A case for an international consortium on system-of-systems engineering

A system-of-systems (SoS) conceptualization is essential in resolving issues involving heterogeneous independently operable systems to achieve a unique purpose. Successful operation as an SoS requires communication among appropriate individuals and groups across enterprises through an effective protocol. This paper presents a position on the creation of a consortium of concerned system engineers and scientists worldwide to examine the problems and solutions strategies associated with SoS. The consortium could lead efforts in clarifying ambiguities and in seeking remedies to numerous open questions with respect to SoS analysis, SoS engineering (SoSE), as well as differences between systems engineering (SE) and SoSE. The mission of this consortium is envisioned to: 1) act as a neutral party; 2) provide a forum to put forth Calls to Action; and 3) establish a community of interest to recommend a set of solutions.

Factories of the future : a system of systems engineering perspective

Factories of the Future will be distinguished by intelligent machines, automation, human factors integration and knowledge management. Modelling and simulation is recognised as a key enabling technology essential to economic, social and environmental sustainability of future manufacturing systems. This talk will explore the history, recent achievements and directions in modelling and simulation for 21st century factories and supply chains. A systems science approach is employed, from stakeholder engagement through participative modelling to self-tuning and self-assembling simulations. Our contributions lower the cost of the application of modelling and simulation to manufacturing processes, enabling real time planning, dynamic risk analysis, dashboards and 3D visualisation. This realisation of the virtual factory integrates human factors and decisions into the core technology platform. The implications to future manufacturing enterprises are explored through a series of case studies from aerospace, mining and small and medium manufacturing enterprises.

Future integrated factories: a system of systems engineering perspective

The manufacturing sector has gone through tremendous change in the last decade. We have witnessed the transformation from stand alone, manual processes to smart and integrated systems, from hand written reports to interactive computer-based dashboards. Future integrated factories will operate as a system of systems through intelligent machines, human factors integration, and integrated supply chains. To effectively operate and manage these emerging enterprises, a systems science approach is required. Modelling and simulation is recognised as a key enabling technology, with application from stakeholder engagement and knowledge elicitation to operational decision support through self-tuning and self-assembling simulations. Our research has led to the introduction of effective modelling and simulation methods and tools to enable real time planning, dynamic risk analysis and effective visualisation for production processes, resources and systems. This paper discusses industrial applicable concepts for real-time simulation and decision support, and the implications to future integrated factories, or factories of the future, are explored through relevant case studies from aerospace manufacturing to mining and materials processing enterprises.

A common functional observer scheme for three systems with unknown inputs

This paper presents a novel common functional observer scheme for three systems with unknown inputs. The scheme uses three observers in cascade with two logic switches. The existence conditions of the scheme are investigated and presented in terms of the original system matrices. Significantly, the conditions allow the observers to be designed independently of each other which greatly simplify the design process, and also serve as a basis of comparison for future development of common functional observer schemes. A numerical example is given to illustrate the effectiveness of the proposed scheme.

A transformation technique to estimate the process capability index for non-normal processes

Estimating the process capability index (PCI) for non-normal processes has been discussed by many researches. There are two basic approaches to estimating the PCI for non-normal processes. The first commonly used approach is to transform the non-normal data into normal data using transformation techniques and then use a conventional normal method to estimate the PCI for transformed data. This is a straightforward approach and is easy to deploy. The alternate approach is to use non-normal percentiles to calculate the PCI. The latter approach is not easy to implement and a deviation in estimating the distribution of the process may affect the efficacy of the estimated PCI. The aim of this paper is to estimate the PCI for non-normal processes using a transformation technique called root transformation. The efficacy of the proposed technique is assessed by conducting a simulation study using gamma, Weibull, and beta distributions. The root transformation technique is used to estimate the PCI for each set of simulated data. These results are then compared with the PCI obtained using exact percentiles and the Box-Cox method. Finally, a case study based on real-world data is presented.

A transformation-based multivariate chart to monitor process dispersion

Multivariate monitoring techniques such as multivariate control charts are used to control the processes that contain more than one correlated characteristic. Although the majority of previous researches are focused on controlling only the mean vector of multivariate processes, little work has been performed to monitor the covariance matrix. In this research, a new method is presented to detect possible shifts in the covariance matrix of multivariate processes. The basis of the proposed method is to eliminate the correlation structure between the quality characteristics by transformation technique and then use an S chart for each variable. The performance of the proposed method is then compared to the ones from other existing methods and a real case is presented.

A note on multivariate non-normal process capability analysis using "mvtnorm" library in R

In this note we examine using Genzbretz and Miwa algorithms to improve estimation of proposition of non-conformance in multivariate normal distributions. This estimation is required in the procedure outlined in Abbasi and Niaki (Int J Adv Manuf Technol 50(5-8):823-830, 2010) to determine process capability index of multivariate non-normal processes.

Layered fragment architecture for situational methodology engineering

Many organizations make use of information system development methodologies to guide their staff in developing computerised information systems. This thesis contributes to methodology engineering research by introducing a number of important innovations in methodology fragment architectures.

Improved GART neural network model for pattern classification and rule extraction with application to power systems

Generalized adaptive resonance theory (GART) is a neural network model that is capable of online learning and is effective in tackling pattern classification tasks. In this paper, we propose an improved GART model (IGART), and demonstrate its applicability to power systems. IGART enhances the dynamics of GART in several aspects, which include the use of the Laplacian likelihood function, a new vigilance function, a new match-tracking mechanism, an ordering algorithm for determining the sequence of training data, and a rule extraction capability to elicit if-then rules from the network. To assess the effectiveness of IGART and to compare its performances with those from other methods, three datasets that are related to power systems are employed. The experimental results demonstrate the usefulness of IGART with the rule extraction capability in undertaking classification problems in power systems engineering.

Aligning students and staff perspectives in an engineering design curriculum

This paper focuses on the alignment of students and staff perspectives in an engineering design curriculum. Deakin University recognised the importance of student learning with engagement in design-centred education. Staff across the university are committed to ensure that students are engaged at a fairly deep learning level. Engaging students is an important aspect of learning and teaching process because it enhances the student to be self directed active learners. To measure the student engagement and staff experiences in learning and teaching process, Deakin engineering has used design based learning as one of its engineering learning principle. This study examines students perceptions of DBL in their curriculum through a paper based survey given to a cohort of senior year undergraduate engineering students. The research also illustrates the staff perceptions of DBL in engineering curriculum by conducting face-to-face interviews with them. From the analysed results, this research shows that the students and staff have an adequate experience of learning and teaching engineering through design based learning approach in an engineering design curriculum.

Protecting and promoting mental health in the workplace : developing a systems approach to job stress

Issue addressed: Job stress has been linked to a wide range of adverse effects on mental, physical, and organisational health. Despite the evidence that systems approaches are most effective in reducing the adverse impact of job stress, prevalent practice is dominated by worker- or individual-focused strategies in the absence of commensurate intervention on working conditions. Methods: A literature review and cross-disciplinary conceptual synthesis were combined in the articulation of a systems approach to job stress. Results: An outline of the job stress process is followed by explanation of how a systems approach addresses the various steps in the stress process. Systems approaches to job stress emphasise primary prevention or focusing on stressors as the upstream determinants of job stress. Additionally, systems approaches integrate primary with worker-directed secondary and illness-directed tertiary intervention, include the meaningful participation of groups targeted by intervention, and are context- sensitive. Systems approach intervention principles are illustrated by concrete examples of intervention strategies and activities. Conclusions: Further efforts are needed to promote, disseminate, implement, and evaluate systems approaches to job stress and to improve cross-disciplinary cooperation in this effort. (author abtract)