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

Abstract

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.

A Review of Smart Contract Blockchain Based on Multi-Criteria Analysis: Challenges and Motivations

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“…After the approval of an order, the resource establishes direct relationship with the client and executes the production order. The resource may give permission for the client to see the production order to be executed and may allow the client to control its use on distance (when the resource is a machine, a computer or software), either from the control room, the PC, or from a mobile device, and can even be remotely operated (Vieira et al, 2016). Figure 1 illustrated the platform architecture implemented in the textile factory studied and Figure 2 some of the main forms of implementation according possible interactions that can be established with different kind of machines, tools or other peripherals.…”