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.
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This work was supported by FCT “Fundação para a Ciência e a Tecnologia” under the program: PEST2015-2020, reference: UID/CEC/00319/2013.
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Vieira, G.G., Varela, L.R., Ribeiro, R.A. (2016). A Knowledge Based System for Supporting Sustainable Industrial Management in a Clothes Manufacturing Company Based on a Data Fusion Model. In: Liu, S., Delibašić, B., Oderanti, F. (eds) Decision Support Systems VI - Addressing Sustainability and Societal Challenges. ICDSST 2016. Lecture Notes in Business Information Processing, vol 250. Springer, Cham. https://doi.org/10.1007/978-3-319-32877-5_9
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