CBE-conveyor: a case-based reasoning system to assist engineers in designing conveyor systems

In this paper, we address the use of CBR in collaboration with numerical engineering models. This collaborative combination has a particular application in engineering domains where numerical models are used. We term this domain “Case Based Engineering” (CBE), and present the general architecture of a CBE system. We define and discuss the general characteristics of CBE and the special problems which arise. These are: the handling of engineering constraints of both continuous and nominal kind; interpolation over both continuous and nominal variables, and conformability for interpolation. In order to illustrate the utility of the method proposed, and to provide practical examples of the general theory, the paper describes a practical application of the CBE architecture, known as CBE-CONVEYOR, which has been implemented by the authors.Pneumatic conveying is an important transportation technology in the solid bulks conveying industry. One of the major industry concerns is the attrition of powders and granules during pneumatic conveying. To minimize the fraction of particles during pneumatic conveying, engineers want to know what design parameters they should use in building a conveyor system. To do this, engineers often run simulations in a repetitive manner to find appropriate input parameters. CBE-Conveyor is shown to speed up conventional methods for searching for solutions, and to solve problems directly that would otherwise require considerable intervention from the engineer.

A life cycle model for product-service systems design

Western manufacturing companies are developing innovative ways of delivering value that competes with the low cost paradigm. One such strategy is to deliver not only products, but systems that are closely aligned with the customer value proposition. These systems are comprised of integrated products and services, and are referred to as Product-Service Systems (PSS). A key challenge in PSS is supporting the design activity. In one sense, PSS design is a further extension of concurrent engineering that requires front-end input from the additional downstream sources of product service and maintenance. However, simply developing products and service packages is not sufficient: the new design challenge is the integrated system. This paper describes the development of a PSS data structure that can support this integrated design activity. The data structure is implemented in a knowledge base using the Protégé knowledge base editor.

Manufacturing knowledge verification in design support systems

This paper identifies the need for a verification methodology for manufacturing knowledge in design support systems; and proposes a suitable methodology based on the concept of ontological commitment and the PSL ontology (ISO/CD18629). The use of the verification procedures within an overall system development methodology is examined, and an understanding of how various categories of manufacturing knowledge (typical to design support systems) map onto the PSL ontology is developed. This work is also supported by case study material from industrial situations, including the casting and machining of metallic components. The PSL ontology was found to support the verification of most categories of manufacturing knowledge, and was shown to be particularly suited to process planning representations. Additional concepts and verification procedures were however needed to verify relationships between products and manufacturing processes. Suitable representational concepts and verification procedures were therefore developed, and integrated into the proposed knowledge verification methodology.

Investigation into a modular rule-based testing method for testing business rules in scheduling applications

Rule testing in transport scheduling is a complex and potentially costly business problem. This paper proposes an automated method for the rule-based testing of business rules using the extensible Markup Language for rule representation and transportation. A compiled approach to rule execution is also proposed for performance-critical scheduling systems.

The contribution of qualitative research in designing a complex intervention for secondary prevention of coronary heart disease in two different healthcare systems

Background: Developing complex interventions for testing in randomised controlled trials is of increasing importance in healthcare planning. There is a need for careful design of interventions for secondary prevention of coronary heart disease (CHD). It has been suggested that integrating qualitative research in the development of a complex intervention may contribute to optimising its design but there is limited evidence of this in practice. This study aims to examine the contribution of qualitative research in developing a complex intervention to improve the provision and uptake of secondary prevention of CHD within primary care in two different healthcare systems.

Methods: In four general practices, one rural and one urban, in Northern Ireland and the Republic of Ireland, patients with CHD were purposively selected. Four focus groups with patients (N = 23) and four with staff (N = 29) informed the development of the intervention by exploring how it could be tailored and integrated with current secondary prevention activities for CHD in the two healthcare settings. Following an exploratory trial the acceptability and feasibility of the intervention were discussed in four focus groups (17 patients) and 10 interviews (staff). The data were analysed using thematic analysis.

Results: Integrating qualitative research into the development of the intervention provided depth of information about the varying impact, between the two healthcare systems, of different funding and administrative arrangements, on their provision of secondary prevention and identified similar barriers of time constraints, training needs and poor patient motivation. The findings also highlighted the importance to patients of stress management, the need for which had been underestimated by the researchers. The qualitative evaluation provided depth of detail not found in evaluation questionnaires. It highlighted how the intervention needed to be more practical by minimising administration, integrating role plays into behaviour change training, providing more practical information about stress management and removing self-monitoring of lifestyle change.

Conclusion: Qualitative research is integral to developing the design detail of a complex intervention and tailoring its components to address individuals' needs in different healthcare systems. The findings highlight how qualitative research may be a valuable component of the preparation for complex interventions and their evaluation.

Aircraft Cost Modelling using the Genetic Causal Technique within a Systems Engineering Approach

The paper is primarily concerned with the modelling of aircraft manufacturing cost. The aim is to establish an integrated life cycle balanced design process through a systems engineering approach to interdisciplinary analysis and control. The cost modelling is achieved using the genetic causal approach that enforces product family categorisation and the subsequent generation of causal relationships between deterministic cost components and their design source. This utilises causal parametric cost drivers and the definition of the physical architecture from the Work Breakdown Structure (WBS) to identify product families. The paper presents applications to the overall aircraft design with a particular focus on the fuselage as a subsystem of the aircraft, including fuselage panels and localised detail, as well as engine nacelles. The higher level application to aircraft requirements and functional analysis is investigated and verified relative to life cycle design issues for the relationship between acquisition cost and Direct Operational Cost (DOC), for a range of both metal and composite subsystems. Maintenance is considered in some detail as an important contributor to DOC and life cycle cost. The lower level application to aircraft physical architecture is investigated and verified for the WBS of an engine nacelle, including a sequential build stage investigation of the materials, fabrication and assembly costs. The studies are then extended by investigating the acquisition cost of aircraft fuselages, including the recurring unit cost and the non-recurring design cost of the airframe sub-system. The systems costing methodology is facilitated by the genetic causal cost modeling technique as the latter is highly generic, interdisciplinary, flexible, multilevel and recursive in nature, and can be applied at the various analysis levels required of systems engineering. Therefore, the main contribution of paper is a methodology for applying systems engineering costing, supported by the genetic causal cost modeling approach, whether at a requirements, functional or physical level.

