This document presents a graph-based approach for securely managing resources in smart factories. It uses a graph-based organizational model and a declarative query language. The organizational model represents factories and their resources as nodes connected by relationships. The query language can find appropriate production facilities that meet specific manufacturing tasks by traversing the graph. This approach solves the problem of manually enumerating facilities for tasks. It ensures security by identifying currently valid identities and allows for alternative facilities using deputy relationships to improve availability.
Use Case Modeling in Software Development: A Survey and TaxonomyEswar Publications
Identifying use cases is one of the most important steps in the software requirement analysis. This paper makes a literature review over use cases and then presents six taxonomies for them. The first taxonomy is based on the level of functionality of a system in a domain. The second taxonomy is based on primacy of functionality and the third one relies on essentialness of functionality of the system. The fourth taxonomy is concerned with supporting of functionality. The fifth taxonomy is based on the boundary of functionality and the sixth one is related to generalization/specialization relation. Then the use cases are evaluated in a case study in a control command police system. Several guidelines are recommended for developing use cases and their refinement, based on some
practical experience obtained from the evaluation.
New England CollegeFI6315 Managerial FinanceSummer I 2019P.docxvannagoforth
New England College
FI6315 Managerial Finance
Summer I 2019
Problem Set 2/Exam 2
Name:
Date:
Part 1 (19 points) ________
Part 2 (15 points) ________
Part 3 (19 points) ________
Part 4 (19 points) ________
Part 5 (14 points) ________
Part 6 (14 points) ________
Total
=======
Part 1:
Calculate the NPV for the following capital budgeting proposal: $100,000 initial cost for equipment, straight-line depreciation over 5 years to a zero book value, $5,000 pre-tax salvage value of equipment, 35% tax rate, $45,000 additional annual revenues, $15,000 additional annual cash expenses, $8,000 initial investment in working capital to be recouped at project end, and a cost of capital of 11%. Should the project be accepted or rejected? (Show your work computing the NPV.)
Part 2: Essay
Explain why bond prices fluctuate in response to changing interest rates. What adverse effect might occur if bond prices remain fixed prior to their maturity?
Part 3:
A stock offers an expected dividend of $3.50, has a required return of 14%, and has historically exhibited a growth rate of 6%. Its current price is $35.00 and shows no tendency to change. How can you explain this price based on the constant-growth dividend discount model?
Part 4:
Calculate the expected rate of return for the following portfolio, based on a Treasury bill yield of 4% and an expected market return of 13%: (Show your work)
Part 5: Essay
Discuss the capital asset pricing model in general, the CAPM method of determining expected returns, and how the SML can be used to help predict the movement of a stock's price.
Part 6: Essay
Contrast the Dow Jones Industrial Average and the Standard and Poor's Composite Index.
fi6315 exam 2 spring ii 2019 (3).doc
There’s steps on the literature and methodology section in the report structure guide file on canvas, my part is separate from the intro, process model etc
(literature and methodlogy) Use the references at the end of the lecture slides for week 1-3 to help you explain functional and social and then relate it back to how we’ve reccommended it for the mining company. I don’t have to do anything else but this part is about 1000-1500 words
Just these parts
And for lit review there’s articles listed in the learning materials section in weeks 1-3
My group recommended this format as:
One person
intro - which involves answering the interview questions and indentifying the problem
One person
-Literature review - 6 references on the topic, can include the articles that are on the lectures from week 1-3
And methodology
Two people +the help of ...
The paper deals with distributed planning in a Mult
i-Agent System (MAS) constituted by several
intelligent agents each one has to interact with th
e other autonomous agents. The problem faced
is how to ensure a distributed planning through the
cooperation in our multi-agent system.
To do so, we propose the use of fuzzy logic to repr
esent the response of the agent in case of
interaction with the other. Finally, we use JADE p
latform to create agents and ensure the
communication between them.
A Benchmark Production System is used as a running
example to explain our contribution.
Agility by Design - Building Software to Lasteprentise
The implementation of enterprise systems brings with it great promise of better information, consistent systems, and reduced operational costs. Achieving that promise, however, is an immense challenge.
View the original Blog post: http://www.eprentise.com/blog/data-systems/agility-by-design-building-software-to-last/
Website: www.eprentise.com
Twitter: @eprentise
Google+: https://plus.google.com/u/0/+Eprentise/posts
Facebook: https://www.facebook.com/eprentise
Use Case Modeling in Software Development: A Survey and TaxonomyEswar Publications
Identifying use cases is one of the most important steps in the software requirement analysis. This paper makes a literature review over use cases and then presents six taxonomies for them. The first taxonomy is based on the level of functionality of a system in a domain. The second taxonomy is based on primacy of functionality and the third one relies on essentialness of functionality of the system. The fourth taxonomy is concerned with supporting of functionality. The fifth taxonomy is based on the boundary of functionality and the sixth one is related to generalization/specialization relation. Then the use cases are evaluated in a case study in a control command police system. Several guidelines are recommended for developing use cases and their refinement, based on some
practical experience obtained from the evaluation.
New England CollegeFI6315 Managerial FinanceSummer I 2019P.docxvannagoforth
New England College
FI6315 Managerial Finance
Summer I 2019
Problem Set 2/Exam 2
Name:
Date:
Part 1 (19 points) ________
Part 2 (15 points) ________
Part 3 (19 points) ________
Part 4 (19 points) ________
Part 5 (14 points) ________
Part 6 (14 points) ________
Total
=======
Part 1:
Calculate the NPV for the following capital budgeting proposal: $100,000 initial cost for equipment, straight-line depreciation over 5 years to a zero book value, $5,000 pre-tax salvage value of equipment, 35% tax rate, $45,000 additional annual revenues, $15,000 additional annual cash expenses, $8,000 initial investment in working capital to be recouped at project end, and a cost of capital of 11%. Should the project be accepted or rejected? (Show your work computing the NPV.)
