Correlated Process Failure Mode Modeling And Process Schema Analysis For Green Manufacturing

The problem of environmental pollution caused by manufacturing industry is widely concerned all over the world since the resource exhaustion and environmental deterioration are becoming serious threats to human survival. The deeply study of technologies and methodologies for green process planning has important theoretical meaning and practical value for the energy saving and emission reduction of manufacturing industry. In this dissertation, correlated process failure mode modeling and process schema analysis for green manufacturing are put forward and studied based on a review of current research on the methods and technologies of process schema design. Some key technologies and methodologies are deeply investigated. These technologies and methodologies include the modeling of correlated process failure mode, a hierarchy process schema planning and regeneration, decision making of process parameter selection for green manufacturing, and the satisfaction evaluation on process schema. The proposed methods and technologies are applied to the process schema planning for complex automobile parts manufacture. Results indicate the validity of the proposed methods with a better reliability.The organization of this thesis is as follows:In chapter1, a review of product process planning with the focus on design for environment is given. The deficiencies of present research for product process planning and green manufacturing is proposed, and then the research content and architecture of this dissertation is presented.In chapter2, considering some inherent shortcomings of the conventional process failure mode expression and application, a correlated process failure mode modeling is proposed for reprioritization of interrelated failure modes with linguistic vagueness. The fuzzy linguistic knowledge in an evaluation of failure mode is quantified by fuzzy set theory, and an effective number of each failure mode is acquired with a fuzzy-modified technique for order preference by similarity to ideal solution (TOPSIS). A digraph of direct relations between failure modes is constructed, and then a matrix of failure influences is gained using decision making trial and evaluation laboratory (DEMATEL) method. The risk evaluation of failure modes in a complex system with linguistic vagueness is completed with obtained causal degree of each failure mode from the matrix of failure influences. The modeling of correlated process failure mode can be contributed to the application of process failure knowledge in the product process planning.In chapter3, According to the parallelism of product design and process planning in product development process and the regular pattern from roughness to precision of product design information, the product design process is divided into conceptual process, rough process and detail process of three job levels. Each level’s main process activities are modeled by Integrated Computer Aided Manufacturing DEFinition method (IDEF), and the hierarchical process planning model of three levels is constructed with an improvement of time parallelism between product design and process planning. Furthermore, based on the model of correlated process failure modes, an optimization and regeneration of process schema are put forward using the process failure knowledge. The application result shows that it helps to forward the process design stage and improve the manufacture reliability.In chapter4, to solve the problem of process parameter selection and optimization for green manufacturing, a multi-input, process and multi-output grey model for green manufacturing is developed aiming at converting a procedure of process parameter selection and optimization into a multiple-criteria decision making procedure. The fuzzy linguistic expert knowledge in a green evaluation of product manufacturing process is quantified using triangular fuzzy number. Decision making trial and evaluation laboratory (DEMATEL) method is extended in fuzzy environment to deal with the correlation of process evaluation factors and to allocate its weighing factor in accordance with its influence. Furthermore, process parameter selection for green manufacturing is carried out based on a comprehensive DEMATEL-VIKOR algorithm. As a result, a best or compromise set for green process parameter values is obtained with a balanced consideration between maximum group utility and minimum individual regret, and the process controllable factor for green manufacturing is ranked aiming at a better adjustment for process parameter optimization. The better process parameter for green manufacturing is effectively obtained by this proposed method.In chapter5, considering the shortcomings of given meaningless weighing vector in process schema decision making procedure, a decision making method of process schema is proposed for green manufacturing based on decision maker’s preference and mutual feedback. A layered decision making framework for the selection of process schema is formed by detailed description of user layer, preference capture layer, decision making layer, schema evaluation and process schema layer. The fuzzy linguistic knowledge in an evaluation of green manufacturing is quantified by trapezoid fuzzy number. Preference functions reflecting decision maker’s subjective idea are built based on acquired preference information for different objective, and then a physical programming model for the selection of satisfied process schema is constructed. A process schema evaluation for green manufacturing based on the fuzzy physical programming model and mutual feedback is completed by preference information feedback between decision maker and selected process schema.In chapter6, some process planning cases of automotive parts are studied with the theories and methods of correlated process failure mode modeling and process schema analysis for green manufacturing, and the results show the validity and feasibility of the proposed methods and technologies in this dissertation.In Chapter7, the dissertation is summarized and the future research work is prospected.