The reuse of machining knowledge to improve designer awareness through the configuration of knowledge libraries in PLM

The nature of competition induces the need to constantly improve and perform better. For global aerospace manufacturers, this is as timely an epithet as ever as market forces urge for more growth, better financial return and market position. The macroeconomic aspect is compounded by the growth of product complexity and the need for higher product quality, hence the drive to reduce waste places emphasis upon production costs and the need to improve product performance. This paper focuses upon a rapid development and deployment method that enables the capture and representation of machining knowledge so that it may be shared and reused by design engineers to accelerate the design-make process. The study and mapping of information and knowledge relationships are described and put forward as a lightweight ontology. From this, a set of knowledge document templates were created to facilitate the capture, structuring and sharing of machining knowledge within a collaborative multidisciplinary aerospace engineering environment. An experimental pilot system has been developed to test and demonstrate that knowledge document templates can accelerate the sharing of machining knowledge within an industrial product lifecycle management environment. The results are discussed to provide a case for further development and application within the product domain

A social media framework to support engineering design communication

AbstractEngineering Design Communication (EDC) is fundamental to almost all Engineering Design activities as it provides the ability for knowledge and information to be shared between engineers. It is part of ‘what we do’. This communication contains a great deal of rationale relating to the evolution of Product Development and is essential for understanding ‘why the product is the way it is’. The need to support EDC is becoming more important due to the fact that Product Development is becoming more distributed, multi-disciplinary and involving greater re-use of past designs. With the advent of Social Media (SM), it is argued that there is the technical capability to provide more effective support for EDC within a computer-mediated environment. In order to explore this potential, this paper defines the requirements for the effective support of EDC through an extensive review of the literature. It then discusses the suitability of a SM approach and then presents the theoretical foundations of a SM framework to support EDC

A framework for design rationale capture and use during geometry design

Despite broad agreement on the utility of design rationale use and capture, a review of the relevant literature shows that industrial usage remains limited, especially during geometry design.An initial field study confirmed low design rationale capture during the geometry design stage. The lack of linking between design rationale and geometry models is identified as a factor holding back design rationale capture.A toolset is presented to link entities in geometry models to design rationale, allowing the creation of design rationale referring to a specific geometry design decision. Using the design rationale links it is possible to create graphs of the structure of geometry models and attached rationale. Furthermore the presence and quantity of design rationale can be displayed as a coloured overlay on the geometry.The toolset has been tested by 7 groups of student-designers, and although the uptake of the design rationale linking tool by the users was low, results show that groups using the tool captured relatively more design rationale during geometry design, although reservations have to be made regarding to self-selection bias. The study shows that the availability of design rationale linking tools is not by itself enough to improve design rationale capture during geometry design

Approach to identify product and process state drivers in manufacturing systems using supervised machine learning

The developed concept allows identifying relevant state drivers of complex, multi-stage manufacturing systems holistically. It is able to utilize complex, diverse and high-dimensional data sets which often occur in manufacturing applications and integrate the important process intra- and inter-relations. The evaluation was conducted by using three different scenarios from distinctive manufacturing domains (aviation, chemical and semiconductor). The evaluation confirmed that it is possible to incorporate implicit process intra- and inter-relations on process as well as programme level through applying SVM based feature ranking. The analysis outcome presents a direct benefit for practitioners in form of the most important process parameters and state characteristics, so-called state drivers, of a manufacturing system. Given the increasing availability of data and information, this selection support can be directly utilized in, e.g., quality monitoring and advanced process control

Knowledge management solutions and selection tool for engineering organisations

It is widely accepted that engineering research, design, development and manufacturing processes are highly reliant upon the valuable knowledge, experiences and skills stored within the company's systems, processes, documents and employees. If these key knowledge resources can be identified, maintained and efficiently controlled, prior successes and failures can be capitalised upon, best practices can be captured and transferred and new solutions can be developed with minimal duplication of efforts and without unnecessary replication of prior work. Away from manufacturing and engineering organisations, in the broader business world, exists an array of solutions, tools and techniques developed specifically to facilitate the management of knowledge and experience these are collectively labelled as Knowledge Management (KM) tools and solutions. Such solutions, tools and techniques have achieved widespread recognition for their capabilities and consequent importance in enhancing processes across a variety of business applications and contexts. However their relevancy, applicability and relative merits in particular manufacturing and mechanical engineering (MME) contexts have generally not been identified or investigated. This thesis reviews and presents a large number of diverse KM solutions and implementations across industries and organisations and creates a new and unique single KM solutions space in which these solutions are characterised. The KM solution space is subsequently utilised by a new KM methodology and support tool that facilitates and demonstrates the enhancement of mechanical and manufacturing engineering processes through analysis followed by selection and implementation of the most appropriate existing KM solutions. The KM Tool is demonstrated via three industrial case studies detailing the process concerns and associated improvements identified and implemented. The KM Solution Space developed during this research has shown that there is significant opportunity to improve mechanical and manufacturing engineering processes through the adoption of appropriate KM solutions from the broader business world. The KM Tool developed via this research facilitates this identification and adoption of the most appropriate KM solution. In addition to the MME processes covered by the scope of this research there is additional scope to extend the use of the KM Tool and KM Solution Space to other business areas that have not yet had extensive exposure to KM