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In this paper we describe how our Smart Virtual Product Development (SVPD) system can be used to enhance product inspection planning. The SVPD system is comprised of three main modules, these being the design knowledge management (DKM) module, the manufacturing capability and process planning (MCAPP) module, and the product inspection planning (PIP) module. Experiential knowledge relating to formal decisional events is collected, stored and used by the system in the form of set of experiences (SOEs). Here we discuss the working mechanism of the PIP module and show how experiential knowledge relating to the inspection of products that have features and functions in common can be used to enhance product inspection planning during early stages of product development. Our discussion commences with an introduction to fundamental concepts and a general system overview. We then describe the development of our SVPD system's PIP module, and a case study we undertook for validation purposes. Results of the case study show that our system is capable of supporting product inspection planning in smart manufacturing, and thus has a vital role to play in Industry 4.0. [ABSTRACT FROM AUTHOR]

This paper proposes the Smart Virtual Product Development (SVPD) system, which enhances the industrial product manufacturing processes. The proposed system comprises of three main modules: design knowledge management (DKM), manufacturing capability analysis and process planning (MCAPP), and product inspection planning (PIP). Smart virtual product development system collects, stores, and uses experiential knowledge from formal decisional events in the form of set of experience (SOE). This research explains the working mechanism of MCAPP module, and shows how manufacturing knowledge of similar products having some common features and functions is used to enrich the manufacturing process. First, the basic description and principles of the approach are introduced, then the prototype version of the system is developed and tested for manufacturing capability and process planning (MCAPP) module for the case study, which verifies the feasibility of the proposed approach. The presented system successfully supports smart manufacturing, and can play a vital role in Industry 4.0. [ABSTRACT FROM AUTHOR]

This paper presents a system capable of enhancing product development process for industrial manufactured products. The system is known as Smart Virtual Product Development (SVPD), and it helps in decision making by using explicit knowledge of formal decision events. It stores and reuses the past decisional events or set of experiences related to different activities involved in industrial product development process i.e. product design, manufacturing, and product inspection. This system can be potentially used in large enterprises manufacturing a range of similar products in mass production, or a group of small and medium enterprises (SMEs). This research explains that how product manufacturing can be enhanced by using SVPD in Industry 4.0, where cyber-physical systems have to play the key role. The analysis of basic concepts and implementation method proves that this is an expert system facilitating product manufacturing which can play a vital role towards Industry 4.0. [ABSTRACT FROM AUTHOR]

Knowledge and experience are important requirements for product development. The aim of this paper is to propose a systematic approach for industrial product development. This approach uses smart knowledge management system comprising of set of experience knowledge structure and decisional DNA (DDNA) along with virtual engineering tools (virtual engineering object, virtual engineering process, and virtual engineering factory). This system provides a new direction to researchers working on product development, especially designers and manufacturers. It will reduce their communication gap by allowing them to work on the same platform. The proposed system adopts an early consideration of manufacturing issues. Therefore, it can shorten product development cycle time, minimize overall development cost, and ensure a smooth transition into production. The proposed system is dynamic in nature because it updates itself after every time a new decision related to product development activity is made. Product development process can be performed systematically and efficiently using this system as it stores knowledge of experiences of different activities. [ABSTRACT FROM AUTHOR]