Collaborative Network Platform for Multi-site Production

Arrais-Castro, António; Varela, Leonilde; Putnik, Goran D.; Ribeiro, Rita A.

doi:10.1007/978-3-642-32191-7_1

Cited by 10 publications

(5 citation statements)

References 18 publications

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“…Through this system, the information level of logistics enterprises has been effectively improved, and the management costs of logistics enterprises have been reduced, and a better user experience has been brought to the users. [ 9 – 13 ]…”

Section: Discussionmentioning

confidence: 99%

“…rough this system, the information level of logistics enterprises has been effectively improved, and the management costs of logistics enterprises have been reduced, and a better user experience has been brought to the users. [9][10][11][12][13] Data Availability e datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.…”

Section: Discussionmentioning

confidence: 99%

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B/S-Based Construction of a Big Data Logistics Platform

Zhang

2022

Computational Intelligence and Neuroscience

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Due to the overwhelming characteristic of the Internet of Things, devices belonging to these networks are utilized in almost every domain of real life in order to improve the lifestyle of humans. However, these networks result in a huge amount of data related to different application domains, leading to another important research aspect, i.e., big data and cloud computing. Big data and cloud computing technologies in the logistics field have experienced initial contact, gradual penetration, and widespread application. Moreover, it supports traditional logistics to upgrade to smart logistics, aiming to achieve the fundamental requirements of today’s logistics industry and reduce costs with enhanced efficiency. However, the big data and cloud computing wisdom logistics model still has many problems in the construction of logistics public information platforms, end coordination development, government platform construction, and so on, in order to solve the problems of low efficiency, high cost, and low service satisfaction of traditional logistics. In this article, we have designed a new big data-enabled logistics detection system that is based on B/S architecture, constructed a smart logistics model consisting of a supply subsystem, demand subsystem, and supervision subsystem, and finally realized the operation process of the smart logistics model based on big data cloud computing.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

B/S-Based Construction of a Big Data Logistics Platform

Zhang

2022

Computational Intelligence and Neuroscience

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“…The platform supports the dynamic selection of business partners and suppliers by combining a dynamic decision model, based on the works (Jassabi et al, 2014;Campanella et al, 2012;Campanella et al, 2011), with an information fusion method (Ribeiro et al, 2013), to support partner evaluation and selection, integrating historical information, present status and forecasting about future information. The current paper complements the work in (Arrais-Castro et al, 2012;Arrais-Castro et al, 2014), by exploiting an illustrative example, which demonstrates the performance of the used DMCDM adapted model.…”

Section: Introductionmentioning

confidence: 68%

Collaborative Negotiation Platform using a Dynamic Multi-Criteria Decision Model

Arrais-Castro

Varela

Putnik

et al. 2015

International Journal of Decision Support System Technology

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Due to globalization, companies are frequently pushed to grow outside their political and geographical boundaries, forcing them to increase product diversification. As a side effect they can also optimize their resource's management by looking at potential businesses for improving their relations with customers and/or open new markets through partnerships. In this context, implementing agile collaboration networks between businesses is a requirement. This paper proposes an approach to support the selection of businesses in the context of collaborative-networked organizations, through a negotiation process controlled by agents, which is based on a dynamic multi-criteria decision model (DMCDM). The approach combines a dynamic decision making approach - using past, current and future information - with a software agents approach, which autonomously captures business opportunities, select business partners, as well as award and process associated orders. An illustrative example of evaluation and selection of business partners clarifies the dynamic method.

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“…In the literature, many interesting works can be found related to manufacturing management frameworks and approaches [1][2][3][4][5][6][7][8][9][10][11][12]. The research project in [1] addresses the emergence of interactive manufacturing management at three levels: sector, system and enabling technologies.…”

Section: Background Contextmentioning

confidence: 99%

“…An example is the necessity to accurately plan manufacturing resources usage, as the industrial manufacturing environment is no longer working isolated for satisfying its own manufacturing orders, but they also have to satisfy production needs from other outside orders. Therefore, industrial companies have to form strategic relationships with business partners to increase their responsiveness to market changes and to share resources more effectively and efficiently, through reliable decision support systems for supporting manufacturing management [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

A Knowledge Based System for Supporting Sustainable Industrial Management in a Clothes Manufacturing Company Based on a Data Fusion Model

Vieira

Varela

Ribeiro

2016

Lecture Notes in Business Information Processing

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In this paper we propose a knowledge based system (KBS), based on smart objects and a data fusion model to support industrial management decision making applied to a clothes manufacturing enterprise. The management processes cover factory-production levels to higher decision-making levels. Therefore, the proposed KBS contributes to solving different kind of decision problems, including factory supervision, production planning and control, productivity management, real-time monitoring, and data acquisition and processing. The web access via different middleware devices and tools at different process levels, along with the use of integrated algorithms, decision methods, and smart objects, promote an optimized use of knowledge and resources. In this paper the proposed KBS is introduced and an example of its use is illustrated with an example of a clothes manufacturing resources selection, using the embedded dynamic multi-criteria fusion model.

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Collaborative Network Platform for Multi-site Production

Cited by 10 publications

References 18 publications

B/S-Based Construction of a Big Data Logistics Platform

B/S-Based Construction of a Big Data Logistics Platform

Collaborative Negotiation Platform using a Dynamic Multi-Criteria Decision Model

A Knowledge Based System for Supporting Sustainable Industrial Management in a Clothes Manufacturing Company Based on a Data Fusion Model

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