484 research outputs found
Application of ”ART SIMULATOR” for Manufacturing Similarity Identification in Group Technology Design - Chapter 10
This chapter 10 carried out the exceptional implementation of ART-1 neural network in the analysis of the manufacturing similarity of the cylindrical parts within the group technology design. Established concept of the group technology design begins from the complex part of the group or the group representative. Group representative has all the geometrical elements of the parts in group, and manufacturing procedure may be applied to the machining of any part in the group. The complex part may be realistic or a hypothetical one. The ART-1 artificial neural network provided manufacturing classification according to the geometrical similarities of work-pieces for the group of cylindrical parts. For the manufacturing similarity identification within the group technology design, software package "ART Simulator" is developed and presented in this chapter
Delivery Time Uncertainty in Dynamic Supply Networks
Today, business models are invariably part of complex networks of suppliers, manufacturers and distributors. Uncertainty is recognized as an inevitable characteristic of supply networks and managers need to be aware of its specifications and consequences of that. Therefore, understanding, acknowledgement, and moderation of the causes and effect of uncertainty is crucial. Under-controlled uncertainty leads to the improvement of networks performances and reliable networks. This paper complies with uncertain complex supply networks with their fundamental types. By defining critical routes in PERT networks, a combination of stochastic and mathematical models calculates the delivery time uncertainty in supply networks. This approach can be used as a tool for managers to control and monitor uncertainty in complex networks
Knowledge discovery for moderating collaborative projects
In today's global market environment, enterprises are increasingly turning towards
collaboration in projects to leverage their resources, skills and expertise, and
simultaneously address the challenges posed in diverse and competitive markets.
Moderators, which are knowledge based systems have successfully been used to support
collaborative teams by raising awareness of problems or conflicts. However, the
functioning of a moderator is limited to the knowledge it has about the team members.
Knowledge acquisition, learning and updating of knowledge are the major challenges for
a Moderator's implementation. To address these challenges a Knowledge discOvery And
daTa minINg inteGrated (KOATING) framework is presented for Moderators to enable them to continuously learn from the operational databases of the company and semi-automatically update the corresponding expert module. The architecture for the Universal Knowledge Moderator (UKM) shows how the existing moderators can be extended to support global manufacturing.
A method for designing and developing the knowledge acquisition module of the Moderator for manual and semi-automatic update of knowledge is documented using the Unified Modelling Language (UML). UML has been used to explore the static structure and dynamic behaviour, and describe the system analysis, system design and system
development aspects of the proposed KOATING framework. The proof of design has been presented using a case study for a collaborative project in
the form of construction project supply chain. It has been shown that Moderators can
"learn" by extracting various kinds of knowledge from Post Project Reports (PPRs) using
different types of text mining techniques. Furthermore, it also proposed that the
knowledge discovery integrated moderators can be used to support and enhance
collaboration by identifying appropriate business opportunities and identifying
corresponding partners for creation of a virtual organization. A case study is presented in
the context of a UK based SME. Finally, this thesis concludes by summarizing the thesis,
outlining its novelties and contributions, and recommending future research
Demand Response in Smart Grids
The Special Issue “Demand Response in Smart Grids” includes 11 papers on a variety of topics. The success of this Special Issue demonstrates the relevance of demand response programs and events in the operation of power and energy systems at both the distribution level and at the wide power system level. This reprint addresses the design, implementation, and operation of demand response programs, with focus on methods and techniques to achieve an optimized operation as well as on the electricity consumer
Smart Industry - Better Management
The ebook edition of this title is Open Access and freely available to read online.
Smart industry requires better management. As industrial and production systems are future-proofed, becoming smart and interconnected through use of new manufacturing and product technologies, work is advancing on improving product needs, volume, timing, resource efficiency, and cost, optimally using supply chains.
Presenting innovative, evidence-based, and cutting-edge case studies, with new conceptualizations and viewpoints on management, Smart Industry, Better Management explores concepts in product systems, use of cyber physical systems, digitization, interconnectivity, and new manufacturing and product technologies.
Contributions to this volume highlight the high degree of flexibility in people management, production, including product needs, volume, timing, resource efficiency and cost in being able to finely adjust to customer needs and make full use of supply chains for value creation. Smart Industry, Better Management illustrates how industry can enabled by a more network-centric approach, making use of the value of information and the latest available proven manufacturing techniques
EG-ICE 2021 Workshop on Intelligent Computing in Engineering
The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways
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