Model-based Approach for Product Requirement Representation and Generation in Product Lifecycle Management

The requirement specification is an official documentation activity, which is a collection of certain information to specify the product and its life-cycle activities in terms of functions, features, performance, constraints, production, maintenance, disposal process, etc. It contains mainly two phases; product requirement generation and representation. Appropriate criteria for the product design and further life-cycle activities are determined based on the requirement specification as well as the interrelations of product requirements with other life-cycle information such as; materials, manufacturing, working environments, finance, and regulations. The determination of these criteria is normally error-prone. It is difficult to identify and maintain the completeness and consistency of the requirement information across the product life-cycle. Product requirements are normally expressed in abstract and conceptual terms with document base representation which yields unstructured and heterogeneous information base and it is unsuitable for intelligent machine interpretations. Most of the time determination of the requirements and development of the requirement specification documents are performed by the designers/engineers based on their own experiences that might lead to incompleteness and inconsistency. This research work proposes a unique model-based product requirement representation and generation architecture to aid designers/engineers to specify product requirements across the product life-cycle. A requirement knowledge management architecture is developed to enhance the capabilities of the current Product Life-cycle Management (PLM) platforms in terms of product requirement representation and generation. After a systematic study on the categorization of product requirements, an ontological framework is developed for the specification of the requirements and related product life-cycle domain information. The ontological framework is embedded in an existing PLM system. A computational platform is developed and integrated into the PLM system for the intelligent machine processing of the product requirements and related information. This architecture supports product requirement representation in terms of the ontological framework and further information retrieval, inference, and requirement text generation activities

Developing a QFD-Based design-integrated structural analysis methodology

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Design of the mechanical components greatly depends on their expected structural performances. In modern design applications these performances are quantified by computer-based analysis and occasionally confirmed by experimental measurements or theoretical calculations. The dependency of the mechanical product to the structural analysis process is more significant under the product’s multi-functionality aspect that requires analyses for a variety of Variable Input Parameters, to obtain various structural responses and against more than one failure or design criterion. Structural analysis is known as the expert field, which requires an upfront investment and facilitation to be implemented in commercial design environment. On the other hand, the product design process is a systematic and sequential activity that put the designer in the central role of decision making. Lack of mutual understanding between these two disciplines reduces the efficiency of the structural analysis for design. This research aims to develop an integrated methodology to embed the structural analysis in the design process. The proposed methodology in this research combines the benefits of state-of-the-art approaches, early simulation and Validation and Verification practice, towards the specified aim. Moreover the novelty of the proposed methodology is in creative implication of Quality Function Deployment method to include the product’s multi-functionality aspect. The QFD-Based Design Integrated Structural Analysis methodology produces a reliable platform to increase the efficiency of the structural analysis process for product design purpose. The application of this methodology is examined through an industrial case-study for the telescopic cantilever boom, as it appears in Access platforms, and Cranes products. Findings of the case-study create a reliable account for the structural performance in early stages of the design, and ensure the functionality of the proposed methodology.This research programme was funded by KTP organisation

Knowledge composition methodology for effective analysis problem formulation in simulation-based design

In simulation-based design, a key challenge is to formulate and solve analysis problems efficiently to evaluate a large variety of design alternatives. The solution of analysis problems has benefited from advancements in commercial off-the-shelf math solvers and computational capabilities. However, the formulation of analysis problems is often a costly and laborious process. Traditional simulation templates used for representing analysis problems are typically brittle with respect to variations in artifact topology and the idealization decisions taken by analysts. These templates often require manual updates and "re-wiring" of the analysis knowledge embodied in them. This makes the use of traditional simulation templates ineffective for multi-disciplinary design and optimization problems. Based on these issues, this dissertation defines a special class of problems known as variable topology multi-body (VTMB) problems that characterizes the types of variations seen in design-analysis interoperability. This research thus primarily answers the following question: How can we improve the effectiveness of the analysis problem formulation process for VTMB problems? The knowledge composition methodology (KCM) presented in this dissertation answers this question by addressing the following research gaps: (1) the lack of formalization of the knowledge used by analysts in formulating simulation templates, and (2) the inability to leverage this knowledge to define model composition methods for formulating simulation templates. KCM overcomes these gaps by providing: (1) formal representation of analysis knowledge as modular, reusable, analyst-intelligible building blocks, (2) graph transformation-based methods to automatically compose simulation templates from these building blocks based on analyst idealization decisions, and (3) meta-models for representing advanced simulation templates VTMB design models, analysis models, and the idealization relationships between them. Applications of the KCM to thermo-mechanical analysis of multi-stratum printed wiring boards and multi-component chip packages demonstrate its effectiveness handling VTMB and idealization variations with significantly enhanced formulation efficiency (from several hours in existing methods to few minutes). In addition to enhancing the effectiveness of analysis problem formulation, KCM is envisioned to provide a foundational approach to model formulation for generalized variable topology problems.Ph.D.Committee Co-Chair: Dr. Christiaan J. J. Paredis; Committee Co-Chair: Dr. Russell S. Peak; Committee Member: Dr. Charles Eastman; Committee Member: Dr. David McDowell; Committee Member: Dr. David Rosen; Committee Member: Dr. Steven J. Fenve