Part 2: Essay
Explain why bond prices fluctuate in response to changing interest rates. What adverse effect might occur if bond prices remain fixed prior to their maturity?
Part 3:
A stock offers an expected dividend of $3.50, has a required return of 14%, and has historically exhibited a growth rate of 6%. Its current price is $35.00 and shows no tendency to change. How can you explain this price based on the constant-growth dividend discount model?
Part 4:
Calculate the expected rate of return for the following portfolio, based on a Treasury bill yield of 4% and an expected market return of 13%: (Show your work)
Part 5: Essay
Discuss the capital asset pricing model in general, the CAPM method of determining expected returns, and how the SML can be used to help predict the movement of a stock's price.
Part 6: Essay
Contrast the Dow Jones Industrial Average and the Standard and Poor's Composite Index.
fi6315 exam 2 spring ii 2019 (3).doc
There’s steps on the literature and methodology section in the report structure guide file on canvas, my part is separate from the intro, process model etc
(literature and methodlogy) Use the references at the end of the lecture slides for week 1-3 to help you explain functional and social and then relate it back to how we’ve reccommended it for the mining company. I don’t have to do anything else but this part is about 1000-1500 words
Just these parts
And for lit review there’s articles listed in the learning materials section in weeks 1-3
My group recommended this format as:
One person
intro - which involves answering the interview questions and indentifying the problem
One person
-Literature review - 6 references on the topic, can include the articles that are on the lectures from week 1-3
And methodology
Two people +the help of ...
The paper deals with distributed planning in a Mult
i-Agent System (MAS) constituted by several
intelligent agents each one has to interact with th
e other autonomous agents. The problem faced
is how to ensure a distributed planning through the
cooperation in our multi-agent system.
To do so, we propose the use of fuzzy logic to repr
esent the response of the agent in case of
interaction with the other. Finally, we use JADE p
latform to create agents and ensure the
communication between them.
A Benchmark Production System is used as a running
example to explain our contribution.
Agility by Design - Building Software to Lasteprentise
The implementation of enterprise systems brings with it great promise of better information, consistent systems, and reduced operational costs. Achieving that promise, however, is an immense challenge.
View the original Blog post: http://www.eprentise.com/blog/data-systems/agility-by-design-building-software-to-last/
Website: www.eprentise.com
Twitter: @eprentise
Google+: https://plus.google.com/u/0/+Eprentise/posts
Facebook: https://www.facebook.com/eprentise
An Overview of Workflow Management on Mobile Agent TechnologyIJERA Editor
Mobile agent workflow management/plugins is quite appropriate to handle control flows in open distributed system; basically it is the emerging technology which can bring the process oriented tasks to run as a single unit from diverse frameworks. This workflow technology offers organizations the opportunity to reshape business processes beyond the boundaries of their own organizations so that instead of static models, modern era incurring dynamic workflows which can respond the changes during its execution, provide necessary security measures, great degree of adaptivity, troubleshoot the running processes and recovery of lost states through fault tolerance. The prototype that we are planning to design makes sure to hold reliability, security, robustness, scalability without being forced to make tradeoffs the performance. This paper is concerned with design, implementation and evaluation of performance on the improved methods of proposed prototype models based on current research in this domain.
An approach to modeling interoperability within an ecosystem facing rapid tempos of change in the nature of demands. The approach identifies interoperability risks of existing architectures and drives economic modeling of the impact of changes in architecture.
Intelligent Buildings: Foundation for Intelligent Physical AgentsIJERA Editor
FIPA is an IEEE Computer Society standards organization that promotes agent-based technology and the interoperability of its standards with other technologies. In the design phase of Intelligent Buildings, it is essential to manage many services and facilities, to do this, multi-agent systems are a good tool to manage them. In this paper, we will gereneral description of the features and elements of multiagent systems described by Foundation for Intelligent Physical Agents (FIPA). Secondly, we will focus on the architectures of these multiagent systems. And finally, we will propose a multi-agent system design to see the application in the design of a detached house where the lighting, air conditioning and security systems will be integrated.
Aligning the business operations with the appropriate IT infrastructure is a challenging and critical activity. Without efficient business/IT alignment, the companies face the risk not to be able to deliver their business services satisfactorily and that their image is seriously altered and jeopardized. Among the many challenges of business/IT alignment is the access rights management which should be conducted considering the rising governance needs, such as taking into account the business actors' responsibility. Unfortunately, in this domain, we have observed that no solution, model and method, fully considers and integrates the new needs yet. Therefore, the paper proposes firstly to define an expressive Responsibility metamodel, named ReMMo, which allows representing the existing responsibilities at the business layer and, thereby, allows engineering the access rights required to perform these responsibilities, at the application layer. Secondly, the Responsibility metamodel has been integrated with ArchiMate® to enhance its usability and benefits from the enterprise architecture formalism. Finally, a method has been proposed to define the access rights more accurately, considering the alignment of ReMMo and RBAC. The research was realized following a design science and action design based research method and the results have been evaluated through an extended case study at the Hospital Center in Luxembourg.
Information systems analysis and requirements analysis produces a requirements specification. This specification states the project goal and the related data storage, data movement
Analysis of Agile and Multi-Agent Based Process Scheduling Modelirjes
As an answer of long growing frustration of waterfall Software development life cycle concepts,
agile software development concept was evolved in 90’s. The most popular agile methodologies is the Extreme
Programming (XP). Most software companies nowadays aim to produce efficient, flexible and valuable
Software in short time period with minimal costs, and within unstable, changing environments. This complex
problem can be modeled as a multi-agent based system, where agents negotiate resources. Agents can be used to
represent projects and resources. Crucial for the multi-agent based system in project scheduling model, is the
availability of an effective algorithm for prioritizing and scheduling of task. To evaluate the models, simulations
were carried out with real life and several generated data sets. The developed model (Multi-agent based System)
provides an optimized and flexible agile process scheduling and reduces overheads in the software process as it
responds quickly to changing requirements without excessive work in project scheduling.
