Nowadays, industries face very strong challenges because of the high competitiveness between them. In fact, they are required to offer products with high quality and minimum cost in the minimum time. Since most of the characteristics and costs of the product and its manufacturing process are fixed in the design phase, this paper is focused on this strategic phase. Indeed, a new integrated product design approach is presented. It considers at the same time design requirements, materials characteristics, manufacturing parameters and the assembly process specifications. The developed approach is quantitative. Actually, the decision making is based on all its steps on objective and subjective indicators. To validate the integrated approach, a case study on the Schrader Robot is developed. This application allows to choose the most appropriate materials, manufacturing processes and assembly solution of its different components.
Nowadays, competitiveness between industries has become very strong. Thus, industries are faced to serious challenges in terms of products qualities, time development and production cost. As assembly operations difficulties cause a big part of production problems, the integration of assembly selection since the earlier product life cycle phases has become a necessity for every company in order to survive. However, despite the large number of approaches that have been proposed in order to achieve this integration goal, many other problems are still present. It is in this context that a flexible and automated decision making system is proposed. It is based on ontologies and also on the Case Based Reasoning (CBR) and Rule Based Reasoning (RBR) concepts. Indeed, this system is an automation of the integrated DFMMA approach, in particular its assembly solution selection methodology. The developed system permits to designers avoiding the redundancy in the works by benefiting from their previous studies and their experience. In addition to that, it facilitates and automates the assembly solution selection even if the number of assembly alternatives is high. Finally, to illustrate the efficacy of the proposed system, a case of study is developed in the end of the work.
Over the last decades, there has been growing pressure on industrial companies to offer to their costumers products with high quality, in the minimum deadlines and with reasonable prices. Since the design phase plays a key role to achieve these difficult goals, many traditional, DFX (Design For X) and integrated approaches have been proposed. However, many limits are still present. Thus, the main objectives of this work were first to identify these limits and then to overcome them by proposing and developing an automated framework for integrated product design. In this work, we automated the integrated DFMMA (Design For Materials, Manufacturing and Assembly) approach by developing an architecture composed of four levels, namely: the Common Information Modeling Level, the Selection Systems Level, the Inference and Computation Level and finally the Application Level. The proposed automated system is based on ontologies, on the CBR (Cases Based Reasoning) and the RBR (Rules Based Reasoning). The first main result obtained throughout the contributions consists on the integration of Manufacturing process selection, Assembly solution selection and materials selection in one integrated design approach. The second main result obtained consists on the exploitation of all the previous design studies developed by the design team and the ability to reuse the designers experience throughout the case based reasoning used in the proposed architecture. Another important result consists on the formalization and the automation of the execution of the design rules and the ability to infer new results and to check inconsistencies in the developed product using the data and information modeled in the ontological model and throughout the Cases Based Reasoning that we have incorporated in the developed approach. In this way, the redundancy in work and the difficulties faced in case of having a high number of design alternatives are avoided. Consequently, the product quality increases and wastes of time and money decrease. Finally, to validate the functioning and the efficacy of the proposed DFMMA system, an application on the design of a complex mechanical product is developed in the end of the work.
Currently, the industrial and economic environment is highly competitive, forcing companies to keep up with technological progress and to be efficient in terms of quality and responsiveness, not only to survive, but also to dominate the market. So, to achieve this goal, companies are always looking to master their production processes, as well as to enlarge their range of products, either by developing new products or by improving old ones. This confronts companies to many problems, including the identification of adequate and optimal production parameters for the development of their products. In this context, a decision making system based on digital twins (DT), case-based reasoning (CBR) and Ontologies is proposed. The originality of this work lies in the fact that it combines three emerging artificial intelligence tools for modeling, reasoning and decision making. Thus, this work proposes a new flexible and automated system that ensures an optimal selection of production parameters for a given complex product. An industrial case of study is developed to illustrate the effectiveness of the proposed approach.
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