DecMS : an approach to providing decision support within NEC delivery

Decision-making across the military capability lifecycle phases can vary considerably in terms of the types of decisions made and the manner in which they are made. Although decision-making has received considerable attention within the research community, much work has concentrated on providing decision support for particular styles of decision-making. However, within capability delivery there is a need to develop approaches that can both map styles of decision-making to particular decision problems, and provide decision support at an executable level of detail. This paper presents the Decision Management and Support (DecMS) approach to providing decision support during capability delivery. The approach is based upon refining a fundamental model of decision-making to an executable level of detail. Refinement is controlled using analogical reasoning to ensure that the model is refined in accordance with the needs of the decision problem at hand. Future work will involve testing the effectiveness of the approach

CAFixD: A Case-based Reasoning Method for Fixture Design

Fixtures accurately locate and secure a part during machining operations such that the part can be manufactured to design specifications. To reduce the design costs associated with fixturing, various computer-aided fixture design (CAFD) methods have been developed through the years to assist the fixture designer. Much research has been directed towards developing systems that determine an optimal fixture plan layout, but there is still a need to develop a CAFD method that can continue to assist designers at the unit level where the key task is identifying the appropriate structure that the individual units comprising a fixture should take. This research work details the development of a CAFD methodology (called CAFixD) that seeks to fill this hole in the CAFD field. The approach taken is to consider all operational requirements of a fixture problem, and use them to guide the design of a fixture at the unit level. Based upon a case-based reasoning (CBR) methodology where relevant design experience is retrieved and adapted to provide a new fixture design solution, the CAFixD methodology adopts a rigorous approach to indexing design cases in which axiomatic design functional requirement decomposition is adopted. Thus, the design requirement is decomposed in terms of functional requirements, physical solutions are retrieved and adapted for each individual requirement, and the design re-constituted to form a complete fixture design. Case adaptation knowledge is used to guide the retrieval process. Possible adaptation strategies for modifying candidate cases are identified and then evaluated. Case and adaptation strategy combinations that result in adapted designs that best satisfy the preferences of the designer are used as the final design solutions. Possible means of refining the effectiveness of the method include combining adaptation strategies and considering the order in which design decisions are taken

A design view of capability

In order to optimise resource deployment in a rapid changing operational environment, capability has received increasing concerns in terms of maximising the utilisation of resources. As a result of such extant research, different domains were seen to endow different meanings to capability, indicating a lack of common understanding of the true nature of capability. This paper presents a design view of capability from design artefact knowledge perspective. Capability is defined as an intrinsic quality of an entity closely related to artefact behavioural and structural knowledge. Design artefact knowledge was categorised across expected, instantiated, and interpreted artefact knowledge spaces (ES, IsS, and ItS). Accordingly, it suggests that three types of capability exist in the three spaces, which can be used in employing resources. Moreover, Network Enabled Capability (NEC), the capability of a set of linked resources within a specific environment is discussed, with an example of how network resources are deployed in a Virtual Integration Platform (VIP)

An integrated decision support environment for organisational decision making

Traditional decision support systems are based on the paradigm of a single decision maker working at a stand-alone computer or terminal who has a specific decision to make with a specific goal in mind. Organisational decision support systems aim to support decision makers at all levels of an organisation (from executive, middle management managers to operators), who have a variety of decisions to make, with different priorities, often in a distributed environment. Such systems are designed and developed with extra functionality to meet the challenge. This paper proposes an Integrated Decision Support Environment (IDSE) for organisational decision making. The IDSE is designed and developed based on distributed client/server networking, with a combination of tight and loose integration approaches for information exchange and communication. The prototype of the IDSE demonstrates a good balance between flexibility and reliability