Configuration management for lyee softwaremariase324
Configuration management for lyee software
Esta es una herramienta por la cual, Esta es una herramienta por la cual4 Esta es una herramienta por la cual7Esta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualv
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
Abstract: multi-agent systems and particularly bdi agents are mostly used in a wide range of projects, from agent-based simulations to air-traffic control. They all benefit from the autonomy and proactive behavior that provides agent-based architectures, as well as the characteristics of reasoning that are outlined by the bdi architecture. Thereforethe belief desire intention agent model and agentspeak language have becomea state-of-the-art and one of the challenging research subjects in the agent modeling and programming area.
In particular the bdi architecture is frequently used in the development of agents that try to simulate certainaspects of human behavior, and precisely perception and formulation of beliefs are two of the elements of bdiagents that require special attention in the development of such agents. Thiswork propose a way to extend the reasoning cycle algorithm on bdi agents, in a way that it allows to process inaccurate perceptions in the formulation of beliefs in such agents; it also shows an example implemented in agentspeak as well as the results of its execution within the jason interpreter.
Abstract: multi-agent systems and particularly bdi agents are mostly used in a wide range of projects, from agent-based simulations to air-traffic control. They all benefit from the autonomy and proactive behavior that provides agent-based architectures, as well as the characteristics of reasoning that are outlined by the bdi architecture. Thereforethe belief desire intention agent model and agentspeak language have becomea state-of-the-art and one of the challenging research subjects in the agent modeling and programming area.
In particular the bdi architecture is frequently used in the development of agents that try to simulate certainaspects of human behavior, and precisely perception and formulation of beliefs are two of the elements of bdiagents that require special attention in the development of such agents. Thiswork propose a way to extend the reasoning cycle algorithm on bdi agents, in a way that it allows to process inaccurate perceptions in the formulation of beliefs in such agents; it also shows an example implemented in agentspeak as well as the results of its execution within the jason interpreter.Keywords: Agent, Agent Speak, Beliefs, BDI, Fuzzy-BDI, Fuzzy Perceptions, Simulation.
Title :An Extended Reasoning Cycle Algorithm for BDI Agents
Author: Donald Rodriguez-Ubeda, Dora-Luz Flores, Luis Palafox, Manuel Castanon-Puga, Carelia Gaxiola-Pacheco, Ricardo Rosales
International Journal of Recent Research in Mathematics Computer Science and Information Technology
ISSN: 2350- 1022
Paper Publications
PREDICTING BANKRUPTCY USING MACHINE LEARNING ALGORITHMSIJCI JOURNAL
This paper is written for predicting Bankruptcy using different Machine Learning Algorithms. Whether the company will go bankrupt or not is one of the most challenging and toughest question to answer in the 21st Century. Bankruptcy is defined as the final stage of failure for a firm. A company declares that it has gone bankrupt when at that present moment it does not have enough funds to pay the creditors. It is a global
problem. This paper provides a unique methodology to classify companies as bankrupt or healthy by applying predictive analytics. The prediction model stated in this paper yields better accuracy with standard parameters used for bankruptcy prediction than previously applied prediction methodologies.
Understanding information systems infrastructure inengineeri.docxwillcoxjanay
Understanding information systems infrastructure in
engineering SMEs: A case study
B.J. Hicks a, S.J. Culley a, C.A. McMahon a, P. Powell b,*
a University of Bath, Bath BA2 7AY, United Kingdom
b Birkbeck, University of London, London WC1E 7HX, United Kingdom
1. Introduction
The importance of information and systems for management are widely accepted (Jessup, 2006).
Applications such as finance, payroll, customer relationship management (CRM), and inventory
management support operations and strategy. The full range of business functions which commercial
off-the-shelf (COTS) information systems (IS) address is shown in the lower portion of Fig. 1. Within
any organisation the IS infrastructure may comprise many different functional elements and
associated software applications.
J. Eng. Technol. Manage. 27 (2010) 52–73
A R T I C L E I N F O
Article history:
Available online 3 April 2010
JEL classification:
M15
O32
Keywords:
Information systems
Engineering SMEs
Functional elements
Information dependencies
Integration
Investment
A B S T R A C T
The benefits of integrated enterprise-wide information systems (IS),
such as Enterprise Resource Planning (ERP) systems, are widely
accepted. The implementation of such systems in large organisations
is established with many in their second or third generation.
However, in small to medium-sized enterprises (SMEs) the maturity
and extent of their IS infrastructure is less clear. In engineering SMEs,
this infrastructure needs to support not only business processes but
also the activities of design and manufacture.
In this case study, our goal is to provide a better understanding of
current IS infrastructure, the functional elements of IS infrastruc-
ture, integration and expenditures are explored in ten engineering
SMEs. A model of IS functionality is developed and used to identify
and classify functional elements within the firms and to compare
and contrast the IS infrastructures. The findings are contrasted with
the SME literature and conclusions and implications developed.
� 2010 Elsevier B.V. All rights reserved.
* Corresponding author. Tel.: +44 0 20 3073 8086; fax: +44 0 1223 386928.
E-mail address: [email protected] (P. Powell).
Contents lists available at ScienceDirect
Journal of Engineering and
Technology Management
journal homepage: www.elsevier.com/locate/jengtecman
0923-4748/$ – see front matter � 2010 Elsevier B.V. All rights reserved.
doi:10.1016/j.jengtecman.2010.03.004
Information systems need to support core business functions and to ensure that the overall
infrastructure is integrated. Integration provides accurate, timely information across the organisation.
One route to integration is through Enterprise Resource Planning (ERP) systems, which arose from
earlier developments of Materials Resource Planning (MRP) systems (Langenwalter, 1999). These
systems evolved from linking stores and production departments to their current manifestation that
includ ...
