Browsing by Author "Maksimovic, Maksim"

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    A3 thinking approach to support knowledge-driven design
    (Springer, 2013-03-01) Mohd Saad, Norhairin; Al-Ashaab, Ahmed; Maksimovic, Maksim; Zhu, L.; Shehab, Essam; Ewers, P.; Kassam, A.
    Problem solving is a crucial skill in product development. Any lack of effective decision making at an early design stage will affect productivity and increase costs and the lead time for the other stages of the product development life cycle. This could be improved by the use of a simple and informative approach which allows the designers and engineers to make decisions in product design by providing useful knowledge. This paper presents a novel A3 thinking approach to problem solving in product design, and provides a new A3 template which is structured from a combination of customised elements (e.g. the 8 Disciplines approach) and reflection practice. This approach was validated using a case study in the Electromagnetic Compatibility (EMC) design issue for an automotive electrical sub-assembly product. The main advantage of the developed approach is to create and capture the useful knowledge in a simple manner. Moreover, the approach provides a reflection section allowing the designers to turn their experience of design problem solving into proper learning and to represent their understanding of the design solution. These will be systematically structured (e.g. as a design checklist) to be circulated and shared as a reference for future design projects. Thus, the recurrence of similar design problems will be prevented and will aid the designers in adopting the expected EMC test results.
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    Knowledge creation and visualisation by using trade-off curves to enable set-based concurrent engineering
    (Academic Conferences International Ltd, 2016-04-01) Araci, Zehra Canan; Al-Ashaab, Ahmed; Maksimovic, Maksim
    The increased international competition forces companies to sustain and improve market share through the production of a high quality product in a cost effective manner and in a shorter time. Set‑based concurrent engineering (SBCE), which is a core element of lean product development approach, has got the potential to decrease time‑to‑market as well as enhance product innovation to be produced in good quality and cost effective manner. A knowledge‑based environment is one of the important requ irements for a successful SBCE implementation. One way to provide this environment is the use of trade‑off curves (ToC). ToC is a tool to create and visualise knowledge in the way to understand the relationships between various conflicting design parame ters to each other. This paper presents an overview of different types of ToCs and the role of knowledge‑based ToCs in SBCE by employing an extensive literature review and industrial field study. It then proposes a process of generating and using knowledg e‑based ToCs in order to create and visualise knowledge to enable the following key SBCE activities: (1) Identify the feasible design space, (2) Generate set of conceptual design solutions, (3) Compare design solutions, (4) Narrow down the design sets, (5) Achieve final optimal design solution. Finally a hypothetical example of a car seat structure is presented in order to provide a better understanding of using ToCs. This example shows that ToCs are effective tools to be used as a knowledge sou rce at the early stages of product development process.
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    Lean knowledge life cycle framework to support lean product development
    (Cranfield University, 2013-07) Maksimovic, Maksim; Shehab, Essam; Al-Ashaab, Ahmed
    This research thesis presents the development of a novel Lean Knowledge Life Cycle (LeanKLC) framework to support the transformation into a Lean Product Development (LeanPD) knowledge environment. The LeanKLC framework introduces a baseline model to understand the three dimensions of knowledge management in product development as well as its contextualisation with acclaimed LeanPD process models. The LeanKLC framework comprises 23 tasks, each accomplished in one of the seven key stages, these being: knowledge identification, previous knowledge capture, knowledge representation, knowledge sharing, knowledge integration, knowledge use and provision and dynamic knowledge capture. The rigorous research methodology employed to develop the LeanKLC framework entailed extensive data collection starting with a literature review to highlight the gap in the current body of knowledge. Additionally, industrial field research provides empirical evidence on the current industrial perspectives and challenges in managing product development knowledge. This research was part of a European FP7 project entitled Lean Product and Process Development (LeanPPD), which provided the opportunity to involve industrial collaborators in action research to support practical aspects during the LeanKLC framework development. The synthesis with the current LeanPD paradigm is accomplished by demonstrating the LeanKLC stages in two distinct streams related to the development of A3 thinking for problem solving and the development of trade-off curves to facilitate set based design at the conceptual stage. The novel LeanKLC is validated in two case studies providing the industry with detailed insights on real product development applications. In particular this research highlights that the LeanPD knowledge environment is a wide subject area that has not yet been thoroughly understood and that industry engagement in empirical research is vital in order to realise any form of LeanPD transformation.
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    Towards a Semantic Knowledge Life Cycle Approach for Aerospace Design Engineering
    (2011-07-09T00:00:00Z) Sanya, Isaac; Shehab, Essam; Lowe, Dave; Al-Ashaab, Ahmed; Maksimovic, Maksim; Frey, Daniel D.; Fukuda, Shuichi; Rock, Georg (Eds.)
    The efficient and effective management of knowledge is becoming increasingly important within the aerospace design engineering sector due to the complexity of product development. Semantic technology is becoming mainstream technology and is being applied by many disciplines for the management of complex knowledge. However, there is a lack of a semantic knowledge life cycle to support the semantic knowledge management discipline. This paper presents a systematic knowledge life cycle (KLC) for supporting the semantic knowledge management discipline with a particular emphasis on the importance of structuring knowledge. The semantic KLC comprises eight stages namely: (1) Understand the domain (2) Structure (3) Enrich vocabulary (4) Capture (5) Represent (6) Interpret the „know how‟ (7) Share (8) KBE system. This research project adopts a qualitative approach and a five-phased research methodology. An illustrative scenario within the aerospace engineering industry for producing gas turbine systems is used to demonstrate the practicality and applicability of the proposed approach. The semantic KLC supports a shared agreement of meaning and understanding between design and manufacturing engine