Simulation-based support tool for operator performance in batch manufacturing

In industry, the workload and utilization of shop floor operators is often misunderstood. In this paper, we will present several real case studies, using Discrete Event Simulation (DES) models, which allow us to better understand operators in a batch manufacturing environment. The first study investigates labour in a machining plant consisting of multiple identical CNC machines that batch produce parts. The second study investigates labour in an eight station, gravity die casting rotary table. The results from these studies have shown that there can be potential improvements made by the production planners in the current labour configuration. In the first case study, a matrix is produced that estimates what the operator's utilization levels will be for various configurations. From this, the preferred operator to machine ratio over a range of cycle times is presented. In the second study, the results have shown that by reducing the casting cycle time, the operator would be overloaded. A discrete event simulation of these two cases highlighted areas that were misunderstood by plant management, and provided them with a useful decision support tool for production planning.

A decision support tool for resource allocation in batch manufacturing

A decision support tool for production planning is discussed in this paper to perform the job of machine grouping and labour allocation within a machining line. The production plans within the industrial partner have been historically inefficient because the relationship between the cycle times, the machine group size, and the operator's utilisation hasn't been properly understood. Starting with a simulation model, a rule-base has been generated to predict the operator's utilisation for a range of production settings. The resource allocation problem is then solved by breaking the problem into a series of smaller sized tasks. The objective is to minimise the number of operators and the difference between the maximum and minimum cycle times of machines within each group. The results from this decision support tool is presented for the particular case study.

Decision support tool for production planning of a machining line

A decision support tool for production planning was developed to perform the difficult and time consuming task of allocating resources within the industrial partner's machining line, consisting of identical Computerized Numerically Controlled machines. The production-planning tool identified significant labour savings in a number of the industrial partner's production plans.

Virtual melawati : 3D GIS as a decision support tool for urban planning

Virtual Melawati is an environment for developing expertise in the application of 3D interactive visualization and GIS (Geographic Information System) to address problems of the built environment and to test the model as a decision support tool in the context of the local planning authorities in Malaysia. The visual approach enables the integration of highly complex spatial GIS information such as the evolution and transformation of the urban precinct as well as the impact of planned developments into the decision making process. The study will examine the techniques of data acquisition, data reconstruction from physical to digital, urban analysis and visualization in constructing an interactive 3D GIS model to support and assist the decision making process in urban design and planning. The outcomes of the study will deliver an experimental test bed for improving decision making processes in urban planning and design utilizing 3D modeling and GIS. The project will accelerate the uptake of digital and multimedia methods in local government, facilitate current planning and consultation processes between councils and stakeholders and improve the dissemination and management of spatial information about urban environments.

Virtual Werribee : a planning support tool

Virtual Werribee is collaborative research in applying 3-D modelling and visualisation as a planning support tool in comparison to 2-D plans and drawings. It was a joint initiative involving Deakin University and the Wyndham City Council to demonstrate the use of 3-D visualisation for planning process in the actual context of a planning authority in Australia. The objective of this project was to assist the council in preparing for the revised Local Structure Plan. By reconstructing the council’s data into easily understood information, 3-D model and visualisation served as a verification and discussion tool for decision making. The integration of wider site context also provided a better understanding of the surrounding development areas. This could equip other stakeholders as well as the community to participate in council’s planning agenda activities, such as increasing the urban density and building heights limit.

Virtual Werribee included the development planning agenda, categorised as new, re-development and hypothetical. The modelling process progressed with sufficient data from the council. Some changes to the initial plan were made, including the use of CAD modelling software instead of GIS software, and production of a block model with selected detail buildings, instead of a full draped 3-D model. The council decided that the block model would be sufficient for their planning purposes. This was determined while taking into consideration the available facilities at the council.