An Overview of Workflow Management on Mobile Agent TechnologyIJERA Editor
Mobile agent workflow management/plugins is quite appropriate to handle control flows in open distributed system; basically it is the emerging technology which can bring the process oriented tasks to run as a single unit from diverse frameworks. This workflow technology offers organizations the opportunity to reshape business processes beyond the boundaries of their own organizations so that instead of static models, modern era incurring dynamic workflows which can respond the changes during its execution, provide necessary security measures, great degree of adaptivity, troubleshoot the running processes and recovery of lost states through fault tolerance. The prototype that we are planning to design makes sure to hold reliability, security, robustness, scalability without being forced to make tradeoffs the performance. This paper is concerned with design, implementation and evaluation of performance on the improved methods of proposed prototype models based on current research in this domain.
An approach to modeling interoperability within an ecosystem facing rapid tempos of change in the nature of demands. The approach identifies interoperability risks of existing architectures and drives economic modeling of the impact of changes in architecture.
Intelligent Buildings: Foundation for Intelligent Physical AgentsIJERA Editor
FIPA is an IEEE Computer Society standards organization that promotes agent-based technology and the interoperability of its standards with other technologies. In the design phase of Intelligent Buildings, it is essential to manage many services and facilities, to do this, multi-agent systems are a good tool to manage them. In this paper, we will gereneral description of the features and elements of multiagent systems described by Foundation for Intelligent Physical Agents (FIPA). Secondly, we will focus on the architectures of these multiagent systems. And finally, we will propose a multi-agent system design to see the application in the design of a detached house where the lighting, air conditioning and security systems will be integrated.
Aligning the business operations with the appropriate IT infrastructure is a challenging and critical activity. Without efficient business/IT alignment, the companies face the risk not to be able to deliver their business services satisfactorily and that their image is seriously altered and jeopardized. Among the many challenges of business/IT alignment is the access rights management which should be conducted considering the rising governance needs, such as taking into account the business actors' responsibility. Unfortunately, in this domain, we have observed that no solution, model and method, fully considers and integrates the new needs yet. Therefore, the paper proposes firstly to define an expressive Responsibility metamodel, named ReMMo, which allows representing the existing responsibilities at the business layer and, thereby, allows engineering the access rights required to perform these responsibilities, at the application layer. Secondly, the Responsibility metamodel has been integrated with ArchiMate® to enhance its usability and benefits from the enterprise architecture formalism. Finally, a method has been proposed to define the access rights more accurately, considering the alignment of ReMMo and RBAC. The research was realized following a design science and action design based research method and the results have been evaluated through an extended case study at the Hospital Center in Luxembourg.
Information systems analysis and requirements analysis produces a requirements specification. This specification states the project goal and the related data storage, data movement
Analysis of Agile and Multi-Agent Based Process Scheduling Modelirjes
As an answer of long growing frustration of waterfall Software development life cycle concepts,
agile software development concept was evolved in 90’s. The most popular agile methodologies is the Extreme
Programming (XP). Most software companies nowadays aim to produce efficient, flexible and valuable
Software in short time period with minimal costs, and within unstable, changing environments. This complex
problem can be modeled as a multi-agent based system, where agents negotiate resources. Agents can be used to
represent projects and resources. Crucial for the multi-agent based system in project scheduling model, is the
availability of an effective algorithm for prioritizing and scheduling of task. To evaluate the models, simulations
were carried out with real life and several generated data sets. The developed model (Multi-agent based System)
provides an optimized and flexible agile process scheduling and reduces overheads in the software process as it
responds quickly to changing requirements without excessive work in project scheduling.
Configuration management for lyee softwaremariase324
Configuration management for lyee software
Esta es una herramienta por la cual, Esta es una herramienta por la cual4 Esta es una herramienta por la cual7Esta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualEsta es una herramienta por la cualv
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
Abstract: multi-agent systems and particularly bdi agents are mostly used in a wide range of projects, from agent-based simulations to air-traffic control. They all benefit from the autonomy and proactive behavior that provides agent-based architectures, as well as the characteristics of reasoning that are outlined by the bdi architecture. Thereforethe belief desire intention agent model and agentspeak language have becomea state-of-the-art and one of the challenging research subjects in the agent modeling and programming area.
In particular the bdi architecture is frequently used in the development of agents that try to simulate certainaspects of human behavior, and precisely perception and formulation of beliefs are two of the elements of bdiagents that require special attention in the development of such agents. Thiswork propose a way to extend the reasoning cycle algorithm on bdi agents, in a way that it allows to process inaccurate perceptions in the formulation of beliefs in such agents; it also shows an example implemented in agentspeak as well as the results of its execution within the jason interpreter.
Abstract: multi-agent systems and particularly bdi agents are mostly used in a wide range of projects, from agent-based simulations to air-traffic control. They all benefit from the autonomy and proactive behavior that provides agent-based architectures, as well as the characteristics of reasoning that are outlined by the bdi architecture. Thereforethe belief desire intention agent model and agentspeak language have becomea state-of-the-art and one of the challenging research subjects in the agent modeling and programming area.
In particular the bdi architecture is frequently used in the development of agents that try to simulate certainaspects of human behavior, and precisely perception and formulation of beliefs are two of the elements of bdiagents that require special attention in the development of such agents. Thiswork propose a way to extend the reasoning cycle algorithm on bdi agents, in a way that it allows to process inaccurate perceptions in the formulation of beliefs in such agents; it also shows an example implemented in agentspeak as well as the results of its execution within the jason interpreter.Keywords: Agent, Agent Speak, Beliefs, BDI, Fuzzy-BDI, Fuzzy Perceptions, Simulation.
