Knowledge Management Based Process Planning System

Process planning knowledge (PPK) is one of the most important knowledge in production manufacturing enterprise. The traditional method of organizing data into knowledge relies on manual analysis and interpretation. This paper analyzes the source and composing of process planning knowledge and state of arts on process planning discovery in production manufacturing enterprise. On the basis of the application of computer aided process planning (CAPP) system in mechanical manufacturing enterprise, the concept of process planning information model (PPIM) is proposed based on process planning databases. This paper provides a CAPP database developed in own research, clarifying how PPK and PPIM in CAPP database are related both to each other and to related fields, the technology database of process planning knowledge discovery is modeled based on object-oriented model-driven technology, and the process planning knowledge discovery script is designed

Continuous Innovativeness Supported by Integrated Computer-based and PLM Solutions

Motivating product designers and research groups to think "outside the box" is of special interest for companies and research centres willing to remain competitive even in times of crisis. It is proven that those leaders which realized that the continuous innovativeness is a result of in-crossed creativity support and sustained quality are more prepared for changes and bring their companies to success. Innovation management has significantly changed towards approaches that support innovation process especially the early phases in which creativity is more than needed. Approaches towards Product Lifecycle Management are changed also. In the advent of Web.2.0 these approaches have become increasingly computer-based enabling access to large user communities evolving into open or semi-open Enterprise 2.0 platforms. The parallel development of tools that could support innovative (creative) thinking based on off-line so-called Classical methods and IT solutions which claim to be collaborative and support idea generation brings to doubts about the choice of most suitable solutions. On the other side, companies are more eager to use solutions which can follow the different business processes including product lifecycle and that can aid their innovative capacity by being closer to customers. In this research an integrated solution is suggested that includes ideation and collaborative tools cross-used with PLM solutions which could support continuous innovativeness. Existing concepts and approaches on computer-based solutions for innovation and PLM are presented, with a focus on the "creative" phases such as product design that elevates the success of the products. The overview is made with a scope to underline the necessity of integration of the pragmatic aspects of creativity into solutions having features recognized with literature and test analysis that could support mainly creative thinking and knowledge sharing in companie

Process of innovation in product lifecycle management business strategy

This article proposes a scenario of Product Lifecycle Management (PLM), as a innovative business strategy based on the analysis of business drivers, industry requirements, limit of current solution, and recent state-of-the-art review in the domain related to PLM. Potential industrial impact of the developed PLM technology solutions is analyzed. It is hoped that the proposed PLM technology solutions will form the frontier basis for further research, development, and application of PLM systems to quickly adapt to the dynamic changing market for industry companies to pursue the most advanced competitiveness. This article presents a process oriented framework to support effective PLM implementation with a set of lifecycle oriented business process reference models which links the necessary fundamental concepts, enterprise knowledge and software solutions to effectively deploy PL

Intelligent approach for optimal modeling of manufacturing systems

Purpose: This paper proposes a methodology for analysis and modeling of machining conditions by optimal determination of the cutting parameters in multi-pass NC machining operations. Design/methodology/approach: This paper proposes optimal determination of the cutting parameters by using a deterministic method (DM) and a genetic algorithm (GA). In the research, it is created the complex mathematical model for design of the cutting condition for machining process. In next phase, it is created a numerical algorithm for optimization and its developed software called OPTIMAD (Optimization of Milling and Drilling), by using DM. Also, it is created software, caled GAMO (Genetic Algorithm for Machining Operation), as a GA program modul based of the elementary pseudo-code for GA, with using the MatLAB program language and C++ developed rutines. Findings: Modeling of optimal cutting parameters, as a part of process planning, enables generating of manufacturing data and knowledge representation in machining process plan. Verification of optimized cutting parameters in real machining condition has done confirmation for design of cutting parameters by virtual modelling, using optimization methodologies OPTIMAD and GAMO. Research limitations/implications: The optimization approach is proposed and its uses optimization of mathematical model using a classic and heuristic methods. In this research, GA based optimization method and deterministic optimization method are developed and there implementations into real manufacturing process are analyzed. Practical implications: Use of proposed aproach resulted in improved productivity and efficiency of machining process where the cutting conditions are designed by OPTIMAD and GAMO softwares. In the future, this results will be integrated in computer system for process planning. Originality/value: The paper describes a method for eliminating the need for using the extensive user intervention in CAM processes, during determination of cutting parameters. Keywords: Analysis and modelling; Technological design; CAMS; Optimisation; NC machining proces