Knowledge re-use for decision support

Effective decision support has already been identified as a fundamental requirement for the realisation of Network Enabled Capability. Decision making itself is a knowledge-intensive process, and it is known that right decisions can only be reached based on decision maker's good judgement, which in turn is based on sufficient knowledge. It is not unusual for decision makers to make incorrect decisions because of insufficient knowledge. However, it is not always possible for decision makers to have all the knowledge needed for making decisions in complex situations without external support. The re-use of knowledge has been identified as providing an important contribution to such support, and this paper considers one, hitherto unexplored, aspect of how this may be achieved. This paper is concerned with the computational view of knowledge re-use to establish an understanding of a knowledge-based system for decision support. The paper explores knowledge re-use for decision support from two perspectives: knowledge provider's and knowledge re-user's. Key issues and challenges of knowledge re-use are identified from both perspectives. A structural model for knowledge re-use is proposed with initial evaluation through empirical study of both experienced and novice decision maker's behaviour in reusing knowledge to make decisions. The proposed structural model for knowledge re-use captures five main elements (knowledge re-uers, knowledge types, knowledge sources, environment, and integration strategies) as well as the relationships between the elements, which forms a foundation for constructing a knowledge-based decision support system. The paper suggests that further research should be investigating the relationship between knowledge re-use and learning to achieve intelligent decision support

Towards an understanding of the impact of resources on the design process

Considerable effort has been devoted within the design research community to understanding the structure of design processes and their development for different design problems. Whilst much work has examined the impact of design goals upon the structure of a design process, less attention has been paid to the role that design resources can play. This paper describes an experiment directed towards gaining an understanding of the impact that both active resources (which perform design tasks) and passive resources (which are used by active resources) can have upon design process structure. Main outcomes from the experiment were the conclusive identification that resources can significantly impact design process structure and a number of examples of how these impacts manifest themselves. The main conclusion of the paper is that given the sizeable impact resources can have upon process structure, there is a considerable need to obtain a greater understanding of these impacts to facilitate the development of techniques that can support design process definition based upon an understanding of the design resources being used to solve a design problem

Decision-focussed resource modelling for design decision support

Resource management including resource allocation, levelling, configuration and monitoring has been recognised as critical to design decision making. It has received increasing research interests in recent years. Different definitions, models and systems have been developed and published in literature. One common issue with existing research is that the resource modelling has focussed on the information view of resources. A few acknowledged the importance of resource capability to design management, but none has addressed the evaluation analysis of resource fitness to effectively support design decisions. This paper proposes a decision-focused resource model framework that addresses the combination of resource evaluation with resource information from multiple perspectives. A resource management system constructed on the resource model framework can provide functions for design engineers to efficiently search and retrieve the best fit resources (based on the evaluation results) to meet decision requirements. Thus, the system has the potential to provide improved decision making performance compared with existing resource management systems

Creation dependencies of evolutionary artefact and design process knowledge

As design progresses, artefact and process knowledge often evolve together. However, there is very limited knowledge on the true nature of the dependencies between these two elements of knowledge. This paper presents the first attempt to clearly define 'creation' dependencies, which cause a change in design knowledge. Three data analyses were used to identify the dependencies: two were in-depth protocol analyses of a single student product design project and a senior ship designer’s daily work, and a third was a quantitative questionnaire analysis involving seven experienced complex system designers from industry. The analyses revealed a set of 52 previously unknown creation dependencies between artefact and design process knowledge with commonality found in only 5, with additional dependencies being identified that were specific to the design being studied. Different frequencies of dependency occurrence and particular dependency loops were identified. In addition, the importance and role of domain knowledge were explicitly revealed. The described research highlights the need for further work to provide a more comprehensive definition of the nature of evolutionary artefact and design process knowledge dependencies. Identification of these dependencies offers a significant opportunity to develop tools and techniques with an enhanced ability to support 'what–if' analyses during design

The impact of resources on decision making

Decision making is a significant activity within industry and although much attention has been paid to the manner in which goals impact on how decision making is executed, there has been less focus on the impact decision making resources can have. This article describes an experiment that sought to provide greater insight into the impact that resources can have on how decision making is executed. Investigated variables included the experience levels of decision makers and the quality and availability of information resources. The experiment provided insights into the variety of impacts that resources can have upon decision making, manifested through the evolution of the approaches, methods, and processes used within it. The findings illustrated that there could be an impact on the decision-making process but not on the method or approach, the method and process but not the approach, or the approach, method, and process. In addition, resources were observed to have multiple impacts, which can emerge in different timescales. Given these findings, research is suggested into the development of resource-impact models that would describe the relationships existing between the decision-making activity and resources, together with the development of techniques for reasoning using these models. This would enhance the development of systems that could offer improved levels of decision support through managing the impact of resources on decision making