Title :An Extended Reasoning Cycle Algorithm for BDI Agents
Author: Donald Rodriguez-Ubeda, Dora-Luz Flores, Luis Palafox, Manuel Castanon-Puga, Carelia Gaxiola-Pacheco, Ricardo Rosales
International Journal of Recent Research in Mathematics Computer Science and Information Technology
ISSN: 2350- 1022
Paper Publications
PREDICTING BANKRUPTCY USING MACHINE LEARNING ALGORITHMSIJCI JOURNAL
This paper is written for predicting Bankruptcy using different Machine Learning Algorithms. Whether the company will go bankrupt or not is one of the most challenging and toughest question to answer in the 21st Century. Bankruptcy is defined as the final stage of failure for a firm. A company declares that it has gone bankrupt when at that present moment it does not have enough funds to pay the creditors. It is a global
problem. This paper provides a unique methodology to classify companies as bankrupt or healthy by applying predictive analytics. The prediction model stated in this paper yields better accuracy with standard parameters used for bankruptcy prediction than previously applied prediction methodologies.
Understanding information systems infrastructure inengineeri.docxwillcoxjanay
Understanding information systems infrastructure in
engineering SMEs: A case study
B.J. Hicks a, S.J. Culley a, C.A. McMahon a, P. Powell b,*
a University of Bath, Bath BA2 7AY, United Kingdom
b Birkbeck, University of London, London WC1E 7HX, United Kingdom
1. Introduction
The importance of information and systems for management are widely accepted (Jessup, 2006).
Applications such as finance, payroll, customer relationship management (CRM), and inventory
management support operations and strategy. The full range of business functions which commercial
off-the-shelf (COTS) information systems (IS) address is shown in the lower portion of Fig. 1. Within
any organisation the IS infrastructure may comprise many different functional elements and
associated software applications.
J. Eng. Technol. Manage. 27 (2010) 52–73
A R T I C L E I N F O
Article history:
Available online 3 April 2010
JEL classification:
M15
O32
Keywords:
Information systems
Engineering SMEs
Functional elements
Information dependencies
Integration
Investment
A B S T R A C T
The benefits of integrated enterprise-wide information systems (IS),
such as Enterprise Resource Planning (ERP) systems, are widely
accepted. The implementation of such systems in large organisations
is established with many in their second or third generation.
However, in small to medium-sized enterprises (SMEs) the maturity
and extent of their IS infrastructure is less clear. In engineering SMEs,
this infrastructure needs to support not only business processes but
also the activities of design and manufacture.
In this case study, our goal is to provide a better understanding of
current IS infrastructure, the functional elements of IS infrastruc-
ture, integration and expenditures are explored in ten engineering
SMEs. A model of IS functionality is developed and used to identify
and classify functional elements within the firms and to compare
and contrast the IS infrastructures. The findings are contrasted with
the SME literature and conclusions and implications developed.
� 2010 Elsevier B.V. All rights reserved.
* Corresponding author. Tel.: +44 0 20 3073 8086; fax: +44 0 1223 386928.
E-mail address: [email protected] (P. Powell).
Contents lists available at ScienceDirect
Journal of Engineering and
Technology Management
journal homepage: www.elsevier.com/locate/jengtecman
0923-4748/$ – see front matter � 2010 Elsevier B.V. All rights reserved.
doi:10.1016/j.jengtecman.2010.03.004
Information systems need to support core business functions and to ensure that the overall
infrastructure is integrated. Integration provides accurate, timely information across the organisation.
One route to integration is through Enterprise Resource Planning (ERP) systems, which arose from
earlier developments of Materials Resource Planning (MRP) systems (Langenwalter, 1999). These
systems evolved from linking stores and production departments to their current manifestation that
includ ...
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Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
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A Graph-based and Declarative Approach to a Secure Resource Management in Smart Factories
1. A Graph-based and Declarative Approach to a
Secure Resource Management in Smart Factories
Alexander Lawall1
and Thomas Schaller2
1
IU International University of Applied Science,
Juri-Gagarin-Ring 152, 99084 Erfurt, Germany
2
University of Applied Sciences Hof, Alfons-Goppel-Platz 1, 95028 Hof, Germany
Abstract. The article presents an applied research using the Design
Science Research Methodology for securely managing resources of smart
factories via a graph-based approach combined with a declarative query
language. This query language can be used to find appropriate produc-
tion facilities that are able to fulfill specific manufacturing tasks. This
approach is aimed to solve the problem with the management effort for
production facilities using enumeration for naming these facilities for the
manufacturing tasks. Thus, the security is ensured by identifying the
“current” valid identities (resources). Additionally, the usage of deputy
relationships leads to alternative production facilities if resources have a
breakdown or have to be serviced which has an effect on the availability.
Keywords: Identity Management · Industry 4.0 · Smart Factory · Or-
ganizational Model· Access Control.
1 Industry 4.0, Smart Factories and Resource
Management
Production plants as we know them today are actually overthought within the
industry 4 initiative. Central production plans for manufacturing big numbers
of similar products are replaced by intelligent objects (agents) embedded in self-
organizing systems called smart factories [1]. These objects are cyber-physical
systems [2] using intelligent sensors for gathering information about the world
around them. Similar to multiagent systems [3,4] they are able to react to en-
vironmental changes and to generate plans for fulfilling their goals. So, if a
customer orders a product at a manufacturing company, an agent responsible
for the production of the article is created. This agent knows all about the bill of
material and the working plan for the creation of the product. Thus, the agent
encompasses the physical and cyber space [5]. On basis of this information, the
agent generates a plan how the product can be manufactured. For this he has
to communicate with agents representing the resources of the company [6].
1
DOI:10.5121/ijcis.2022.12301
2. Additionally, cyber–physical production systems consist of elements and sub-
systems that connect communications and interactions in production, of ma-
chines, processes to manufacturing networks [7]. Cyber-physical production sys-
tems summarize the cooperation and response to the assigned tasks. Such sys-
tems include i.a. operational sensor networks, smart actuators, information sys-
tems, communication protocols and many more [8]. Cyber–physical production
systems evolve the traditional automation pyramid [9]. The top-down hierarchy
of the traditional automation pyramid proceed from enterprise resource plan-
ning, plant management, process control, control (incl. PLCs) to field level [10].