The potentials of the model as a planning tool were demonstrated in this paper, and further compared to the council’s existing materials prepared by the project developers. The advantages of the 3-D interactive model and visualisation over the conventional materials have provided the council officer with a tool for better empowerment in the planning process. This was also evident in the increasing engagement level between the officer and the model as the process developed. As a result of this, the project scope has also expanded, finally covering the entire city.

While Virtual Werribee has the potential to better communicate council’s planning agendas to the stakeholders and the community, the key factor, coupled with its visualisation components, was its interactive capability. Property layers with aerial site image that provided a realistic background served as a virtual city platform for different users. Although limited in its analytic capability found in GIS software, this model offered high visualisation content to assist visual impact assessment through its interactive mode along with a series of still images and a simulation movie.

Investigating the efficacy of an intelligent operation planning and support tool for acute healthcare contexts

Nurses are the largest group of healthcare professionals in hospitals providing 24-hour care to patients. Hence, nurses are pivotal in coordinating and communicating patient care information in the complex network of healthcare professionals, services and other care processes. Yet, despite nurses' central role in health care delivery, intelligent systems have historically rarely been designed around nurses' operational needs. This could explain the poor integration of technologies into nursing work processes and consequent rejection by nursing professionals. The complex nature of acute care delivery in hospitals and the frequently interrupted patterns of nursing work suggest that nurses require flexible intelligent systems that can support and adapt to their variable workflow patterns. This study is designed to explore nurses' initial reactions to a new intelligent operational planning and support tool (IOPST) for acute healthcare. The following reports on the first stage of a longitudinal project to use an innovative approach involving nurses in the development of the IOPST; from conceptualization to implementation.

Optimizing safety, fidelity and usability of an Intelligent Clinical Support Tool (ICST) for acute hospital care: an Australian case study using a multi-method Delphi Process

This research focuses on a major health priority for Australia by addressing existing gaps in the implementation of nursing informatics solutions in healthcare. It serves to inform the successful deployment of IT solutions designed to support patient-centered, frontline acute healthcare delivery by multidisciplinary care teams. The outcomes can guide future evaluations of the contribution of IT solutions to the efficiency, safety and quality of care delivery in acute hospital settings.

Optimising safety, fidelity and usability of an Intelligent Clinical Support Tool (ICST) for acute hospital care: an Australian case Study using a multi-method Delphi process

This research focuses on a major health priority for Australia by addressing existing gaps in the implementation of nursing informatics solutions in healthcare. It serves to inform the successful deployment of IT solutions designed to support patient-centered, frontline acute healthcare delivery by multidisciplinary care teams. The outcomes can guide future evaluations of the contribution of IT solutions to the efficiency, safety and quality of care delivery in acute hospital settings.

An early-stage design decision-support tool for selecting building assemblies to minimise a building's life cycle energy demand

The significant effects of the building industry on the natural environment are well documented and improving the environmental performance of buildings is an on-going challenge. This is particularly the case for projects with restrictive budgets and timelines and because many existing environmental assessment tools are designed to be used too late in the design process. The use of tools during the early design stages may assist in achieving greater improvements in a building’s environmental performance. However, user-friendly tools with the ability to comprehensively compare environmental information between various building assemblies and materials, which can be easily adopted during the early design stages of a project, are not readily available. This paper presents the progress to date in developing a tool which supports building designers in identifying and selecting preferred building assemblies with the aim of minimising a building’s life cycle energy demand. The tool is based on comprehensive energy performance data for a broad range of building assemblies across all Australian climate zones. Allowing for adjustments to a set of pre-defined and user-defined assemblies the designer is able to see how assemblies perform in relation to each other. This provides valuable information to support decision-making relating to minimising the life cycle energy demand of buildings.

iPrevent®: a tailored, web-based, decision support tool for breast cancer risk assessment and management

