all enterprises. It involves the concept of on demand services which means using the cloud resources on demand and we can scale the resources as per demand. Cloud computing provides various benefits and it is a cost effective model in[5]. It is the approaching IT industry murmured words- the users move their
- 2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 12 | Dec 2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 746 applications and data to the remote cloud so that they can have a simple and pervasive way of accessing. 2. LITERATURE SURVEY 2.1 Information about Digital Thread In product overall lifecycle digital twinsare extendedby the digital thread for enclosing all flows during the manufacturability, serviceability, engineering, design, identification and performance . It is the thread which will run in all organization and a condition with which the product or service interacts in [7]. The right information at the right places and at the right time.Dependinguponhowit is used and by whom it is used the data will be transferred into the information and then thisinformationistransferred into the intelligence. With the crossing of the physical and digital world the data which transferredintotheintelligence is transferred into the actions. The main challengeisthatthe information ordata accessandunderstandingwhichpresent at the right place and the right time so that it is can be used as part of new value added products,sothatitcanhelpmake better informed decisions of particular complex design decision in[8]. 2.2 Use of Digital Thread in Data Analytics Data analytics (DA) is the process of examiningdatasets in order to draw conclusions about the informationtheycan contain, increasingly with the specialized systems and software. In commercial industries to enable the organization to become more informative for taking informative decisions and various data analytics techniques are used in [9]. The product is the lifeline of an enterprise of organization. While it is developed, launched and deployed in service, it generates complex and large amount of data. A connected enterprise must be geared towards tapping this continuous stream of data throughout the value chain to extract actionable, real time insights that are usedfor newer and more efficient outcomes, which are lending the organization a competitive edge. Yet, the majority of businesses lack the agility to adapt to the connected world due to various challenges that only a digital thread can address in [10]. 3. APPLICATIONS OF DIGITAL THREAD 3.1 Data Flows From Shop Floor(Administrative Decisions) To The Top Floor(System Wide Visibility) Manufacturing is generally characterized by the hierarchical nature. In the automation pyramid the control loops which are local are supervised by the MC, PLC and industrial PC(IPC) where actuators and sensors are the inputs. 3.2 In Production Automation – Fewer Tradeoffs between Cost, Quality And Speed Manufacturing growth of productivity has become slower in worldwide according to the data from the ILC program from the conference board. 3.3InPredictiveMaintenance–MachineDowntime Visibility and Reduction Predictive Maintenance is nothing but the application of predictive analytical algorithms against the real time observed data to proactively identify the potential concerns before they arise and to make guided recommendations to address the issues. 4. ADVANTAGES OF DIGITAL THREAD 4.1 For Velocity Even in a complex discreteenvironment,wherevolumes become low, manufacturing enterprises have to change quickly and meet demanding or required timelines. 4.2 For Change Management The various layers of change by usingdimensionscanbe measured by the digital thread. 4.3 More Benefits of the Adopting of DigitalThread Adaptation of the DT(Digital Thread) is the first step towards building the Model Based Enterprise for the Smart Factory Revolution. 5. CONCLUSION In our paper we are implemented the digital thread. In our project we had created the graph database from structured data and hosted this graph database on the cloud and gave the security level by level as well. ACKNOWLEDGEMENT We would like to express our deepest appreciation to all those who provided us the possibilitytocompletethispaper. A special thanks we give to our project guide Prof. Sagar Latake and our HOD of computer department Dr. Pallavi Jha whose contribution in suggestions and encouragement and helped us to coordinate in our project mainly in writing this paper. REFERENCES [1] Engineering Design with Digital Thread written By Victor Singh* and Karen E. Willcox Massachusetts Institute of Technology, Cambridge, MA, 02139. [2] What Are the Digital Threads and Digital Twins?https://www.adandp.media/articles/what-are- digital-twins-and-digital-threads.
- 3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 12 | Dec 2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 747 [3] 2014 International Conference on Power System Technology (POWERCON 2014) Chengdu, 20-22 Oct. 2014 [4] INTERNATIONAL CONFERENCE ON INFORMATION, COMMUNICATION & EMBEDDED SYSTEMS (ICICES 2017) 978-1-5090-6135-8/17/$31.00 ©2017 IEEE A Survey Paper on Big Data Analytics By M.D. Anto Praveena1 Dr. B. Bharathi2 1Research Scholar, Sathyabama University, Chennai, Tamilnadu, India. [5] 2015 The Fifth International Conference on Advanced Computing & Communication Technologies, CLOUD COMPUTING SECURITY:AMAZON WEB SERVICE, written by Arushi Jain M.tech Student Department of CSE & IT ITM University Gurgaon ,India [email protected] [6] Exploring the Cloud from Passive Measurements: the Amazon AWS Case Ignacio Bermudez, StefanoTraverso, Marco Mellia, Maurizio Munaf`oDET, Politecnico di Torino, Italy – {lastname}@tlc.polito.it, 2013 Proceedings IEEE INFOCOM [7] https://www.ibaset.com/blog/what-is-the-digital- thread/ [8] https://www.tatatechnologies.com/us/72351-digital- thread-digital-twins-predictive-twins-process- intelligence/ [9] https://searchdatamanagement.techtarget.com/definiti on/data-analytics/ [10] https://www.tcs.com/blogs/digital-thread-unlocking- insights-from-product-data-stream/ [11] IEEE TRANSACTION PAPER ON BIGDATA,VOL.1,NO.1, JANUARY-MARCH 2015