Nowadays, cyber–physical production systems are a connected network with dif-
ferent systems of the traditional automation pyramid hierarchy as nodes. Thus,
the layered structure of the automation pyramid is transformed into a dense
interconnected network. This network is built with systems from layers of the
automation pyramid out of the field, control, supervisory, planning and manage-
ment level [11,12].
In this article we show a graph-based approach for maintaining the resources
(i.a. production systems/machines) of a smart factory and searching for valid
ones using a declarative query language. This language can be used by the pro-
duction agent looking for resources that are able to fulfill manufacturing tasks
of the working plan.
2 Graph-based Resource Management (GBRM)
This section describes the meta-model with its entity- and relation-types, an ex-
ample model for production facilities following this meta-model and the declara-
tive query language resulting in specific resources by traversing the graph-based
model.
Graph-based Resource Management (GBRM) consists of a meta-model for
describing the resources of an organization and a declarative language. Resources
encompass human and automatic agents (please see figure 1: the turners and
mills are machines, the assembly line is stuffed with humans.). They are located
in one organization, but in federated scenarios, other organizations can make
use of them as well (cf. [13]). Therefore, we will have a look at the meta-model,
also called organizational meta-model.
2.1 Organizational Meta-Model
The organizational model, depicted in figure 1 follows the organizational meta-
model3
that is formulated in this section. The excerpt of the meta-model consists
of the set of entity-types V and relation-types R.
3
The basic meta-model is formally described in [14] as an extension of the theory in
[15].
International Journal on Cryptography and Information Security (IJCIS), Vol. 12, No.3, September 2022
2
3. The characteristics of entity-types V = O ∪ F ∪ A of the meta-model are:
– Organizational units O = Oi
∪Oe
are for example departments, subdivisions,
groups, etc.
• Internal organizational units Oi
are used to model intra-organizational
organizational units (e.g. figure 1: Manufactoring Company).
• External organizational units Oe
are entity-types representing organi-
zational units from partner organizations (e.g. figure 1: Assembly Com-
pany). Thus, inter-organizational federations across company borders are
possible.
– Functional units F = Fi
∪ Fe
are roles respectively job functions in which
agents act.
• Internal functional units Fi
represent intra-orga-nizational functional
units like the turners of a manufacturing company (cf. figure 1).
• External functional units Fe
belong to partner companies.
– Human and automatic resources A = Ai
∪ Ae
encompass:
• Internal resources Ai
represent intra-organizational resources (e.g. Turner
1, Mill 4 and Assembly 1 in figure 1).
• External resources Ae
are used to specify resources from partner orga-
nizations (e.g. Assembly 1 – Assembly 4 of the Assembly Company in
figure 1).
The set of relation-types R = Rs∪Ro∪Ru formally defines the interconnections:
– Structural relation-type rs ∈ Rs with
rs ⊂ O × (O ∪ F) (1)
rs ⊂ F × (F ∪ A) (2)
– The sets4
of organization-specific relation-types Ro (deputy, supervision and
reporting) and user-defined relation-types Ru with ∀ro, rf , ra ∈ Ro ∪ Ru :
ro ⊂ O × (O ∪ F ∪ A) (3)
rf ⊂ F × (F ∪ A) (4)
ra ⊂ A × (F ∪ A) (5)
The structural relation-types rs in formulas (1) and (2) define the structural
interconnections between internal and external organizational units, functional
units and resources.
The formulas (3), (4) and (5) correspond to organization-specific and user-
defined relations that connect internal / external entities, cf. deputy relation
between the organizational units Manufacturing Company and Assembly Com-
pany in figure 1.
4
The validity of organization-specific and user-defined relations can be restricted by
constraints, cf. [16].
International Journal on Cryptography and Information Security (IJCIS), Vol. 12, No.3, September 2022
3
4. Hyperedges Lawall formalize in [17] hyperedges related to formula (5), ra ⊂
A × (F ∪ A). The start entity of the organization-specific and user-defined rela-
tions is a resource a ∈ A and the target entity is a functional unit or resource.
The validity of these relations can be restricted role-dependent using hyperedges.
The hyperedge starts with relations ra ∈ Ro ∪ Ru and ends in functional unit
f ∈ F. Thus, the relation ra is only valid if the start resource a of relation ra acts
in functional unit f. The syntax for role-dependent hyperedges rra
is described
in formula (6).
rra ⊆ ra × F (6)
Formula (4) formalizes relations rf ∈ Ro ∪ Ru : rf ⊂ F × (F ∪ A) starting
in functional unit f ∈ F and ending in a functional unit or resource. These
relations are not restricted with hyperedges. The acting functional unit f is
already contained in relation rf and as a consequence considered.
The organization-specific and user-defined relations ro ∈ Ro ∪ Ru : ro ⊂
O × (O ∪ F ∪ A) in formula (3) can also be restricted with hyperedges rro
.
Relations ro start in an organizational unit o ∈ O and end in an organizational
unit, a functional unit or resource. The hyperedge rro restricts the validity of
relation ro concerning the functional unit f ∈ F, cf. formula (7).
rro ⊆ ro × F (7)
The semantics of hyperedge rro
differ from hyperedge rra
. The relation ro is
only valid for the functional unit f respectively the connected resources. For
example, the deputy relation in figure 1 between the Manufacturing Company
and the Assembly Company is only valid for the functional unit Assembly – re-
spectively resources Assembly 1 to 3 – of the Manufacturing Company. Thus,
this deputyship is not effective for the remaining functional units Turner and
Mill and the connected resources Turner 1 to 3 and Mill 1 to 4.
Self-references are used to define recursive relations on entities. It simpli-
fies the interconnection of entities using organization-specific and user-defined
relations. The deputy self-reference of the functional unit Assembly, as depicted
in figure 1, indicates a deputyship between the subordinate resources Assem-
bly 1 to 3 of the Manufacturing Company. Otherwise, all resources have to be
interconnected in particular, cf. [18].
