Constraint capture and maintenance in engineering design

The Designers' Workbench is a system, developed by the Advanced Knowledge Technologies (AKT) consortium to support designers in large organizations, such as Rolls-Royce, to ensure that the design is consistent with the specification for the particular design as well as with the company's design rule book(s). In the principal application discussed here, the evolving design is described against a jet engine ontology. Design rules are expressed as constraints over the domain ontology. Currently, to capture the constraint information, a domain expert (design engineer) has to work with a knowledge engineer to identify the constraints, and it is then the task of the knowledge engineer to encode these into the Workbench's knowledge base (KB). This is an error prone and time consuming task. It is highly desirable to relieve the knowledge engineer of this task, and so we have developed a system, ConEditor+ that enables domain experts themselves to capture and maintain these constraints. Further we hypothesize that in order to appropriately apply, maintain and reuse constraints, it is necessary to understand the underlying assumptions and context in which each constraint is applicable. We refer to them as “application conditions” and these form a part of the rationale associated with the constraint. We propose a methodology to capture the application conditions associated with a constraint and demonstrate that an explicit representation (machine interpretable format) of application conditions (rationales) together with the corresponding constraints and the domain ontology can be used by a machine to support maintenance of constraints. Support for the maintenance of constraints includes detecting inconsistencies, subsumption, redundancy, fusion between constraints and suggesting appropriate refinements. The proposed methodology provides immediate benefits to the designers and hence should encourage them to input the application conditions (rationales)

Pattern languages in HCI: A critical review

This article presents a critical review of patterns and pattern languages in human-computer interaction (HCI). In recent years, patterns and pattern languages have received considerable attention in HCI for their potential as a means for developing and communicating information and knowledge to support good design. This review examines the background to patterns and pattern languages in HCI, and seeks to locate pattern languages in relation to other approaches to interaction design. The review explores four key issues: What is a pattern? What is a pattern language? How are patterns and pattern languages used? and How are values reflected in the pattern-based approach to design? Following on from the review, a future research agenda is proposed for patterns and pattern languages in HCI

Coordination approaches and systems - part I : a strategic perspective

This is the first part of a two-part paper presenting a fundamental review and summary of research of design coordination and cooperation technologies. The theme of this review is aimed at the research conducted within the decision management aspect of design coordination. The focus is therefore on the strategies involved in making decisions and how these strategies are used to satisfy design requirements. The paper reviews research within collaborative and coordinated design, project and workflow management, and, task and organization models. The research reviewed has attempted to identify fundamental coordination mechanisms from different domains, however it is concluded that domain independent mechanisms need to be augmented with domain specific mechanisms to facilitate coordination. Part II is a review of design coordination from an operational perspective

ConEditor+: Capture and Maintenance of Constraints in Engineering Design

The Designers' Workbench is a system, developed to support designers in large organizations, such as Rolls-Royce, by making sure that the design is consistent with the specification for the particular design as well as with the company’s design rule book(s). Currently, to capture the constraint information, a domain expert (design engineer) has to work with a knowledge engineer to identify the constraints, and it is then the task of the knowledge engineer to encode these into the Workbench's knowledge base (KB). This is an error prone and time consuming task. It is highly desirable to relieve the knowledge engineer of this task, and so we have developed a tool, ConEditor+ that enables domain experts themselves to capture and maintain these constraints. The tool allows the user to combine selected entities from the domain ontology with keywords and operators of a constraint language to form a constraint expression. Further, we hypothesize that to apply constraints appropriately, it is necessary to understand the context in which each constraint is applicable. We refer to this as "application conditions". We show that an explicit representation of application conditions, in a machine interpretable format, along with the constraints and the domain ontology can be used to support the verification and maintenance of constraints

A design recording framework to facilitate knowledge sharing in collaborative software engineering

This paper describes an environment that allows a development team to share knowledge about software artefacts by recording decisions and rationales as well as supporting the team in formulating and maintaining design constraints. It explores the use of multi-dimensional design spaces for capturing various issues arising during development and presenting this meta-information using a network of views. It describes a framework to underlie the collaborative environment and shows the supporting architecture and its implementation. It addresses how the artefacts and their meta-information are captured in a non-invasive way and shows how an artefact repository is embedded to store and manage the artefacts

The 'what' and 'how' of learning in design, invited paper

Previous experiences hold a wealth of knowledge which we often take for granted and use unknowingly through our every day working lives. In design, those experiences can play a crucial role in the success or failure of a design project, having a great deal of influence on the quality, cost and development time of a product. But how can we empower computer based design systems to acquire this knowledge? How would we use such systems to support design? This paper outlines some of the work which has been carried out in applying and developing Machine Learning techniques to support the design activity; particularly in utilising previous designs and learning the design process

The role of ontologies in creating and maintaining corporate knowledge: a case study from the aero industry

The Designers’ Workbench is a system, developed to support designers in large organizations, such as Rolls-Royce, by making sure that the design is consistent with the specification for the particular design as well as with the company’s design rule book(s). The evolving design is described against a jet engine ontology. Currently, to capture the constraint information, a domain expert (design engineer) has to work with a knowledge engineer to identify the constraints, and it is then the task of the knowledge engineer to encode these into the Workbench’s knowledge base (KB). This is an error prone and time consuming task. It is highly desirable to relieve the knowledge engineer of this task, and so we have developed a tool, ConEditor+ that enables domain experts themselves to capture and maintain these constraints. The tool allows the user to combine selected entities from the domain ontology with keywords and operators of a constraint language to form a constraint expression. Further, we hypothesize that to apply constraints appropriately, it is necessary to understand the context in which each constraint is applicable. We refer to this as “application conditions”. We show that an explicit representation of application conditions, in a machine interpretable format, along with the constraints and the domain ontology can be used to support the verification and maintenance of constraints

Arguing security: validating security requirements using structured argumentation

This paper proposes using both formal and structured informal arguments to show that an eventual realized system can satisfy its security requirements. These arguments, called 'satisfaction arguments', consist of two parts: a formal argument based upon claims about domain properties, and a set of informal arguments that justify the claims. Building on our earlier work on trust assumptions and security requirements, we show how using satisfaction arguments assists in clarifying how a system satisfies its security requirements, in the process identifying those properties of domains that are critical to the requirements

Arguing satisfaction of security requirements

This chapter presents a process for security requirements elicitation and analysis, based around the construction of a satisfaction argument for the security of a system. The process starts with the enumeration of security goals based on assets in the system, then uses these goals to derive security requirements in the form of constraints. Next, a satisfaction argument for the system is constructed, using a problem-centered representation, a formal proof to analyze properties that can be demonstrated, and structured informal argumentation of the assumptions exposed during construction of the argument. Constructing the satisfaction argument can expose missing and inconsistent assumptions about system context and behavior that effect security, and a completed argument provides assurances that a system can respect its security requirements