We aimed to develop a user-centered, web-based, decision support tool for breast cancer risk assessment and personalized risk management. Using a novel model choice algorithm, iPrevent(®) selects one of two validated breast cancer risk estimation models (IBIS or BOADICEA), based on risk factor data entered by the user. Resulting risk estimates are presented in simple language and graphic formats for easy comprehension. iPrevent(®) then presents risk-adapted, evidence-based, guideline-endorsed management options. Development was an iterative process with regular feedback from multidisciplinary experts and consumers. To verify iPrevent(®), risk factor data for 127 cases derived from the Australian Breast Cancer Family Study were entered into iPrevent(®), IBIS (v7.02), and BOADICEA (v3.0). Consistency of the model chosen by iPrevent(®) (i.e., IBIS or BOADICEA) with the programmed iPrevent(®) model choice algorithm was assessed. Estimated breast cancer risks from iPrevent(®) were compared with those attained directly from the chosen risk assessment model (IBIS or BOADICEA). Risk management interventions displayed by iPrevent(®) were assessed for appropriateness. Risk estimation model choice was 100 % consistent with the programmed iPrevent(®) logic. Discrepant 10-year and residual lifetime risk estimates of >1 % were found for 1 and 4 cases, respectively, none was clinically significant (maximal variation 1.4 %). Risk management interventions suggested by iPrevent(®) were 100 % appropriate. iPrevent(®) successfully integrates the IBIS and BOADICEA risk assessment models into a decision support tool that provides evidence-based, risk-adapted risk management advice. This may help to facilitate precision breast cancer prevention discussions between women and their healthcare providers.

Producing a GIS based multiple criteria analysis tool for regional sustainability assessment: the problem of weighting

Decision support tools will be useful in guiding regions to sustainability. These need to be simple but effective at identifying, for regional managers, areas most in need of initiatives to progress sustainability. Multiple criteria analysis (MCA) is often used as a decision support tool for a wide range of applications. This method allows many criteria to be considered at one time. It does this by giving a ranking of possible options based on how closely each option meets the criteria. Thus, it is suited to the assessment of regional sustainability as it can consider a number of indicators simultaneously and demonstrates how sustainability can vary at small scales across the region. Coupling MCA with GIS to produce maps, allows this analysis to become visual giving the manager a picture of sustainability across the region. To do this each indicator is standardised to a common scale so that it can be compared to other indicators. A weighting is then applied to each indicator to calculate weighted summation for each area in the region. This paper argues that this is the critical step in developing a useful decision support tool. A study being conducted in south west Victoria demonstrates that the weights chosen can have a dramatic impact on the results of the sustainability assessment. It is therefore imperative that careful consideration be given to determining indicator weights in a way that is objective and fully considers the impact of that indicator on regional sustainability.

Support needs of parents of sick and/or preterm infants admitted to a neonatal unit

Background: The sudden unexpected delivery of a preterm infant is a shock to parents with studies confirming the importance of providing them with nursing support. The purpose of this descriptive study was to identify the type and level of support that nurses provided to the parents of sick and/or preterm infants. It also investigated whether parents were satisfied with the support provided by nursing staff.
Method: A convenience sample of 112 parents in an Australian tertiary neonatal unit were invited to complete the ‘Nurse Parent Support Tool’ (NPST), which is a 21-item questionnaire. The NPST consists of four domains: emotional, informational, appraisal and instrumental support. A second tool was used to assess parents’ satisfaction with the nurse to parent support.
Results: Instrumental support had the highest mean score for both nurse to parent support at 4.51 (out of 5) and 4.36 (out of 5) for satisfaction. The mean score for nursing support was 4.21 followed by parental satisfaction with nurse to parent support which was 4.16. In contrast, emotional support had the lowest mean score for both nurse to parent support at 3.94 and 3.97 for satisfaction. Parents indicated that they needed further support with lactation, breastfeeding and assistance with parenting skills.
Conclusion: Overall, the results from the study indicated that parents’ perception of nursing support was positive and that parents were highly satisfied with the nursing support provided in the neonatal unit. However, some attention needs to be given to providing more support and information on breastfeeding and parenting skills.