2.2 Organizational Model
Figure 1 depicts an excerpt of the organizational model of a manufacturing
company producing wooden chairs. The model encompasses the internal organi-
zational unit Manufacturing Company with the subordinate internal functional
units Turner, Mill and Assembly. The internal resources Turner 1 to Turner
3 are related to Turner, Mill 1 to Mill 4 belong to Mill and Assembly 1 to
Assembly 4 are part of the internal functional unit Assembly.
International Journal on Cryptography and Information Security (IJCIS), Vol. 12, No.3, September 2022
4
5. Fig. 1. Federation between Partner Companies
Additionally, there exists an external5
partner company (assembly company)
that can take over assembly tasks on load peaks or cyber attacks against the
supply chain [19]. The federation between the manufacturing company and the
assembly company extends the aforementioned organizational model. The exter-
nal organizational unit Assembly Company encompasses the external functional
unit Assembly in conjunction with the external resources Assembly 1 to Assem-
bly 4.
The organization-specific deputy relation between the Manufacturing Com-
pany and the Assembly Company follows formula (3). In addition, the relation is
restricted with an hyperedge that ends in the internal functional unit Assembly,
cf. formula (7). The self-reference of this entity indicates a mutually deputyship
between the internal Assemply resources.
The entities of the organizational model contain attributes. Attributes can
be of any kind (e.g. workpieceLength). Table 1 describes an excerpt of attributes
in conjunction with their values. These attribute-value pairs reflect the charac-
teristics of concrete resources.
2.3 Declarative Query Language
In this chapter we describe a query language that in addition to the organization
model can be used to find specific resources based on relations and attributes.
A query language expression can be based on entities, relations and attributes
that are included in the organizational model. The entities are concrete organiza-
5
The automated propagation of model elements (entities, relations and attributes) to
partner organizations is described in [13].
International Journal on Cryptography and Information Security (IJCIS), Vol. 12, No.3, September 2022
5
6. Resource Attribute Value
Turner 1 workpieceLength 30
workpieceKind octagonal
... ...
Turner 2 workpieceLength 60
workpieceKind octagonal
... ...
Turner 3 workpieceLength 40
workpieceKind square
... ...
Mill 1 maxLength 100cm
maxWidth 100cm
maxHeight 20 cm
Mill 2 .... ...
Table 1. Attributes of Resources
tional units, functional units and resources. Relations are concrete organization-
specific – deputy, supervisor and reporter – and user-defined relations. Attributes
are similar to user-defined relations. Their types are freely definable as needed in
the organizational model. The concrete relations and attributes can be referred
by language expressions.
The following syntax is described in [17]. It is repeated to give an overview
concerning the power of the query language. The language expressions used in
this contribution do not make use of all production rules.
The tuple G = (N, Σ, P, SG) of the context-free grammar G for defining
queries consists of:
– The set of non-terminals N = {start, query, actor, funits, funit, oudef,
ounits, ounit, relationTokens, withParams, contextDef, attConstraints,
kcv, parameter, kvp, id, string}
– The alphabet of terminals Σ = {‘a’,‘b’,...,‘z’,‘A’,‘B’, ...,‘Z’,‘ä’,‘ü’,‘ö’,‘Ä’,‘Ü’,‘Ö’,
‘0’,‘1’,...,‘9’,‘ ’,‘-’,‘(’,‘)’,‘,’,‘.’, ‘*’,‘=’,‘<’,‘>’}
– The set of production rules P6
start → query | query logic query | ε
query → actor|actor ‘AS’ funits
query → query ‘NOT’ query
query → query ‘FALLBACKTO’ query
query → query ‘WITH’ withParams
query → funits ‘(’oudef‘)’
query → relationTokens ‘(’query‘)’
query → ‘(’query logic query‘)’
query → ‘(’query‘).’attConstraints
6
Meaning of meta-symbols: ? means 0 or 1 and * means 0 to ∞ occurrences.
International Journal on Cryptography and Information Security (IJCIS), Vol. 12, No.3, September 2022
6
7. actor → ‘*’ |id|string
funits → funit| ‘(’funit logic funit‘)’
funit → ‘*’ |id|string
oudef → ounit|ounits logic ounits
ounits → ounit| ‘(’ounits logic ounits‘)’
ounit → ‘*’ |id|string|ounit ‘SUBS’
relationTokens → (‘ALL’ | ‘ANY’)? id (‘OF’|‘TO’)
withParams → contextDef | parameter |
withParams ‘,’ withParams
contextDef → ‘CONTEXT=’ context (‘,’ context)∗
attConstraints → ‘ATT.’ kcv
kcv → id comp string| ‘(’kcv logic kcv‘)’
parameter → kvp (‘,’ kvp)∗
kvp → id ‘=’ string
logic → ‘AND’ | ‘OR’
comp → (‘=’ | ‘<=’ | ‘>=’ | ‘<’ | ‘>’ | ‘!=’)
id → ([‘a’-‘z’,‘A’-‘Z’] | ‘ ’ | ‘Ä’ | ‘ä’ | ‘Ü’ | ‘ü’ | ‘Ö’ | ‘ö’) ([‘a’-‘z’,‘A’-‘Z’] | ‘Ä’
| ‘ä’ | ‘Ü’ | ‘ü’ | ‘Ö’ | ‘ö’ |[0 − 9]| ‘ ’ | ‘-’)∗
string → ‘"’ id ‘"’
– The set of start symbols SG = {start}
The informal semantics of the declarative query language is explained be-
low. The language query expressions explicate the reference to entities, relations
and/or attributes:
– The language expression (Turner AND/OR Mill)(*). ATT.
(workpieceLength ≥ "40" AND workpieceKind = "octagonal") refers to
1. Entities: (Turner AND/OR Mill)(*)
(a) Functional Units: Turner and Mill. The result set of resources
is determined by the terminal AND respectively OR. AND means that
resources have to be simultaneously assigned to Turner and Mill.
