Carl Reidsema

Knowledge-based engineering system to estimate manufacturing cost for composite structures

Acosting application utilizing the knowledge-based-engineering environment inCATIAV5 has been developed in this research. The application can be used to estimate the cost of an assembly of composite components modeled in CATIA V5 during the initial conceptual design phase. The assembly cost is determined by extracting manufacturing process costings from a process cost analysis database. The tool uses design rules for aerospace structures to add detail to a conceptual design enabling an estimate of the cost to be determined. In addition, the tool can modify the structures to achieve the design goal of compliance with performance criteria with minimum weight. The tool is thus able to answer “what-if” questions as the design concept evolves.

A blackboard database model of the design planning process in concurrent engineering

The basis for an intelligent decision support system for design process planning within a concurrent engineering (CE) environment is the efficient utilization and coordination of planning knowledge that resides within computerized workgroups of multidisciplinary experts. A systems approach may be taken to derive, represent, and utilize the many models of reasoning that might support a human-centric view of planning in a distributed environment. The blackboard database (BB) provides a suitable framework for utilizing these models in a structured manner by representing the planning problem as a loosely coupled hierarchy of partial problems along with the knowledge needed to progressively solve different parts of this problem. This article discusses the development of such a BB system, which is intended to provide the ability to experiment with various control and domain strategies in order to yield insight into more developed and intelligent methods to assist humans in planning the CE design process.

An algorithm for defining load, paths and a load bearing topology in finite element analysis

Purpose – The purpose of this paper is to describe a post‐processing procedure for defining load paths and a load bearing topology using the stresses from a finite element analysis.Design/methodology/approach – Cauchy stress vectors and a Runge‐Kutta algorithm are used to identify the paths being followed by load components aligned with the coordinate axes. An algorithm is then defined which identifies an efficient topology that will carry the loads by straightening the paths.Findings – The aim of the algorithm is to provide insight into the way a structure is carrying loads by identifying the material most effective in performing the load transfer. The procedure is applied to a number of structures to demonstrate its applicability to structural design.Research limitations/implications – The examples demonstrate an insight of structural behavior that is useful at the conceptual stage of the design process. The load paths identify load transfer and warn the designer of the creation of bending moments and t...

Immune Decomposition and Decomposability Analysis of Complex Design Problems with a Graph Theoretic Complexity Measure

Large scale problems need to be decomposed for tractability purposes. The decomposition process needs to be carefully managed to minimize the interdependencies between sub-problems. A measure of partitioning quality is introduced and its application in problem classification is highlighted. The measure is complexity based (real complexity) and can be employed for both disjoint and overlap decompositions. The measure shows that decomposition increases the overall complexity of the problem, which can be taken as the measure’s viability indicator. The real complexity can also indicate the decomposability of the design problem, when the complexity of the whole after decomposition is less than the complexity sum of sub-problems. As such, real complexity can specify the necessary paradigm shift from decomposition based problem solving to evolutionary and holistic problem solving.

Automated Feature Recognition System for supporting conceptual engineering design

A computer based Feature-Recognition (FR) process is being developed to extract critical manufacturing features from engineering product CAD models. Feature-recognition technology is used for automating the extraction of data from CAD product models to minimise redundant user interaction with a product model. The feature-recognition process was developed using rule-based methods with wire-frame geometry extracted from an IGES neutral file format. Use of wire-frame models simplifies product geometry and has the potential to support rapid manufacturing shape evaluation at the conceptual design stage. The FR process is demonstrated using a range of typical metallic aerospace components.

IMMUNITY AS A DESIGN DECISION MAKING PARADIGM FOR COMPLEX SYSTEMS: A ROBUSTNESS APPROACH

Within complex organizational systems such as Concurrent Engineering (CE) Product Development environments, uncertainty in information, and thus the knowledge required to make effective decisions, strongly influences the quality of the final product. Such systems are marked by high degrees of data variability making techniques such as optimization less than ideal, particularly for multiobjective problem types. Although different methods that enable designers to deal with uncertainty have been utilized, they derive from what appears to be a less than adequate representation of complex system behavior. This article presents a representation for complex systems based on the analogy of immunity where the environment of a system or “nonself” represents the set of input and outputs with the “self” of the system as the resulting “effect.” A fuzzy approach to the random perturbation of the system variables through the introduction of a global robustness index is proposed. The approach is presented in the context of decision making for tolerance control within manufacturing process design.

