A decision support framework for concurrent multi-DFX implementation to optimize the machine design process

  • Author / Creator
    Itani, Anas
  • Industry 4.0 has sparked rapid changes in the manufacturing and construction sectors, leading to a major shift in how prefab construction machines are designed and manufactured in a concurrent engineering environment. Design for X (DFX) is one of the most effective methods for implementing in concurrent engineering as a methodical and proactive approach to machine design that maximizes total benefits over the entire product lifecycle. However, this task is challenging and time-consuming considering the vast number of feasible permutations involved. The unresolved challenge is how the information contained within Multi-DFX (MDFX) can be organized such that the implications of decisions are proactively evaluated and implemented. For this purpose, designers require robust decision-making tools for supporting MDFX techniques in machine design. Because if applied, they can generate a propagation effect that spans multiple life phases. Also, the necessity is growing for a design decision support system to guide designers and alert them to what possible consequences they could encounter in the downstream life-cycle phases if MDFX is applied. Therefore, to overcome these challenging tasks, designers have recently started to utilize innovative searching and optimizing methods that can aid them in the MDFX trade-off analysis and in finding the optimal utilization plan for design development. To cope with this, a functional collaborative DFX scheme mitigated with Stuart Pugh: Total Design Activity Model is developed in this research where various DFX techniques are grouped and allocated to different phases of the machine development lifecycle. Furthermore, the research progressed to analyze the conflict arising from the application of MDFX in a machine design problem and automatically resolve the conflict of design experts’ opinion by simulating the MDFX interactions and design decision criteria multi-layers in the developed aggregated matrix model. However, for any machine design development project, there are specific product design specifications that a designer must attend to during the design and aim to satisfy the client needs in the final machine. Therefore, to balance the allocation and control the integration of MDFX techniques in each design criterion, this research proposed a hybrid multi-objective optimization model based on the fuzzy set theory. This model was integrated with an intelligently automated searching model that focuses on finding the optimal MDFX utilization solutions. These solutions minimize the machine design development cost and time while maximizes its quality. Also, this model can analyze these results from a financial perspective by aggregating the performance metrics and by accounting for machine design specific constraints. The proposed research materials are applied in various machine design real-world case studies to validate their feasibility, applicability, and effectiveness in a dynamic machine development environment and in visualizing the optimal trade-offs among MDFX metrics while coupling their engineering-financial terms for a better decision-making process within the domain of machine design for prefabricated construction.

  • Subjects / Keywords
  • Graduation date
    Spring 2019
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • License
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