However, OR indicates that resources have to be Turner and/or Mill.
(b) Organizational Units: *, arbitrary organizational units. The spec-
ification of concrete organizational units is similar to the definition
of functional units. AND and OR are also semantically identical.
2. Attributes: workpieceLength ≥ "40" AND
workpieceKind = "octagonal"
After traversing the organizational model for appropriate entities, result-
ing resources are proven if the requirements of attributes are fulfilled.
– DEPUTY OF(Assembly(Manufacturing Company).ATT.
(workpieceLength ≥ "30")) refers to
1. Entities: Assembly(Manufacturing Company)
(a) Functional Unit: Assembly. The intermediate result set of the
query contains the internal resources Assembly 1, Assembly 2 and
Assembly 3 and the external resources Assembly 1 to Assembly 4.
(b) Organizational Unit: The entity Manufacturing Company induces
a reduction of the intermediate result set to the internal resources
Assembly 1 to Assembly 4.
International Journal on Cryptography and Information Security (IJCIS), Vol. 12, No.3, September 2022
7
8. 2. Relations: DEPUTY OF(...)
The intermediate result set of the inner query "..." is the start for the
traversal following specific relations. The detailed algorithm searching
for concrete organization-specific and user-defined relations is described
in [18]. In this example expression is the deputy relation integrated. The
lookup starts in the resource level. There are no deputy relations, cf.
figure 1.
In the functional unit level is a self-reference that indicates a mutual
deputyship of the resources. The organizational unit level will be con-
sidered if no suitable deputy is available.
The deputy relation between the Manufacturing Company and the As-
sembly Company is an hyperedge ending in functional unit Assembly, cf.
formula (7). Thus, the deputy relation is only valid for the functional
unit Assembly. The intermediate result set then consists of the external
resources Assembly 1 to Assembly 4.
3. Attributes: workpieceLength ≥ "30"
The final step of the lookup algorithm proves the fulfillment of all at-
tribute requirements. The result set of the remaining resources is handed
back to the “requester”.
3 GBRM and Smart Factories
In this section, we demonstrate how the idea of smart factories and Graph-based
Resource Management can be combined. Smart factory environments are usually
decentrally organized. In order to tackle that fact, two crucial issues have to be
addressed.
The first question is how the products that have to be produced know about
the production facilities and their availability. This can be addressed by GBRM.
Here a model of a production environment is set up, containing all facilities,
their abilities, their availability and replacement/deputy relations (please see
section 2.2). The product can formulate an organization query and receives the
matching facilities.
Second, if the product knows the available resources, the next question is,
which resource is chosen for the single working steps and when.
From the viewpoint of a production facility a lot of products are concurring
for the dispatching of their working steps. So there has to be a strategy that
leads to a facility working plan. Options for that like optimization on basis of
the marginal return and auctions (e.g. when subcontractors can be used) are
discussed deeply in [20]. In this article we will not address this point specifically.
In the following we will concentrate on the first question and will explain
how the right production resources can be found using GBRM. Let us assume
we would like to produce a chair with four legs, one seat and one back. According
International Journal on Cryptography and Information Security (IJCIS), Vol. 12, No.3, September 2022
8
9. to the working plan in table 2 we have to turn the four legs and to mill the seat
and the back all with specific dimensions 7
.
Task Number Task Specification Amount
1 Turn chair leg Turn, 40cm, octagonal 4
2 Mill seat Mill, 30cm x 35cm x 5cm 1
3 Mill back rest Mill, 20cm x 35cm x 5cm 1
4 Assemble chair Assemble 1
Table 2. Working Plan of a Chair
After that we can assemble the single components of the chair. For the mo-
ment we disregard the fact that the leg, the seat and the chair can be produced
in parallel. If an order for one chair arrives in our company a virtual chair object
CV irt will be created. This object knows the working plan and needs to figure
out which machineries or production systems are able to carry out the single
manufacturing operations. This can easily be done if there is a GBRM model
of the underlying manufacturing system. If this model exists the only thing
CV irt has to do, is to specify a query and send it to the Organization-Server
8
. The server determines the resources that are able to carry out the speci-
fied production steps and sends them back to the CV irt object. In our example
the query (Turner)(*).ATT.(workpieceLength ≥ "40" AND workpieceKind
= "octagonal") will lead to the result that only turner 2 will be appropriate.
Via the use of deputy relations and propagation nodes alternative production
scenarios can be modelled. If a production component has to be serviced, has a
breakdown or in case of an employee beeing sick, it is easy to find a deputy. In
figure 1 the hyperedge at the assembly node means that an assembly agent can
take over the task of one of it’s colleagues. If no resource is available propagation
nodes denote that a task can be carried out by a subcontractor. Figure 1 shows
the option to use a subcontractor for the assembly operation.
In a decentral smart factory environment the production facilities are repre-
sented by agents. On receiving the result set of the possible production resources
CV irt can start negotiating with the agents representing those facilities. The ne-
gotiations can follow different strategies with related patterns and optimization
criteria. Examples are bilateral trading, auctioning or request for proposals. A
deep insight on this subject is given in [20].
4 Conclusion and Outlook
In this paper we present an approach that brings the concept of smart factories
and Graph-based Resource Management together. Because necessary production
7
For clarification issues we leave out the bill of materials.
8
There is a implementation of the GBRM theory called C-Org.
International Journal on Cryptography and Information Security (IJCIS), Vol. 12, No.3, September 2022
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10. resources are described instead of enumerated, the maintenance effort will be
significantly reduced and at the same time security in sense of finding valid
identities (here human or automatic resources) is increased. For example, if a
facility or a new manufacturing partner is added to the manufacturing system,
the only thing is to update the graph model. From this moment on, all requests of
products will consider the new situation. Via the usage of deputy relationships
the model is robust against disturbances like machine breakdowns, illness or
cyber attacks targeting the availability of resources.
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