DESIGN INFORMATION HANDLING IN A KNOWLEDGE BASED INTELLIGENT DESIGN SYSTEM

The advancements in internet technology have had a tremendous impact on the development of knowledge-based engineering systems that support concurrent engineering. Not only the conventional knowledge acquisition and representation techniques need to be improved to adapt the new situation, but the information retrieval and distribution have arisen to be new questions to answer. This article addresses these issues of management and handling of knowledge in a knowledge-based intelligent design system. A search algorithm based on the computation of a similarity index is proposed to retrieve a design case from the project library. An initial design report is used to distribute design information so that the information such as a designers intent which cannot be included in a standard CAD file, can be retained. In addition, a simple constraint definition frame is presented to define the relationships between critical design parameters, and two information representation schemas, information matrix and constraint tree, are described. The presented research efforts in this article aim to provide promising tools to harness the full potential of ontologies in knowledge management within an intelligent design system.

Review of Intelligent Software Architectures for the Development of An Intelligent Decision Support System for Design Process Planning in Concurrent Engineering

Concurrent engineering (CE) is a strategy that attempts to process as many product development tasks in parallel and incorporate relevant life-cycle attributes as early as possible in the design phase in an effort to reduce the duration of design projects, save development costs, and provide better quality products. The CE environment is characterized by a high degree of distributed cognitive processing in the form of product development team structures. The distribution of appropriate knowledge to members of these teams and other participants in the design process for the purpose of supporting management and planning decisions is a considerably complex problem. New approaches and tools based on artificial intelligence methodologies are needed to deal with this level of complexity in coordinating knowledge resources. This paper reviews a number of potential candidates for an intelligent software architecture that can represent this type of problem as well as support the knowledge handling necessary to solve such problems. The selection of an appropriate architecture will support the development of an intelligent information system that is able to mimic human cognitive processes as the basic tool for providing decision-making support for planning and controlling a CE design process.

Tools and Methods for Risk Management in Multi-Site Engineering Projects

In today’s highly global business environment, engineering and manufacturing projects often involve two or more geographically dispersed units or departments, research centers or companies. This paper attempts to identify the requirements for risk management in a multi-site engineering project environment, and presents a review of the state-of-the-art tools and methods that can be used to manage risks in multi-site engineering projects. This leads to the development of a risk management roadmap, which will underpin the design and implementation of an intelligent risk mapping system.

Reciprocal peer recommendation for learning purposes

Larger student intakes by universities and the rise of education through Massive Open Online Courses has led to less direct contact time with teaching staff for each student. One potential way of addressing this contact deficit is to invite learners to engage in peer learning and peer support; however, without technological support they may be unable to discover suitable peer connections that can enhance their learning experience. Two different research subfields with ties to recommender systems provide partial solutions to this problem. Reciprocal recommender systems provide sophisticated filtering techniques that enable users to connect with one another. To date, however, the main focus of reciprocal recommender systems has been on providing recommendation in online dating sites. Recommender systems for technology enhanced learning have employed and tailored exemplary recommenders towards use in education, with a focus on recommending learning content rather than other users. In this paper, we first discuss the importance of supporting peer learning and the role recommending reciprocal peers can play in educational settings. We then introduce our open-source course-level recommendation platform called RiPPLE that has the capacity to provide reciprocal peer recommendation. The proposed reciprocal peer recommender algorithm is evaluated against key criteria such as scalability, reciprocality, coverage, and quality and shows improvement over a baseline recommender. Primary results indicate that the system can help learners connect with peers based on their knowledge gaps and reciprocal preferences, with designed flexibility to address key limitations of existing algorithms identified in the literature.