Fault reconstruction in linear dynamic systems using multivariate statistics

Treasure et al. (2004) recently proposed a new sub space-monitoring technique, based on the N4SID algorithm, within the multivariate statistical process control framework. This dynamic-monitoring method requires considerably fewer variables to be analysed when compared with dynamic principal component analysis (PCA). The contribution charts and variable reconstruction, traditionally employed for static PCA, are analysed in a dynamic context. The contribution charts and variable reconstruction may be affected by the ratio of the number of retained components to the total number of analysed variables. Particular problems arise if this ratio is large and a new reconstruction chart is introduced to overcome these. The utility of such a dynamic contribution chart and variable reconstruction is shown in a simulation and by application to industrial data from a distillation unit.

Learning soft computing control strategies in a modular neural network architecture

Modelling and control of nonlinear dynamical systems is a challenging problem since the dynamics of such systems change over their parameter space. Conventional methodologies for designing nonlinear control laws, such as gain scheduling, are effective because the designer partitions the overall complex control into a number of simpler sub-tasks. This paper describes a new genetic algorithm based method for the design of a modular neural network (MNN) control architecture that learns such partitions of an overall complex control task. Here a chromosome represents both the structure and parameters of an individual neural network in the MNN controller and a hierarchical fuzzy approach is used to select the chromosomes required to accomplish a given control task. This new strategy is applied to the end-point tracking of a single-link flexible manipulator modelled from experimental data. Results show that the MNN controller is simple to design and produces superior performance compared to a single neural network (SNN) controller which is theoretically capable of achieving the desired trajectory. (C) 2003 Elsevier Ltd. All rights reserved.

Electrochemical ammonia gas sensing in nonaqueous systems: A comparison of propylene carbonate with room temperature ffonc liquids

First, the direct and indirect electrochemical oxidation of ammonia has been studied by cyclic voltammetry at glassy carbon electrodes in propylene carbonate. In the case of the indirect oxidation of ammonia, its analytical utility of indirect for ammonia sensing was examined in the range from 10 and 100 ppm by measuring the peak current of new wave resulting from reaction between ammonia and hydroquinone, as function of ammonia concentration, giving a sensitivity 1.29 x 10(-7) A ppm(-1) (r(2)=0.999) and limit-of-detection 5 ppm ammonia. Further, the direct oxidation of ammonia has been investigated in several room temperature ionic liquids (RTILs), namely 1-butyl-3-methylimidazolium tetrafluoroborate ([C(4)mim] [BF4]), 1-butyl-3-methylimiclazolium trifluoromethylsulfonate ([C4mim] [OTf]), 1-Ethyl -3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([C(2)mim] [NTf2]), 1-butyl-3-methylimidazolium bis(tritluoromethylsulfonyl)imide ([C4mim] [NTf2]) and 1-butyl-3-methylimidazolium hexafluorophosphate ([C4mim] [PF6]) on a 10 put diameter Pt microdisk electrode. In four of the RTILs studied, the cyclic voltammetric analysis suggests that ammonia is initially oxidized to nitrogen, N-2, and protons, which are transferred to an ammonia molecule, forming NH4+ via the protonation of the anion(s) (A(-)). However, in [C4mim] [PF6], the protonated anion was formed first, followed by NH4+. In all five RTILs, both HA and NH4+ are reduced at the electrode surface, forming hydrogen gas, which is then oxidized. The analytical ability of this work has also been explored further, giving a limit-of-detection close to 50 ppm in [C(2)mim] [NTf2], [C(4)mim] [OTf], [C(4)mim] [BF4], with a sensitivity of ca. 6 x 10(-7) A ppm(-1) (r(2) = 0.999) for all three ionic liquids, showing that the limit of detection was ca. ten times larger than that in propylene carbonate since ammonia in propylene carbonate might be more soluble in comparison with RTILs when considering the higher viscosity of RTILs.

Improved fault diagnosis in multivariate systems using regression-based reconstruction

Subspace monitoring has recently been proposed as a condition monitoring tool that requires considerably fewer variables to be analysed compared to dynamic principal component analysis (PCA). This paper analyses subspace monitoring in identifying and isolating fault conditions, which reveals that the existing work suffers from inherent limitations if complex fault senarios arise. Based on the assumption that the fault signature is deterministic while the monitored variables are stochastic, the paper introduces a regression-based reconstruction technique to overcome these limitations. The utility of the proposed fault identification and isolation method is shown using a simulation example and the analysis of experimental data from an industrial reactive distillation unit.

A Scalable and Programmable Modular Traffic Manager Architecture

A key issue in the design of next generation Internet routers and switches will be provision of traffic manager (TM) functionality in the datapaths of their high speed switching fabrics. A new architecture that allows dynamic deployment of different TM functions is presented. By considering the processing requirements of operations such as policing and congestion, queuing, shaping and scheduling, a solution has been derived that is scalable with a consistent programmable interface. Programmability is achieved using a function computation unit which determines the action (e.g. drop, queue, remark, forward) based on the packet attribute information and a memory storage part. Results of a Xilinx Virtex-5 FPGA reference design are presented.